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Africa

June 2023

DOI:10.1017/9781009325844.011

In book: Climate Change 2022 – Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp.1285-1456)
Edition: 6
Chapter: 9
Publisher: Cambridge University Press

Authors:

Ibidun O. Adelekan

University of Ibadan

Edmond Totin

Université d'Agriculture de Kétou

Ayansina Ayanlade

Obafemi Awolowo University

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The Working Group II contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) provides a comprehensive assessment of the scientific literature relevant to climate change impacts, adaptation and vulnerability. The report recognizes the interactions of climate, ecosystems and biodiversity, and human societies, and integrates across the natural, ecological, social and economic sciences. It emphasizes how efforts in adaptation and in reducing greenhouse gas emissions can come together in a process called climate resilient development, which enables a liveable future for biodiversity and humankind. The IPCC is the leading body for assessing climate change science. IPCC reports are produced in comprehensive, objective and transparent ways, ensuring they reflect the full range of views in the scientific literature. Novel elements include focused topical assessments, and an atlas presenting observed climate change impacts and future risks from global to regional scales. Available as Open Access on Cambridge Core.

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SPM

1285

9Africa

Coordinating Lead Authors: Christopher H. Trisos (South Africa), Ibidun O. Adelekan (Nigeria),

Edmond Totin (Benin)

Lead Authors: Ayansina Ayanlade (Nigeria), Jackson Eﬁtre (Uganda), Adugna Gemeda (Ethiopia),

Kanungwe Kalaba (Zambia), Christopher Lennard (South Africa), Catherine Masao (Tanzania),

Yunus Mgaya (Tanzania), Grace Ngaruiya (Kenya), Daniel Olago (Kenya), Nicholas P. Simpson

(Zimbabwe/South Africa), Sumaya Zakieldeen (Sudan)

Contributing Authors: Philip Antwi-Agyei (Ghana), Aaron Atteridge (Sweden/Australia), Rachel

Bezner-Kerr (Canada/USA), Timothy Breitbarth (USA/South Korea), Max Callaghan (UK/Germany),

Tamma Carleton (USA), Colin Carlson (USA), Hayley Clements (South Africa), Declan Conway

(UK), Sean Cooke (South Africa), Matthew Chersich (South Africa), David Chiawo (Kenya), Romy

Chevalier (South Africa), Joanne Clarke (Australian/UK), Marlies Craig (South Africa), Olivier Crespo

(South Africa), James Cullis (South Africa), Jampel Dell’Angelo (Italy/USA), Luleka Dlamini (South

Africa) Hussen Seid Endris (Kenya), Christien Engelbreht (South Africa), Aidan Farrell (Trinidad

and Tobago/Ireland), James Franke (USA), Thian Yew Gan (Malaysia/Canada), Christopher Golden

(USA), Kerry Grey (South Africa), Toshihiro Hasegawa (Japan), Ryan Hogarth (Canada/UK), Hassan

O. Kaya (South Africa), Nadia Khalaf (UK), Mercy Kinyua (Kenya), Scott Kulp (USA), William F.

Lamb (UK/Germany), Charne Lavery (South Africa), Johan Maritz (South Africa), Guy Midgley

(South Africa), Danielle Millar (South Africa), Jan Minx (Germany), Glenn Moncrieff (South

Africa), Rachid Moussadek (Morocco), Mzime Ndebele-Murisa (Zimbabwe), Emily Nicklin (South

Africa), Michelle North (South Africa), Mary Nyasimi (Kenya), Elizabeth Nyboer (Canada), Romaric

Odoulami (Benin/South Africa), Andrew Okem (South Africa/Nigeria), Gladys Okemwa (Kenya),

Kulthoum Omari (Botswana/South Africa), Esther Onyango (Kenya/Australia), Birgitt Ouweneel

(the Netherlands/South Africa), Indra Øverland (Norway), Lorena, Pasquini (South Africa), Laura

Pereira (South Africa), Belynda Petrie (South Africa), Alex Pigot (UK), Wilfried Pokam (Cameroon),

Bronwen Powell (Canada/USA), Jeff Price (UK), Heather Randell (USA), Maren Radeny (Kenya),

Jonathan Rawlins (South Africa), Kanta Kumari Rigaud (Malaysia/USA), Carla Roncoli (USA),

Olivia Rumble (South Africa), Elisa Sainz de Murieta (Spain), Georgia Savvidou (Sweden/Cyprus),

Lucia Schlemmer (South Africa), Laura Schmitt Olabisi (USA), Chandni Singh (India), Thomas

Smucker (USA), Nicola Stevens (South Africa), Anna Steynor (South Africa), Bamba Sylla (Rwanda/

Senegal), Arame Tall (Senegal/USA), Richard Taylor (Canada/UK), Meryem Tenarhte (Morocco/

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Chapter 9 Africa

Germany), Mia Thom (South Africa), Jessica Thorn (Namibia/South Africa), Maria Tirado (USA/

SPAIN), Katharina Waha (Germany/Australia), Hitomi Wakatsuki (Japan), Edna Wangui (Kenya/

USA), Portia Adade Williams (Ghana), Kevin Winter (South Africa), Caradee Wright (South Africa),

Luckson Zvobgo (Zimbabwe/South Africa)

Review Editors: Stuart Mark Howden (Australia), Robert (Bob) J. Scholes (South Africa), Pius

Yanda (Tanzania)

Chapter Scientists: Michelle North (South Africa), Luckson Zvobgo (Zimbabwe/South Africa)

This chapter should be cited as:

Trisos, C.H., I.O. Adelekan, E. Totin, A. Ayanlade, J. Eﬁtre, A. Gemeda, K. Kalaba, C. Lennard, C. Masao, Y. Mgaya,

G. Ngaruiya, D. Olago, N.P. Simpson, and S. Zakieldeen, 2022: Africa. In: Climate Change 2022: Impacts, Adaptation

and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel

on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig,

S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press, Cambridge, UK and New York,

NY, USA, pp. 1285–1455, doi:10.1017/9781009325844.011.

Africa Chapter 9

Table of Contents

Executive Summary �� 1289

9.1 Introduction �� 1294

9.1.1 Point of Departure �� 1294

9.1.2 Major Conclusions from Previous Assessments 1294

9.1.3 What’s New on Africa in AR6? �� 1295

9.1.4 Climate Change Impacts Across Africa �� 1298

9.1.5 Climate Data and Research Gaps Across Africa 1298

9.1.6 Loss and Damage from Climate Change �� 1299

9.2 Key Risks for Africa �� 1299

9.3 Climate Adaptation Options �� 1301

9.3.1 Adaptation Feasibility and Effectiveness �� 1301

9.3.2 Adaptation Co-Beneﬁts and Trade-Offs with

Mitigation and SDGs �� 1304

9.4 Climate Resilient Development �� 1304

9.4.1 Climate Finance �� 1305

9.4.2 Governance �� 1309

9.4.3 Cross-sectoral and Transboundary Solutions �� 1310

9.4.4 Climate Change Adaptation Law in Africa �� 1312

9.4.5 Climate Services, Perception and Literacy �� 1313

Box9.1 | Vulnerability Synthesis �� 1318

9.5 Observed and Projected Climate Change �� 1320

9.5.1 Climate Hazards in Africa �� 1320

9.5.2 North Africa �� 1322

9.5.3 West Africa �� 1325

9.5.4 Central Africa �� 1326

9.5.5 East Africa �� 1327

9.5.6 Southern Africa �� 1328

9.5.7 Tropical Cyclones �� 1329

9.5.8 Glaciers �� 1329

9.5.9 Teleconnections and Large-Scale Drivers of

African Climate Variability �� 1329

9.5.10 African Marine Heatwaves �� 1329

Box9.2 | Indigenous knowledge and local

knowledge �� 1330

9.6 Ecosystems �� 1332

9.6.1 Observed Impacts of Climate Change on African

Biodiversity and Ecosystem Services �� 1332

9.6.2 Projected Risks of Climate Change for African

Biodiversity and Ecosystem Services �� 1334

9.6.3 Nature-based Tourism in Africa �� 1338

9.6.4 Ecosystem-based Adaptation in Africa �� 1339

Box9.3 | Tree planting in Africa �� 1341

9.7 Water �� 1342

9.7.1 Observed Impacts from Climate Variability

and Climate Change �� 1342

Box9.4 | African cities facing water scarcity �� 1343

9.7.2 Projected Risks and Vulnerability �� 1344

9.7.3 Water Adaptation Options and Their Feasibility 1346

Box9.5 | Water–energy–food nexus �� 1347

9.8 Food Systems �� 1349

9.8.1 Vulnerability to Observed and Projected Impacts

from Climate Change �� 1350

9.8.2 Observed Impacts and Projected Risks to Crops

and Livestock �� 1350

9.8.3 Adapting to Climate Variability and Change

in Agriculture �� 1356

9.8.4 Climate Information Services and Insurance

for Agriculture Adaptation �� 1357

9.8.5 Marine and Inland Fisheries �� 1357

9.9 Human Settlements and Infrastructure �� 1360

9.9.1 Urbanisation, Population and Development

Trends �� 1360

9.9.2 Observed Impacts on Human Settlements and

Infrastructure �� 1360

9.9.3 Observed Vulnerabilities of Human Settlements

to Climate Risks �� 1363

9.9.4 Projected Risks for Human Settlements and

Infrastructure �� 1363

9.9.5 Adaptation in Human Settlements and for

Infrastructure �� 1368

9.10 Health �� 1371

9.10.1 The Inﬂuence of Social Determinants of Health

on the Impacts of Climate Change �� 1371

9.10.2 Observed Impacts and Projected Risks �� 1372

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Chapter 9 Africa

Box9.6 | Pandemic risk in Africa: COVID-19 and future

threats �� 1375

Box9.7 | The health–climate change nexus in

Africa �� 1380

9.10.3 Adaptation for Health and Well-being in Africa 1380

9.11 Economy, Poverty and Livelihoods �� 1385

9.11.1 Observed Impacts of Climate Change on African

Economies and Livelihoods �� 1385

9.11.2 Projected Risks of Climate Change for African

Economies and Livelihoods �� 1387

9.11.3 Informality �� 1387

9.11.4 Climate Change Adaptation to Reduce

Vulnerability, Poverty and Inequality �� 1388

9.11.5 COVID-19 Recovery Stimulus Packages for

Climate Action �� 1390

Box9.8 | Climate change, migration and displacement

in Africa �� 1391

9.12 Heritage �� 1393

9.12.1 Observed Impacts on Cultural Heritage. �� 1393

Box9.9 | Climate Change and Security: Interpersonal

Violence and Large-scale Civil Conﬂict �� 1394

9.12.2 Projected Risks �� 1395

9.12.3 Adaptation �� 1396

Frequently Asked Questions

FAQ 9.1 | Which climate hazards impact African

livelihoods, economies, health and well-being the

most? �� 1399

FAQ 9.2 | What are the limits and beneﬁts of climate

change adaptation in Africa? �� 1401

FAQ 9.3 | How can African countries secure enough

food in changing climate conditions for their growing

populations? �� 1401

FAQ 9.4 | How can African local knowledge serve

climate adaptation planning more effectively? �� 1402

References �� 1403

1289

Africa Chapter 9

Executive Summary

Overall Key Messages

Africa is one of the lowest contributors to greenhouse gas

emissions causing climate change, yet key development sectors

have already experienced widespread losses and damages

attributable to human-induced climate change, including

biodiversity loss, water shortages, reduced food production,

loss of lives and reduced economic growth (high conﬁdence1).

{9.1.1, 9.1.6, 9.2, 9.6.1, 9.8.2, 9.10.2, 9.11.1, Box9.4}

Between 1.5°C and 2°C global warming—assuming localised

and incremental adaptation—negative impacts are projected

to become widespread and severe with reduced food

production, reduced economic growth, increased inequality

and poverty, biodiversity loss, increased human morbidity

and mortality (high conﬁdence). Limiting global warming

to 1.5°C is expected to substantially reduce damages to

African economies, agriculture, human health, and ecosystems

compared to higher levels of global warming (high conﬁdence).

{9.2, 9.6.2, 9.8.2, 9.8.5, 9.10.2, 9.11.2}

Exposure and vulnerability to climate change in Africa

are multi-dimensional with socioeconomic, political and

environmental factors intersecting (very high conﬁdence).

Africans are disproportionately employed in climate-exposed sectors:

55–62% of the sub-Saharan workforce is employed in agriculture and

95% of cropland is rainfed. In rural Africa, poor and female-headed

households face greater livelihood risks from climate hazards. In urban

areas, growing informal settlements without basic services increase

the vulnerability of large populations to climate hazards, especially

women, children and the elderly. {9.8.1, 9.9.1, 9.9.3, 9.11.4, Box9.1}

Adaptation in Africa has multiple beneﬁts, and most assessed

adaptation options have medium effectiveness at reducing

risks for present-day global warming, but their efﬁcacy at

future warming levels is largely unknown (high conﬁdence).

{9.3, 9.6.4, 9.8.3, 9.11.4}

Enabling Climate Resilient Development

Climate-related research in Africa faces severe data constraints,

as well as inequities in funding and research leadership that

reduces adaptive capacity (very high conﬁdence). Many countries

lack regularly reporting weather stations, and data access is often

limited. From 1990–2019, research on Africa received just 3.8% of

climate-related research funding globally: 78% of this funding for

Africa went to EU and north American institutions and only 14.5% to

African institutions. The number of climate research publications with

locally based authors are among the lowest globally and research led

by external researchers may focus less on local priorities. Increased

funding for African partners, and direct control of research design and

1 In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, medium, or high. A level of conﬁdence is

expressed using ﬁve qualiﬁers: very low, low, medium, high, and very high, and typeset in italics, e.g., medium conﬁdence. For a given evidence and agreement statement, different conﬁdence levels

can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing conﬁdence.

resources can provide more actionable insights on climate risks and

adaptation options in Africa. {9.1,5 9.4.5, 9.5.2}

Adaptation generally is cost-effective, but annual ﬁnance

ﬂows targeting adaptation for Africa are billions of US dollars

less than the lowest adaptation cost estimates for near-term

climate change (high conﬁdence). Finance has not targeted more

vulnerable countries (high conﬁdence). From 2014–2018 more ﬁnance

commitments were debt than grants and—excluding multilateral

development banks—only 46% of commitments were disbursed

(compared to 96% for other development projects). {9.4.1}

Adaptation costs will rise rapidly with global warming (very

high conﬁdence). Increasing public and private ﬁnance ﬂows

by billions of dollars per year, increasing direct access to

multilateral funds, strengthening project pipeline development

and shifting more ﬁnance to project implementation would help

realise transformative adaptation in Africa (high conﬁdence).

Concessional ﬁnance will be required for adaptation in low-income

settings (high conﬁdence). Aligning sovereign debt relief with climate

goals could increase ﬁnance by redirecting debt-servicing payments to

climate resilience. {9.4.1}

Governance for climate resilient development includes long-

term planning, all-of-government approaches, transboundary

cooperation and beneﬁt-sharing, development pathways that

increase adaptation and mitigation and reduce inequality, and

implementation of Nationally Determined Contributions (NDCs)

(high conﬁdence). {9.3.2, 9.4.2, 9.4.3}

Cross-sectoral ‘nexus’ approaches provide signiﬁcant oppor-

tunities for large co-beneﬁts and/or avoided damages (very

high conﬁdence). For example, climate change adaptation beneﬁts

pandemic preparedness, ‘One Health’ approaches beneﬁt human and

ecosystem health, and ecosystem-based adaptation can deliver adap-

tation and emissions mitigation (high conﬁdence). {9.4.3, 9.6.4, 9.11.5;

Box9.6}

Without cross-sectoral, transboundary and long-term planning,

adaptation and mitigation response options in one sector can

become response risks, exacerbating impacts in other sectors

and causing maladaptation (very high conﬁdence). For example,

maintaining indigenous forest beneﬁts biodiversity and reduces

greenhouse gas emissions, but afforestation—or wrongly targeting

ancient grasslands and savannas for reforestation—harms water

security and biodiversity, and can increase carbon loss to ﬁre and

drought. Planned hydropower projects may increase risk as rainfall

changes impact water, energy and food security, exacerbating trade-

offs between users, including across countries. {9.4.3, Boxes 9.3, 9.5}

Robust legislative frameworks that develop or amend laws to

mainstream climate change into their empowerment and plan-

ning provisions will facilitate effective design and implemen-

1290

Chapter 9 Africa

tation of climate change response options (high conﬁdence).

{9.4.4}

Climate information services that are demand driven and

context speciﬁc (e.g., for agriculture or health) combined with

climate change literacy can be the difference between coping

and informed adaptation responses (high conﬁdence). Across

33 African countries, 23–66% of people are aware of human-caused

climate change—with larger variation at sub-national scales (e.g.,

5–71% among states in Nigeria). Climate change literacy increases

with education level but is undermined by poverty, and literacy rates

average 12.8% lower for women than men. Around 71% of Africans

that are aware of climate change agree it should be stopped. Production

of salient climate information in Africa is hindered by limited availability

of and access to weather and climate data. {9.4.5, 9.5.1, 9.8.4, 9.10.3}

Ecosystem-based adaptation can reduce climate risk while

providing social, economic and environmental beneﬁts (high

conﬁdence). Direct human dependence on ecosystem services in

Africa is high. Ecosystem protection and restoration, conservation

agriculture practices, sustainable land management, and integrated

catchment management can support climate resilience. Ecosystem-

based adaptation can cost less than grey infrastructure in human

settlements (e.g., using wetlands and mangroves as coastal protection).

{9.6.4, 9.7.3, 9.8.3, 9.9.5, 9.12.3, Box9.7}

Observed Impacts and Projected Risks

Climate

Increasing mean and extreme temperature trends across

Africa are attributable to human-caused climate change (high

conﬁdence). {9.5.1, 9.5.2}

Climate change has increased heat waves (high conﬁdence)

and drought (medium conﬁdence) on land, and doubled the

probability of marine heatwaves around most of Africa (high

conﬁdence). Multi-year droughts have become more frequent in west

Africa, and the 2015–2017 Cape Town drought was three times more

likely2 due to human-caused climate change. {9.5.3–7, 9.5.10}

Increases in drought frequency and duration are projected over

large parts of southern Africa above 1.5°C global warming

(high conﬁdence), with decreased precipitation in North Africa

at 2°C global warming (high conﬁdence), and above 3°C global

warming, meteorological drought frequency will increase, and

duration will double from approximately 2 months to 4 months

in parts of North Africa, the western Sahel and southern Africa

(medium conﬁdence). {9.5.2, 9.5.3, 9.5.6.}

Frequency and intensity of heavy rainfall events will increase at

all levels of global warming (except in north and southwestern

2 In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result: Virtually certain 99–100% probability, Very likely 90–100%, Likely 66–100%, About as

likely as not 33–66%, Unlikely 0–33%, Very unlikely 0–10%, and Exceptionally unlikely 0–1%. Additional terms (Extremely likely: 95–100%, More likely than not >50–100%, and Extremely unlikely

0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely). This Report also uses the term ‘likely range’ to indicate that the assessed likelihood of an outcome

lies within the 17–83% probability range.

Africa), increasing exposure to pluvial and riverine ﬂooding

(high conﬁdence). {9.5.3–7, 9.7}

Glaciers on the Rwenzoris and Mt Kenya are projected to disappear

by 2030, and by 2040 on Kilimanjaro (medium conﬁdence). {9.5.8}

In east and southern Africa, tropical cyclones making landfall

are projected to become less frequent but have more intense

rainfall and higher wind speeds at increasing global warming

(medium conﬁdence). {9.5.7}

Heat waves on land, in lakes and in the ocean will increase

considerably in magnitude and duration with increasing global

warming (very high conﬁdence). Under a 1.5°C-compatible

scenario, children born in Africa in 2020 are likely to be exposed

to 4–8 times more heat waves compared to people born in 1960,

increasing to 5–10 times for 2.4°C global warming. The annual

number of days above potentially lethal heat thresholds reaches 50–

150 in west Africa at 1.6°C global warming, 100–150 in central Africa

at 2.5°C, and 200–300 over tropical Africa for >4°C. {9.5.2, 9.5.3,

9.5.4, 9.5.5, 9.5.6, 9.7.2.1}

Most African countries will enter unprecedented high temperature

climates earlier in this century than generally wealthier, higher

latitude countries, emphasising the urgency of adaptation

measures in Africa (high conﬁdence). {9.5.1}

Compound risks

Multiple African countries are projected to face compounding

risks from reduced food production across crops, livestock

and ﬁsheries, increased heat-related mortality, heat-related

loss of labour productivity and ﬂooding from sea level rise,

especially in west Africa (high conﬁdence). {9.8.2, 9.8.5, 9.9.4,

9.10.2, 9.11.2}

Water

Recent extreme variability in rainfall and river discharge

(around −50% to +50% relative to long-term historical means)

across Africa have had largely negative and multi-sector

impacts across water-dependent sectors (high conﬁdence).

{9.7.2, 9.10.2} Hydrological variability and water scarcity have induced

cascading impacts from water supply provision and/or hydroelectric

power production to health, economies, tourism, food, disaster risk

response capacity and increased inequality of water access. {Box9.4}

Extreme hydrological variability is projected to progressively

amplify under all future climate change scenarios relative to

the current baseline, depending on region (high conﬁdence).

Projections of numbers of people exposed to water stress by the 2050s

vary widely—decreases/increases by hundreds of millions, with higher

numbers for increases—with disagreement among global climate

1291

Africa Chapter 9

models on the major factor driving these large ranges. Populations in

drylands are projected to double by 2050. Projected changes present

heightened cross-cutting risks to water-dependent sectors, and require

planning under deep uncertainty for the wide range of extremes

expected in future. {9.7.1, 9.7.2, 9.9.4}

Economy and livelihoods

Climate change has reduced economic growth across Africa,

increasing income inequality between African countries

and those in temperate northern hemisphere climates (high

conﬁdence). One estimate suggests gross domestic product (GDP)

per capita for 1991–2010 in Africa was on average 13.6% lower

than if climate change had not occurred. Impacts manifest largely

through losses in agriculture, as well as tourism, manufacturing and

infrastructure. {9.6.3, 9.11.1}

Climate variability and change undermine educational attainment

(high agreement, medium evidence). High temperatures, low

rainfall and ﬂooding, especially in the growing season, may mean

children are removed from school to assist income generation. Early life

undernutrition associated with low harvests or weather-related food

supply interruptions can impair cognitive development. {9.11.1.2}

Limiting global warming to 1.5°C is very likely to positively

impact GDP per capita across Africa. Increasing economic damage

forecasts under high emissions diverge from low emission pathways

by 2030. Inequalities between African countries are projected to widen

with increased warming. Across nearly all African countries, GDP per

capita is projected to be at least 5% higher by 2050 and 10–20% higher

by 2100 if global warming is held to 1.5°C compared with 2°C. {9.11.2}

Food systems

In Africa, climate change is reducing crop yields and productivity

(high conﬁdence). Agricultural productivity growth has been reduced

by 34% since 1961 due to climate change, more than any other

region. Maize and wheat yields decreased on average 5.8% and 2.3%,

respectively in sub-Saharan Africa due to climate change in the period

1974–2008. Farmers and pastoralists perceive the climate to have

changed and over two-thirds of Africans perceive climate conditions for

agricultural production have worsened over the past 10years. Woody

plant encroachment has reduced fodder availability. {9.4.5, 9.6.1, 9.8.2}

Future warming will negatively affect food systems in Africa

by shortening growing seasons and increasing water stress

(high conﬁdence). By 1.5°C global warming, yields are projected

to decline for olives (north Africa) and sorghum (west Africa) with a

decline in suitable areas for coffee and tea (east Africa). Although yield

declines for some crops may be partially compensated by increasing

atmospheric CO2 concentrations, global warming above 2°C will result

in yield reductions for staple crops across most of Africa compared

to 2005 yields (e.g., 20–40% decline in west African maize yields),

even when considering adaptation options and increasing CO2

(medium conﬁdence). Relative to 1986–2005, global warming of 3°C

is projected to reduce labour capacity in agriculture by 30–50% in sub-

Saharan Africa. {9.8.2, 9.8.3, 9.11.2}

Climate change threatens livestock production across

Africa (high agreement, low evidence). Rangeland net primary

productivity is projected to decline 42% for west Africa by 2050 at 2°C

global warming. Vector-borne livestock diseases and the duration of

severe heat stress are both projected to become more prevalent under

warming. {9.8.2}

Climate change poses a signiﬁcant threat to African marine and

freshwater ﬁsheries (high conﬁdence). Fisheries provide the main

source of protein for approximately 200million people in Africa and

support the livelihoods of 12.3million people. At 1.5°C global warming,

marine ﬁsh catch potential decreases 3–41%, and decreases by 12–69%

at 4.3°C by 2081–2100 relative to 1986–2005 levels, with the highest

declines for tropical countries. Under 1.7°C global warming, reduced ﬁsh

harvests could leave 1.2–70million people in Africa vulnerable to iron

deﬁciencies, up to 188million for vitamin A deﬁciencies, and 285million

for vitamin B

and omega-3 fatty acids by mid-century. For inland

ﬁsheries, 55–68% of commercially harvested ﬁsh species are vulnerable

to extinction under 2.5°C global warming by 2071–2100. {9.8.5}

Health

Climate variability and change already negatively impacts the

health of tens of millions of Africans through exposure to non-

optimal temperatures and extreme weather, and increased

range and transmission of infectious diseases (high conﬁdence).

{9.10.1}

Mortality and morbidity will escalate with further global

warming, placing additional strain on health and economic

systems (high conﬁdence). Above 2°C of global warming, distribution

and seasonal transmission of vector-borne diseases is expected to

increase, exposing tens of millions more people, mostly in west, east

and southern Africa (high conﬁdence). Above 1.5°C risk of heat-related

deaths rises sharply (medium conﬁdence), with at least 15 additional

deaths per 100,000 annually across large parts of Africa, reaching

50–180 additional deaths per 100,000 people annually in regions

of North, West, and East Africa for 2.5°C, and increasing to 200–600

per 100,000 people annually for 4.4°C. Above 2°C global warming,

thousands to tens of thousands of additional cases of diarrhoeal

disease are projected, mainly in west, central and east Africa (medium

conﬁdence). These changes risk undermining improvements in health

from future socioeconomic development (high agreement, medium

evidence). {9.10.2, Fig.9.35}

Human settlements

Exposure of people, assets and infrastructure to climate hazards

is increasing in Africa compounded by rapid urbanisation,

infrastructure deﬁcit, and growing population in informal

settlements (high conﬁdence).

High population growth and urbanisation in low-elevation

coastal zones will be a major driver of exposure to sea level rise

in the next 50years (high conﬁdence). By 2030, 108–116million

people in Africa will be exposed to sea level rise (compared to

1292

Chapter 9 Africa

54million in 2000), increasing to 190–245million by 2060 (medium

conﬁdence). {9.9.1, 9.9.4}

Africa’s rapidly growing cities will be hotspots of risks from

climate change and climate-induced in-migration, which could

amplify pre-existing stresses related to poverty, informality,

social and economic exclusion, and governance (high conﬁdence).

Urban population exposure to extreme heat is projected to increase from

2billion person-days per year in 1985–2005 to 45billion person-days

by the 2060s (1.7°C global warming with low population growth) and

to 95 billion person-days (2.8°C global warming with medium-high

population growth), with greatest exposure in west Africa. Under relatively

low population growth scenarios, the sensitive populations (people under

5 or over 64years old) in African cities exposed to heat waves of at least

15days above 42°C in African cities is projected to increase from around

27 million in 2010 to 360 million by 2100 for 1.8°C global warming

(Shared Socioeconomic Pathway 1 (SSP1)) and 440million (SSP5) for

>4°C global warming. Compared to 2000, urbanisation is projected to

increase urban land extent exposed to arid conditions by around 700%

and exposure to high-frequency ﬂooding by 2600% across west, central

and east Africa by 2030. {9.9.1, 9.9.2, 9.9.4, Box9.8}

Migration

Most climate-related migration observed currently is within

countries or between neighbouring countries, rather than to

distant high-income countries (high conﬁdence). Urbanisation has

increased when rural livelihoods were negatively impacted by low rainfall.

Over 2.6 million and 3.4 million new weather-related displacements

occurred in sub-Saharan Africa in 2018 and 2019. {Box9.8}

Climate change is projected to increase migration, especially

internal and rural to urban migration (high agreement, medium

evidence). With 1.7°C global warming by 2050, 17–40million people

could migrate internally in sub-Saharan Africa, increasing to 56–

86million for 2.5°C (>60% in west Africa) due to water stress, reduced

crop productivity and sea level rise. This is a lower-bound estimate

excluding rapid-onset hazards such as ﬂoods and tropical cyclones.

{Box9.8}

Infrastructure

Climate-related infrastructure damage and repairs will be a

ﬁnancially signiﬁcant burden to countries (high conﬁdence).

Without adaptation, aggregate damages from sea level rise and coastal

extremes to 12 major African coastal cities in 2050 under medium and

high emissions scenarios will be USD65billion and USD86.5billion,

respectively. Potential costs of up to USD 183.6 billion may be

incurred through 2100 to maintain existing road networks damaged

from temperature and precipitation changes due to climate change.

Increased rainfall variability is expected to affect electricity prices in

countries highly dependent on hydropower. {9.9.4, Boxes 9.4, 9.5}

Ecosystems

Increasing CO2 levels and climate change are destroying marine

biodiversity, reducing lake productivity, and changing animal

and vegetation distributions (high conﬁdence). Impacts include

repeated mass coral bleaching events in east Africa, and uphill (birds)

or poleward (marine species) shifts in geographic distributions. For

vegetation, the overall observed trend is woody plant expansion,

particularly into grasslands and savannas, reducing grazing land and

water supplies. {9.6.1, 9.6.2, 9.8.2}

The outcome of the effect of the interaction of increasing

CO2 and aridity that operate in opposing directions on future

biome distributions is highly uncertain. Further increasing CO2

concentrations could increase woody plant cover, but increasing aridity

could counteract this, destabilising forest and peatland carbon stores

in central Africa (low conﬁdence). Changes in vegetation cover could

occur rapidly if tipping points are crossed {9.6.1, 9.6.2, 9.8.2}

African biodiversity loss is projected to be widespread and

escalating with every 0.5°C increase above present-day global

warming (high conﬁdence). Above 1.5°C, half of assessed species

are projected to lose over 30% of their population or area of suitable

habitat. At 2°C, 36% of freshwater ﬁsh species are vulnerable to

local extinction, 7–18% of terrestrial species assessed are at risk of

extinction, and over 90% of east African coral reefs are projected

to be destroyed by bleaching. Above 2°C, risk of sudden and severe

biodiversity losses becomes widespread in west, central and east

Africa. Climate change is also projected to change patterns of invasive

species spread. {9.6.2, Figure9.19}

Climate security

There is increasing evidence linking increased temperatures

and drought to conﬂict risk in Africa (high conﬁdence).

Agriculturally dependent and politically excluded groups are

especially vulnerable to drought-associated conﬂict risk. However,

climate is one of many interacting risk factors, and may explain

a small share of total variation in conﬂict incidence. Ameliorating

ethnic tensions, strengthening political institutions and investing in

economic diversiﬁcation could mitigate future impacts of climate

change on conﬂict. {Box9.9}

Heritage

African cultural heritage is already at risk from climate hazards,

including sea level rise and coastal erosion. Most African

heritage sites are neither prepared for, nor adapted to, future

climate change (high conﬁdence). {9.12}

Adaptation

With global warming increasing above present-day levels, the

ability of adaptation responses to offset risk is substantially

reduced (high conﬁdence). Crop yield losses, even after adaptation,

are projected to rise rapidly above 2°C global warming. Limits to

adaptation are already being reached in coral reef ecosystems.

Immigration of species from elsewhere may partly compensate for

local extinctions and/or lead to local biodiversity gains in some regions.

However, more African regions face net losses than net gains. At 1.5°C

1293

Africa Chapter 9

global warming, over 46% of localities face net losses in terrestrial

vertebrate species richness with net increases projected for under 15%

of localities. {9.6.1.4, 9.6.2.2, 9.8.2.1, 9.8.2.2, 9.8.4}

Technological, institutional and ﬁnancing factors are major

barriers to climate adaptation feasibility in Africa (high con-

ﬁdence). {9.3, 9.4.1}

There is limited evidence for economic growth alone reducing

climate damages, but under scenarios of inclusive and sustainable

development, millions fewer people in Africa will be pushed

into extreme poverty by climate change and negative impacts

to health and livelihoods can be reduced by 2030 (medium

conﬁdence). {9.10.3, 9.11.4}

Gender-sensitive and equity-based adaptation approaches reduce

vulnerability for marginalised groups across multiple sectors

in Africa, including water, health, food systems and livelihoods

(high conﬁdence). {9.7.3, 9.8.3, 9.9.5, 9.10.3, 9.11.4, Boxes 9.1, 9.2}

Integrating climate adaptation into social protection pro-

grammes, such as cash transfers, public works programmes and

healthcare access, can increase resilience to climate change

(high conﬁdence). Nevertheless, social protection programmes may

increase resilience to climate-related shocks, even if they do not spe-

ciﬁcally address climate risks. {9.4.2, 9.10.3, 9.11.4}

The diversity of African Indigenous Knowledge and local knowl-

edge systems provide a rich foundation for adaptation actions

at local scales (high conﬁdence). African Indigenous Knowledge

systems are exceptionally rich in ecosystem-speciﬁc knowledge used

for management of climate variability. Integration of Indigenous

Knowledge systems within legal frameworks, and promotion of In-

digenous land tenure rights can reduce vulnerability. {9.4.4, Boxes

9.1, 9.2}

Early warning systems based on targeted climate services

can be effective for disaster risk reduction, social protection

programmes, and managing risks to health and food systems

(e.g., vector-borne disease and crops) (high conﬁdence). {9.4.5,

9.5.1, Box9.2, 9.8.4, 9.8.5, 9.10.3, 9.11.4}

Risk-sensitive infrastructure delivery and equitable provision

of basic services can reduce climate risks and provide net

ﬁnancial savings (high conﬁdence). However, there is limited

evidence of proactive climate adaptation in African cities. Proactive

adaptation policy could reduce road repair and maintenance costs

by 74% compared to a reactive policy. Adapting roads for increased

temperatures and investment in public transport are assessed as ‘no

regret’ options. In contrast, hydropower development carries risk of

regrets due to damages when a different climate than was expected

materialises. Energy costs for cooling demands are projected to

accumulate to USD51.3billion by 2035 at 2°C global warming and to

USD486.5billion by 2076 at 4°C. {9.8.5}

Reduced drought and ﬂood risk, and improved water and

sanitation access, can be delivered by water sensitive and climate

scenario planning, monitored groundwater use, waterless on-

site sanitation, rainwater harvesting and water re-use, reducing

risk to human settlements, food systems, economies and human

health (high conﬁdence). {9.8, 9.9, 9.10, 9.11}

Water sector adaptation measures show medium social and

economic feasibility but low feasibility for most African cities

due to technical and institutional restrictions, particularly for

large supply dams and centralised distribution systems (medium

conﬁdence). {9.3.1, 9.7.3} Use of integrated water management,

water supply augmentation and establishment of decentralised water

management systems can reduce risk. Integrated water management

measures including sub-national ﬁnancing, demand management

through subsidies, rates and taxes, and sustainable water technologies

can reduce water insecurity caused by either drought or ﬂoods (medium

conﬁdence). {9.7.3, Box9.4}

Agricultural and livelihood diversiﬁcation, agroecological

and conservation agriculture practices, aquaculture, on-farm

engineering and agroforestry can increase resilience and

sustainability of food systems in Africa under climate change

(medium conﬁdence). However, smallholder farmers tend to address

short-term shocks or stresses by deploying coping responses rather

than transformative adaptations. Climate information services,

institutional capacity building, secure land tenure, and strategic

ﬁnancial investment can help overcome these barriers to adaptation

(medium conﬁdence). {9.3.1, 9.4.5, 9.8.3, 9.8.5}

African countries and communities are inadequately insured

against climate risk, but innovative index-based insurance

schemes can help transfer risk and aid recovery, including

in food systems (medium conﬁdence). Despite their potential,

uptake of climate insurance products remains constrained by lack of

affordability, awareness and product diversity. {9.4.5, 9.8.4, 9.11.4.1}

Human migration is a potentially effective adaptation strategy

across food systems, water, livelihoods and in climate-induced

conﬂict areas, but can also be maladaptive if vulnerability is

increased, particularly for health and human settlements (high

conﬁdence). Migration of men from rural areas can aggravate the

work burden faced by women. The more agency migrants have (i.e.,

degree of voluntarity and freedom of movement) the greater the

potential beneﬁts for sending and receiving areas (high agreement,

medium evidence).{9.3, 9.8.3, 9.9.1–3, 9.10.2.2.2, Boxes 9.8, 9.9,

Cross-Chapter BoxMIGRATE in Chapter 7}

1294

Chapter 9 Africa

9.1 Introduction

9.1.1 Point of Departure

This chapter assesses the scientiﬁc evidence on observed and projected

climate change impacts, vulnerability and adaptation options in Africa.

The assessment refers to ﬁve African sub-regions—north, west,

central, east and southern—closely following the African Union (AU),

but including Mauritania in west Africa and Sudan in north Africa

because much of the literature assessed places these countries in these

regions (Figure9.1). Madagascar and other island states are addressed

in Chapter 15.

The contribution of Africa is among the lowest of historical greenhouse

gas (GHG) emissions responsible for human-induced climate change

and it has the lowest per capita GHG emissions of all regions currently

(high conﬁdence) (Figure 9.2). Yet Africa has already experienced

widespread impacts from human-induced climate change (high

conﬁdence) (Figure9.2; see Table9.1).

Since AR5 (Assessment Report 5), there have been notable policy

changes in Africa and globally. The Paris Agreement, 2030 Sustainable

Development Goals (SDGs), the Sendai Framework and Agenda 2063

emphasise interlinked aims to protect the planet, reduce disaster risk,

end poverty and ensure all people enjoy peace and prosperity (AU,

2015; UNFCCC Paris Agreement, 2015; UNISDR Sendai Framework,

2015; United Nations General Assembly, 2015). To match these

interlinked ambitions, this chapter assesses risks and response options

both for individual sectors and cross-sectorally to assess how risks

can compound and cascade across sectors, as well as the potential

feasibility and effectiveness, co-beneﬁts and trade-offs and potential for

maladaptation from response options (Simpson etal., 2021b; Williams

etal., 2021).

9.1.2 Major Conclusions from Previous Assessments

Based on an analysis of 1022 mentions of Africa or African countries

across the three AR6 Special Reports, the following main conclusions

emerged.

• Hot days, hot nights and heatwaves have become more frequent;

heatwaves have also become longer (high conﬁdence). Drying

is projected particularly for west and southwestern Africa (high

conﬁdence) (IPCC, 2018c; Shukla etal., 2019).

• Climate change is contributing to land degradation, loss of

biodiversity, bush encroachment and spread of pests and invasive

species (IPCC, 2018b; IPCC, 2019a; IPCC, 2019b).

• Climate change has already reduced food security through losses

in crop yields, rangelands, livestock and ﬁsheries, deterioration in

food nutritional quality, access and distribution, and price spikes.

Risks to crop yields are substantially less at 1.5°C compared with

2°C of global warming, with a large reduction in maize cropping

areas projected even for 1.5°C, as well as reduced ﬁsheries catch

potential (IPCC, 2018b; IPCC, 2019b; IPCC, 2019a).

• Increased deaths from undernutrition, malaria, diarrhoea, heat stress

and diseases related to exposure to dust, ﬁre smoke and other air

pollutants are projected from further warming (IPCC, 2018c; Shukla

etal., 2019).

• The largest reductions in economic growth for an increase from

1.5°C to 2°C of global warming are projected for low- and middle-

income countries, including in Africa (IPCC, 2018c).

• Climate change interacts with multi-dimensional poverty, among

other vulnerabilities. Africa is projected to bear an increasing

proportion of the global exposed and vulnerable population at 2°C

and 3°C of global warming (IPCC, 2018c).

• Poverty and limited ﬁnancing continue to undermine adaptive

capacity, particularly in rapidly growing African cities (Shukla etal.,

2019).

• Large-scale afforestation and bioenergy can reduce food

availability and ecosystem health (IPCC, 2018c; IPCC, 2019a).

• Transitioning to renewable energy would reduce reliance on wood

fuel and charcoal, especially in urban areas, with co-beneﬁts

including reduced deforestation, desertiﬁcation, ﬁre risk and

improved indoor air quality, local development and agricultural

yield (Shukla etal., 2019).

5,001–10,000

2,501–5,000

1,001–12,500

501–1,000

101–500

51–100

21–50

11–20

>10,000

5–10

The five regions of Africa used in Chapter 9

Estimated population

density in 2019

Number of people per km

Figure9.1 |  The ﬁve regions of Africa used in this chapter, also showing

estimated population density in 2019. The population of Africa was estimated

at 1.312billion for 2020, which is about 17% of the world’s population but this is

projected to grow to around 40% of the world’s population by 2100 (UNDESA, 2019a).

Although 57% of the African population currently live in rural areas (43% urban), Africa

is the most rapidly urbanising region globally and is projected to transition to a majority

urban population in the 2030s, with a 60% urban population by 2050 (UNDESA,

2019b). The 2019 gross domestic product (GDP) per capita in constant 2010 USD

averaged USD2250 across the 43 countries reporting data, ranging from USD202

(Burundi) to USD8840 (Gabon), with 40% of the population of sub-Saharan Africa

living below the international poverty line of USD1.90 per day in 2018 (World Bank,

2019). The highest life expectancy at birth is 67 (Botswana and Senegal) and the lowest

is 52 (Central African Republic) World Bank (2019). Grid-cell population density data for

mapping are from Tatem (2017); WorldPop (2021).

1295

Africa Chapter 9

Historical greenhouse gas (GHG) emission trends for Africa compared to other world regions

SmallIslands

NorthAmerica

Europe

Centraland

S. America

Australasia

Asia

Africa

01020304050

GHG Emissions per capita (tCO₂eq/capita)

19902000 20102019

GHG Emissions (Gt CO2eq)

(b) Regional GHG emission trends

Tunisia

Cong

o, Dem. Rep.

Uganda

Chad

Tanzania

Libya

Angola

Kenya

Morocco

Sudan

Ethiopia

Algeria

Egypt, Arab Rep.

Nigeria

SouthAfrica

0200 400600

GHG Emissions (MtCO

₂

eq)

1990

2019 0

1990 2000 2010 2019

GHG Emissions (Gt CO2eq/year)

CH₄

CO₂

N₂O

1990 2000 2010 2019

Agriculture

Buildings

Industry

Transport

Energy

systems

(a) Regional per capita GHG emissions

1990

2019

Region

average

Single

countries

Africa

Asia

Australasia

Europe

North America

Central and South

America

Small Islands

Figure9.2 | Historical greenhouse gas (GHG) emission trends for Africa compared to other world regions:

(a) Per person GHG emissions by region and their change from 1990 to 2019 (circles represent countries, diamonds represent the region average).

(b) Total GHG emissions by region since 1990.

(d) Total emissions in Africa since 1990, broken down by GHG (left) and sector (right). Methane and CO2 emissions comprise an almost equal share of GHG emissions in Africa,

with the largest emissions sectors being energy and agriculture (Crippa etal., 2021). Agriculture emissions in panel (d) do not include land use, land use change and forestry

(LULUCF CO2). One-hundred-year global warming potentials consistent with WGI estimates are used. Emissions data are from Crippa etal. (2021), compiled in Working Group III

(WGIII) Chapter 2.

• Sustainable use of biodiversity, conservation agriculture, reduced

deforestation, land and watershed restoration, rainwater

harvesting and well-planned reforestation can have multiple

beneﬁts for adaptation and mitigation, including water security,

food security, biodiversity, soil conservation and local surface

cooling (IPBES, 2018; Shukla etal., 2019).

• Climate resilience can be enhanced through improvements to

early warning systems, insurance, investment in safety nets, secure

land tenure, transport infrastructure, communication, access to

information and investments in education and strengthened local

governance (Shukla etal., 2019).

• Scenarios of socio-environmental change are under-used in

decision making in Africa (IPBES, 2018).

• Africa’s rich biodiversity together with a wealth of Indigenous

Knowledge and Local Knowledge (IKLK) is a key strategic asset for

sustainable development (IPBES, 2018).

9.1.3 What’s New on Africa in AR6?

• Increased conﬁdence in observed and projected changes in climate

hazards, including heat and precipitation

• Increased regional, national and sub-national observed impacts

and projected risks

• Loss and damage assessment

• Increased quantiﬁcation of projected risks at 1.5°C, 2°C, 3°C and

4°C of global warming (see Section9.2; Figure9.6)

• Improved assessment of sea level rise risk (Sections9.9; 9.12)

• Increased quantiﬁcation of risk across all sectors assessed

• Expanded assessment of adaptation feasibility and effectiveness

and limits to adaptation (see Figure9.7)

• Assessment of adaptation ﬁnance (Section9.4.1)

• Increased assessment of how climate risk and adaptation and

mitigation response options are interlinked across multiple key

development sectors (Section9.4.3; Boxes 9.4; 9.5).

1296

Chapter 9 Africa

Funding for climate-related research on Africa is a very small proportion

of global climate-related research funding

100

120

140

(e) Distribution of funding across risk categories, 1990–2020

before and after the Paris Agreement, million 2010 USD

Japan

Poland

China

Switzerland

Finland

Canada

France

Norway

Sweden

Germany

USA

050 100 150

2016–2020, Total1990–2015, Total

020406080 100 120 140

South Africa

Kenya

Italy

Norway

Netherlands

France

Sweden

Germany

United Kingdom

United States

(d) Top 10 country locations of institutions receiving funding for

climate change research on Africa, 1990–2020, million 2010 USD

Mitigation

17% Other climate change research (3%)

Adaptation

40%

Impact

40%

(f) Funding for climate impact, mitigation and adaptation research on Africa

1990 2000 2010 2020

Million

2015

USD

(a) Funding for climate research on Africa and on whole world

3500

3000

2500

2000

1500

1000

500

World

Africa

10%

12%

1990 2000 2010 2020

Climate

research

funding as

percentage

of general

research

funding

(b) Percentage of total research funding spent on climate research

World

Africa

050 100 150

Million

2010

USD

Food

systems

Eco-

systems

Fresh-

water

Health Poverty

and

livelihoods

Cities/

urban

areas

Security

and

conflict

Figure9.3 | Climate-related research on Africa has received a very small percentage (around 4%) of global climate research funding (a).

(b) As a percentage of all research funding allocated to a region, climate research has, since 2010, made up 5% of Africa-related research funding compared to a 3% share for

climate research in global research funding.

(d) Most funding for climate-related research on Africa ﬂows to institutions based in Europe and the USA. Funding comes mainly from government organisations with private

philanthropy providing only around 1% (Overland etal., 2021).

(e) Africa-related climate research funding focuses mostly on food systems, ecosystems and freshwater, while health, poverty, security and conﬂict, and urban areas have received

the least.

(f) Research on climate mitigation received only 17% of funding while climate impacts and adaptation each received 40%. A greater proportion of Africa-focused climate funding

has gone to social sciences and humanities (28%) than is the case globally (12%) (Overland etal., 2021). Data are from an analysis of 4,458,719 research grants in the Dimensions

database with a combined value of USD1.51 trillion awarded by 521 funding organisations globally (Overland etal. 2021). The Dimensions database is the world’s largest database

on research funding ﬂows (Overland etal. 2021). It draws on ofﬁcial data from all major funding organisations in the world, mainly government research councils or similar

institutions. Note: The South African National Research Foundation is the only African research funding body that is sufﬁciently large to be included in Dimensions.

1297

Africa Chapter 9

Major gaps in climate change research funding, participation and publication exist within Africa,

and for Africa compared to the rest of the world

(a) Climate change research funding focused on African countries

(b) Climate change studies with locally-based authors

Funding amount

in USD millions

(1990–2020)

Percentage

of studies with

locally-based authors

41–50

31–40

11–20

1–10

21–30

Adaptation

research on

individual countries

(number of papers)

401–600

201–400

601–1,000

>1,000

1–100

No data

101–200

41–60%

21–40%

61%

No data

1–20%

Figure9.4 | Major gaps in climate change research funding, participation and publication exist within Africa, and for Africa compared to the rest of the

world.

(a) Funding: Amount of climate change research funding focused on African countries 1990–2020 (Overland etal., 2021). Considering population size, research on Egypt and

Nigeria stands out as particularly underﬁnanced.

(b) Participation: Percentage of peer-reviewed climate change papers on impacts and adaptation published on a given country that also include at least one author based in that

country (Pasgaard etal. 2015).

(c) Number of publications of climate change adaptation research focused on individual countries identiﬁed from a global sample of 62,191 adaptation-relevant peer-reviewed

articles published from 1988–2020 (Sietsma et al., 2021). There is a general lack of adaptation-related research on many vulnerable countries in Africa. Topic biases in

adaptation-relevant research also exist where research focuses more on disaster and development-related topics in global south countries (but published by authors from the global

north), while research on global north countries focuses more on governance topics (Sietsma etal., 2021).

1298

Chapter 9 Africa

9.1.4 Climate Change Impacts Across Africa

In many parts of southern, east and west Africa, temperature or

precipitation trends since the 1950s are attributable to human-

caused climate change and several studies document the impacts of

these climate trends on human and natural systems (high conﬁdence)

(Figure 9.5; Sections 9.5.6; 9.5.7). Nevertheless, research into

attribution of trends to human-caused climate change or climate

impacts remains scarce for multiple regions, especially in north and

central Africa. This illustrates an ‘attribution gap’ where robust evidence

for attributable impacts is twice as prevalent in high- compared to

low-income countries globally (Callaghan etal., 2021). Most studies

on climate impacts in Africa have focused on terrestrial ecosystems or

water, with fewer on marine ecosystems, agriculture, migration, and

health and well-being (Callaghan etal., 2021). Speciﬁc factors driving

these knowledge gaps include limited data collection, data access and

research funding for African researchers (see next section).

9.1.5 Climate Data and Research Gaps Across Africa

Since AR5, there have been rapid advances in climate impact research

due to increased computing power, data access and new developments

in statistical analysis (Carleton and Hsiang, 2016). However, sparse and

intermittent weather station data limit attribution of climate trends to

human-caused climate change for large areas of Africa, especially for

precipitation and extreme events, and hinder more accurate climate

change projections (Section9.5.2; Figure9.5; Otto etal., 2020). Outside

of South Africa and Kenya, digitally accessible data on biodiversity is

limited (Meyer etal., 2015). Lack of comprehensive socioeconomic data

also limits researchers’ ability to predict climate change impacts. Ideally,

multiple surveys over time are needed to identify effects of a location’s

changing climate on changing socioeconomic conditions. Twenty-ﬁve

African countries conducted only one nationally representative survey

that could be used to construct measures of poverty during 2000–2010

and 14 conducted none over this period (Jean etal., 2016). Because

of these challenges, much of what is known about climate impacts

and risks in Africa relies on evidence from global studies that use

data largely from outside Africa (e.g., Zhao etal., 2021). These studies

generate estimates of average impacts across the globe, but may not

have the statistical power to distinguish whether African nations display

differential vulnerability, exposure or adaptive capacity. In sections

of this chapter, we have relied, when necessary, on such studies, as

they often provide best available evidence for Africa. Increasing data

coverage and availability would increase the ability to discern important

differences in risk both among and within African countries.

Climate-related research in Africa faces severe funding constraints

with unequal funding relationships between countries and with

research partners in Europe and North America (high conﬁdence).

Based on analysis of over 4 million research grants from 521

funding organisations globally, it is estimated that, from 1990–2020,

USD 1.26 billion funded Africa-related research on climate impacts,

mitigation and adaptation. This represents only 3.8% of global funding

for climate-related research—a ﬁgure incommensurate with Africa’s

high vulnerability to climate change (see Figure 9.3; Box 9.1; Chapter8

Figure 8.6; Overland etal., 2021). Almost all funding for Africa-related

Climate impacts on human and natural systems

are widespread across Africa, as are climate trends

attributable to human-caused climate change

Temperature or precipitation Temperature and precipitation

Evidence for climate impacts

Attributable to Human

induced climate change

Attributable to other causes

Low RobustHigh

Climate

trends

Figure 9.5 |  Observed climate change impacts on human and natural

systems are widespread across Africa, as are climate trends attributable

to human-induced climate change. This machine-learning-assisted evidence map

shows the presence of historical trends in temperature and precipitation attributable to

human-induced climate change (pinks compared to greys) and the amount of evidence

(shown by intensity of colours) documenting the impacts of these climate trends on

human and natural systems (e.g., ecosystems, agriculture, health) across Africa. ‘Robust’

indicates more than ﬁve studies documented impacts per grid cell. A ‘High’ amount of

evidence indicates more than 20studies documented impacts for a grid cell. Climate

impact studies from the literature were identiﬁed and categorised using machine

learning. A language representation model was trained on a set of 2373 climate impact

studies coded by hand. This supervised machine learning model identiﬁed 102,160

published studies predicted to be relevant for climate impacts globally; references to

places in Africa were found in 5081studies (5% of global studies). Temperature trends

were calculated from 1951–2018 and precipitation from 1951–2016. Attribution of

climate trends to human induced climate change is limited in some regions of Africa

due to insufﬁcient data (see Section9.5.1, Figure9.15). Hatching shows regions where

trends in both temperature and precipitation are attributable to human-induced climate

change. Data from Callaghan etal. (2021).

climate research originates outside Africa and goes to research

institutions outside Africa (Blicharska et al., 2017; Bendana, 2019;

Siders, 2019; Overland etal., 2021). From 1990–2020, 78% of funding

for Africa-related climate research ﬂowed to institutions in Europe

1299

Africa Chapter 9

and the USA—only 14.5% ﬂowed to institutions in Africa (Figure9.3;

Overland etal., 2021). Kenya (2.3% of total funding) and South Africa

(2.2%) are the only African countries among the top 10countries in

the world in terms of hosting institutions receiving funding for climate-

related research on Africa (Overland etal., 2021).

These unequal funding relations inﬂuence inequalities in climate-related

research design, participation and dissemination between African

researchers and researchers from high-income countries outside Africa, in

ways that can reduce adaptive capacity in Africa (very high conﬁdence).

Those empowered to shape research agendas can shape research

answers: climate research agendas, skills gaps and eligible researchers

are frequently deﬁned by funding agencies, often from a global north

perspective (Vincent et al., 2020a). Larger funding allocations for

research focused on Ghana, South Africa, Kenya, Tanzania and Ethiopia

are reﬂected in higher concentrations of empirical research on impacts

and adaptation options in these countries, and there is a general lack

of adaptation research for multiple of the most vulnerable countries in

Africa (Figure9.4) (Callaghan etal., 2021; Overland etal., 2021; Sietsma

etal., 2021; Vincent and Cundill, 2021). The combination of northern-led

identiﬁcation of both knowledge and skills gaps can result in projects

where African partners are positioned primarily as recipients engaged

to support research and/or have their ‘capacity built’ rather than also

leading research projects on an equal basis (Vincent etal., 2020a; Trisos

etal., 2021). Analysis of >15,000 climate change publications found for

over 75% of African countries 60–100% of climate change publications

on these countries did not include a single local author, with authorship

dominated by researchers from richer countries outside Africa (Pasgaard

etal., 2015). This can reduce adaptive capacity in Africa as researchers

at global north institutions may shape research questions and outputs

for a northern audience rather than providing actionable insights on

priority issues for African partners (Pasgaard et al., 2015; Nago and

Krott, 2020). Moreover, in order to access research publications in a

timely manner, many researchers in Africa are forced to use shadow

websites bypassing journal paywalls (Bohannon, 2016). Ways to

enhance research partnerships to produce actionable insights on climate

impacts and solutions in Africa include: increased funding from African

and non-African sources, increasing direct control of resources for

African partners, having African research and user priorities set research

questions, identify skills gaps, and lead research, and having open access

policies for research outputs (ESPA Directorate, 2018; Vogel etal., 2019;

Vincent etal., 2020a; IDRC, 2021; Trisos etal., 2021).

9.1.6 Loss and Damage from Climate Change

Assessment of impacts, vulnerability, and adaptation highlights climate

change is leading to loss and damage across Africa, that breach current

and projected adaptation limits (Table9.1; Cross-Chapter BoxLOSS in

Chapter 17).

9.2 Key Risks for Africa

A key risk is deﬁned as a potentially severe risk. In line with AR5,

‘severity’ relates to dangerous anthropogenic interference with the

climate system, the prevention of which is the ultimate objective of the

United Nations Framework Convention on Climate Change (UNFCCC)

as stated in its Article 2 (Oppenheimer etal., 2014). The process for

identifying key risks for Africa included reviewing risks from Niang

etal. (2014) and assessing new evidence on observed impacts and

projected risks in this chapter.

Several key risks were identiﬁed for both ecosystems and people

including species extinction and ecosystem disruption, loss of food

production, reduced economic output and increased poverty, increased

disease and loss of human life, increased water and energy insecurity,

loss of natural and cultural heritage and compound extreme events

harming human settlements and critical infrastructure (Table9.2). In

order to provide a sector- and continent-level perspective, the key risks

aggregate across different regions and combine multiple risks within

sectors. For detailed assessments of observed impacts and future risks

within each sector and each sub-region of Africa, see the sector-speciﬁc

sections of this chapter (Sections9.6 to 9.12).

Several expert elicitation workshops of lead and contributing authors

were held to develop ‘burning embers’ assessing how risk increases

with further global warming for a subset of key risks, speciﬁcally risk

of food production losses, risk of biodiversity loss and risk of mortality

Key risks for Africa

increase with increasing global warming

Very high

High

Moderate

Undetectable

Level of

impact or risk

Confidence level

for transition

•

••

•••

••••

Low

Medium

High

Very high

Transition

range

Global mean temperature

increase above pre-industrial

0°C

1°C

2°C

3°C

4°C

1.5 °C

Recent

climate

(2010–2020)

Reduced

food production

from crops

fisheries

and livestock

•••

••

•••

Biodiversity

loss and

ecosystem

disruption

•••

Mortality and

morbidity from

heat and

infectious

disease

••

•••

Figure 9.6 |  Risks increase with increasing levels of global warming, as

shown by this Burning Embers ﬁgure for selected key risks from climate

change in Africa. Increases in risk are assessed for the levels of global warming above

pre-industrial (1850–1900). All three risks are assessed to have already transitioned to

moderate risk by the recent level of global warming 2010–2020 (1.09°C). Risks are

characterised as undetectable, moderate, high, or very high, and the transition between

risk levels as a function of global warming is represented by the colour change of each

bar (IPCC, 2021). Vertical lines show the range of global warming for a change in the

risk level. The dots indicate the conﬁdence level for a given transition in risk and are

placed at the level of global warming that is the assessed best estimate for that increase

in the risk level. For the range of global warming levels for each risk transition used to

make this ﬁgure see Supplementary Material TableSM 9.1.

1300

Chapter 9 Africa

and morbidity from heat and infectious disease (Figure9.6). These key

risks were selected in part because of underlying assessment work in

the chapter to connect multiple studies to observed impacts and/or

risk at increasing global warming levels (Sections9.6.2; 9.8.2; 9.8.5.2;

9.10.2).

All three of these key risks are assessed to have already transitioned

completely into moderate risk—that is, negative impacts have been

detected and attributed to climate change—before the 2010–2020

level of global warming (1.09°C) above pre-industrial times (IPCC,

2021), with medium conﬁdence for increased mortality and morbidity

and high conﬁdence for losses of food productivity and biodiversity

(Figure 9.6). For biodiversity, these impacts include repeated mass

die-offs of coral reefs due to marine heat (Section9.6.1.4), reductions

in lake productivity due to warming (Section 9.6.1.3), and woody

encroachment of grasslands and savannas due to increased atmospheric

CO2 concentrations (Section 9.6.1.1), with negative impacts on

livelihoods (Section 9.6.2). For food production, climate change

impacts include up to 5.8% mean reduction in maize productivity due

to increased temperatures in sub-Saharan Africa (Sections 9.8.2.1;

9.8.2.2) and reduced ﬁsheries catches due to increased temperatures,

especially in tropical regions (Section9.8.2). For health, climate change

impacts include increased mortality and morbidity from changes in the

distribution and incidence of malaria and cholera and the direct effects

of increasing temperatures (Section9.10.2).

In scenarios with low adaptation (that is largely localised and

incremental), the transition to high risk—widespread and severe

impacts—has already begun at the current level of global warming

for biodiversity loss (high conﬁdence), and begins below 1.5°C global

warming for both food production (medium conﬁdence) and mortality

and morbidity from heat and infectious disease (high conﬁdence).

Across all risks, the best estimate for the transition to high risk is at

1.5°C of global warming, with transition to high risk completing before

2°C (Figure9.6). Projected impacts considered high risk around 1.5°C

include: across more than 90% of Africa, more than 10% of species are

at risk of local extinction (Figure9.6; Table9.1); the further expansion

of woody plants into grass-dominated biomes (Section9.6.2.1); 9%

declines in maize yield for west Africa and 20–60% decline in wheat

yield for southern and northern Africa, as well as declines in coffee

Table9.1 |  Loss and damage from climate change across sectors covered in this report. Loss and damage arise from adverse climate-related impacts and risks from both

sudden-onset events, such as ﬂoods and cyclones, and slower-onset processes, including droughts, sea level rise, glacial retreat and desertiﬁcation and include both include both

economic (e.g., loss of assets and crops) and non-economic types (e.g., loss of biodiversity, heritage and health) (UNFCCC Paris Agreement, 2015; IPCC, 2018a; Mechler etal.,

2020). Sections marked with * and in bold highlight Loss and Damage attributed to human-induced climate change (16.1.3).

Sector Loss and damage from climate change Observed Projected

Ecosystems

Local, regional and global extinction

Reduced ecosystem goods and services

Declining natural coastal protection and habitats

Altered ecosystem structure and declining ecosystem functioning

Nature-based tourism

Biodiversity loss

9.6.2

9.6.1; 9.6.2

9.6.1

9.6.3

9.6.2*

9.6.2

9.6.3

Water

Declining lake and river resources

Reduced hydroelectricity and irrigation

Disappearing glaciers

Reduced groundwater recharge and salinisation

Drought

9.7.1

9.7.2; 9.9.1

9.5.9*; 9.7.1

–

Box9.4*

9.7.2

9.7.2; 9.9.3; Box9.5

9.5.9

9.7.2

Food systems

Reduced crop productivity and revenues

Increased livestock mortality and price shocks

Decreased fodder and pasture availability

Reduced ﬁsheries catch and ﬁsher livelihoods

9.7.2*, 9.8.1; 9.8.2; 9.11.1; Box9.5

9.8.2

9.6.1; 9.8.5

9.8.2; 9.8.3; Box9.5

9.8.2

9.8.5

Human settlements and

infrastructure

Loss or damage to formal and informal dwellings

Damage to transport systems

Damage to energy systems

Water supply, sanitation, education and health infrastructure

Migration

9.9.2

9.9.2; 9.10; 9.11.1

9.9.1; Box9.8

9.9.4

9.7.2; 9.9.4

9.7.3; 9.9.4; 9.10; 9.11.1

9.9.4; Box9.8

Health

Loss of life

Loss of productivity

Reduced nutrition

9.9.2*; 9.10.2; Box9.9

9.10.3; 9.11.1

9.8.1; 9.10.2

9.9.4; 9.10.2

9.10.2; 9.11.2

9.10.2

Economy, poverty and

livelihoods

Loss of livelihoods, jobs and income

Reduced productive land

Reduced economic growth and increased inequality

Community and involuntary displacement

Reduced labour productivity and earning potential

Delayed and poorer education progress

Reduced tourism

Increased urban in-migration

9.9.2; 9.10.2; 9.11.1

9.8.2

9.11.1*; Box9.5

9.9.3; Box9.8

9.11.1

9.6.3

9.8.1; 9.9.1; Table Box9.8

9.10.2; 9.11.2

9.8.2

9.11.2

9.9.4; Box9.8

9.11.2

9.11.1

9.5.9, 9.6.3, 9.12.2

9.9.4; Table Box9.8

Heritage

Loss of traditional cultures and ways of life

Loss of language and knowledge systems

Damage to heritage sites

Box9.2; 9.12.1

–

9.12.1

9.12.2

9.12.1

9.12.2

1301

Africa Chapter 9

and tea in east Africa and sorghum in west Africa (Figures9.22; 9.23;

Sections9.8.2.1; 9.8.2.2), and >12% decline in marine ﬁsheries catch

potential for multiple west African countries, potentially leaving

millions at risk of nutritional deﬁciencies (Figure9.25; Section9.8.5);

tens of millions more people exposed to vector-borne diseases in east

and southern Africa (malaria), and north, east and southern Africa

(dengue, zika), increased risk of malnutrition in central, east and west

Africa, and more than 15 additional deaths per 100,000 annually due

to heat in parts of west, east and north Africa (Figures 9.32; 9.35;

Sections9.10.2; 9.9.4.1).

The transition from high to very high risk—that is severe and

widespread impacts with limited ability to adapt—begins either at or

just below 2°C for all three risks (Figure9.6). The assessed temperature

range for the transition to very high risk is wider for food production

than for biodiversity and health. Projected impacts for food include:

10–30% decline in marine ﬁsheries catch potential for the Horn of

Africa region and southern Africa and more than 30% decline for west

Africa at 2°C global warming, with greater declines at higher levels

of warming (Section9.8.2). Beyond 2°C global warming, over 50%

of commercially important freshwater ﬁsh species across Africa are

projected to be vulnerable to extinction (Figure9.26). Between 2°C

and 4°C, wheat, maize and rice yields are projected, on average, to be

lower than 2005 yields across all regions of Africa. From 2°C global

warming, over 40% losses in rangeland productivity are projected for

western Africa. By 3.75°C, severe heat stress may be near year-round

for cattle across tropical Africa (Figure9.24). Multiple countries in west,

central and east Africa are projected to be at risk from simultaneous

negative impacts on crops, ﬁsheries and livestock (Sections 9.8.2;

9.8.5; Thiault etal., 2019).

The best estimate for the onset of very high risk for biodiversity and

health is at 2.1°C. Projected impacts considered very high risk for

biodiversity include potential destabilisation of the African tropical

forest carbon sink, risk of local extinction of more than 50% of plants,

vertebrate and insect species across one-ﬁfth of Africa, 7–18% of

African species at risk of total extinction including, a third of freshwater

ﬁsh, and more than 90% warm-water coral reefs lost (Section9.6.2).

For health, projected impacts considered high risk include potentially

lethal heat exposure for more than 100days per year in west, central

and east Africa, with more than 50 additional heat-related deaths per

100,000 annually across large parts of Africa, and hundreds of millions

more people exposed to extreme heat in cities (Section9.5; 9.10.2;

9.9.4.1; Figure9.35), tens to hundreds of thousands of additional

cases of diarrhoeal disease in east, central and west Africa, and tens

of millions more people exposed to mosquito-borne arboviruses like

dengue or zika in north, east and southern Africa (Section9.10.2).

The feasibility and effectiveness of existing adaptation options

under current levels of warming are assessed in Section9.10.2 and

adaptation options considering future levels of warming are assessed

in the chapter section for each sector.

9.3 Climate Adaptation Options

9.3.1 Adaptation Feasibility and Effectiveness

Based on a systematic assessment of observed climate adaptation

responses in the scientiﬁc literature covering 827 adaptation response

types in 553studies (2013–2021), and expert elicitation process, 24

categories of adaptation responses in Africa were identiﬁed (Williams

et al., 2021; Figure 9.7). This assessment excluded autonomous

adaptation in ecosystems, such as migration and evolution of animal

and plant species.

At the current global warming level, 83% of adaptation response

categories assessed showed medium potential for risk reduction

(that is, mixed evidence of effectiveness). Bulk water infrastructure

(including managed aquifer recharge, dams, pipelines, pump stations,

water treatment plants and distribution networks), human migration,

ﬁnancial investment for sustainable agriculture, and social infrastructure

(including decentralised management, strong community structures

and informal support networks) show high potential for risk reduction

(high evidence of option’s effectiveness)(Sections9.6.4; 9.7.3; Boxes

9.8; 9.9; 9.10; 9.11). However, there was limited evidence to assess

the continued effectiveness of these options at higher global warming

levels (Williams et al., 2021) with some options, such as bulk water

infrastructure (particularly large dams), expected to face increasing risk

with continued warming with damages cascading to other sectors (see

Box9.5), while others, such as crop irrigation and adjusting planting

times, may increasingly reach adaptation limits above 1.5°C and 2°C

global warming (Sections9.8.3; 9.8.4).

The majority of adaptation studies were in west and east Africa

(Ethiopia, Ghana, Kenya and Tanzania), followed by southern Africa,

with the least coming from central and north Africa (Figure 9.7;

Williams etal., 2021). Most studies were on adaptation actions in the

food sector, with the least on health (Figure9.7). The ﬁve adaptation

response categories with the highest number of reported actions were

sustainable water management (food sector), resilient infrastructure

and technologies (health sector), agricultural intensiﬁcation (food

sector), human migration (poverty and livelihoods) and crop

management (food sector).

No adaptation response categories were assessed to have high

feasibility of implementation. Technological barriers dominate factors

limiting implementation (92% of adaptation categories have low

technological feasibility) followed by institutional barriers (71%

of adaptation categories have low institutional feasibility). This

assessment matches review studies ﬁnding institutional responses

to be least common in Africa and highlight inadequate institutional

capacities as key limits to human adaptation (Berrang-Ford etal.,

2021; Thomas etal., 2021) (Cross-Chapter BoxFEASIB in Chapter 18).

Feasibility is higher for the social dimension of adaptation responses

(with moderate feasibility for 88% of categories). The largest evidence

gap is for environmental feasibility for which 67% could not be

assessed due to insufﬁcient evidence (Figure9.7).

Sustainable Water Management (SWM) includes rainwater harvesting

for irrigation, watershed restoration, water conservation practices

1302

Chapter 9 Africa

(e.g., efﬁcient irrigation) and less water-intensive cropping (also see

Section9.8.3), and was the most reported adaptation response in the

food sector. SWM was assessed with medium economic and social

feasibility and low environmental, institutional and technological

feasibility. The feasibility of this adaptation category may depend

largely on socioeconomic conditions (Amamou etal., 2018; Harmanny

and Malek, 2019; Schilling et al., 2020), as many African farmers

cannot afford the cost of SWM facilities (Section9.8.4).

Resilient Infrastructure and Technologies (RIT) for health include improved

housing to limit exposure to climate hazards (Stringer etal., 2020), and

improved water quality, sanitation and hygiene infrastructure (e.g.,

technology across all sectors to prevent contamination and pollution

of water, improved water, sanitation and hygiene (WASH) approaches

such as promotion of diverse water sources for water supply, improving

health infrastructure) (Section9.10.3). Overall, RIT had medium social

feasibility and low institutional and technological feasibility. Bulk

water infrastructure was assessed to have high effectiveness, but low

institutional and technological feasibility. Increasing variability in climate

and environmental challenges has made sustainable and resilient

infrastructure design a key priority (Minsker etal., 2015). RIT is, however,

generally new in the African context (Cumming etal., 2017) and that

may be why there is limited evidence to assess some of its dimensions

(economic and environmental feasibility). Construction of resilient public

water infrastructures that include safeguards for sanitation and hygiene

are expensive and, across national and local levels, planning for its

construction poses multiple challenges (Choko etal., 2019).

Sustainable agricultural intensiﬁcation in smallholder farming systems

(especially agroecological approaches, such as mixed cropping, mixed

farming, no soil disturbance, and mulching) and agroforestry are key

response options to secure food for the growing African population

Table9.2 | Key risks from climate change in Africa

Key climate change risk Climate impact driver Vulnerability Section

Local or global extinction of species and

reduction or irreversible loss of ecosystems

and their services, including freshwater, land

and ocean ecosystems

Increasing temperatures of freshwaters,

ocean and on land; heatwaves; precipitation

changes (both increases and decreases);

increased atmospheric CO2 concentrations;

sea level rise; ocean acidiﬁcation

Vulnerability highest among poorly dispersing organisms (plants) and

species with narrow and disappearing niches (e.g., mountain endemics),

and is exacerbated by non-climate hazards (e.g., habitat loss for

agriculture or afforestation projects); vulnerability is high for Protected

Areas surrounded by transformed land preventing species’ dispersal and

areas with limited elevational gradients that reduce their potential to act

as climate refugia.

9.6

Risks to marine ecosystem health and to

livelihoods in coastal communities

marine heatwaves, increased acidiﬁcation

and sedimentation/turbidity

low-income coastal communities (e.g., artisanal ﬁsherfolk, ﬁshmongers)

whose livelihood depends on healthy coral reefs, seagrass beds and

mangroves

9.6, 9.8

Loss of food production from crops,

livestock and ﬁsheries

Increasing temperatures and heat waves

for freshwaters, ocean and on land;

precipitation changes; drought; increased

atmospheric CO2 concentrations

High for low-income coastal and riparian communities whose livelihood

depends on healthy ocean and freshwater ecosystems, and for populations

reliant on ﬁsh for protein and micronutrients. Vulnerability is high for

many food producers dependent on rainfall and temperature conditions,

including subsistence farmers, the rural poor, and pastoralists. Lack of

access to climate information and services increases vulnerability.

9.8

Mortality and morbidity from increased

heat and infectious diseases (including

vector-borne and diarrhoeal diseases)

Increasing temperatures; heatwaves;

precipitation change (both increases and

decreases)

Vulnerability is highest for the elderly, pregnant women, individuals with

underlying conditions, immune-compromised individuals (e.g., from HIV)

and young children.

Regions without vector control programmes in place or without detection

and treatment regimens.

Inadequate insulation in housing in informal settlements in urban heat

islands. Inadequate improvements in public health systems.

Inadequate water and sanitation infrastructure, especially in rapidly

expanding urban areas and informal settlements.

9.10

Reduced economic output and growth, and

increased inequality and poverty rates

Increased temperatures; reduced rainfall;

drought; extreme weather events

Conditions underlying severe risk are lower income growth, higher

population levels, low rates of structural economic change with more of

the labour force engaged in agriculture and other more climate-exposed

sectors due in part to physical labour outdoors.

9.11

Water and energy insecurity due to

shortage of irrigation and hydropower Heat and drought

High reliance on hydropower for national electricity generation, especially

east and southern African countries. Planned for high reliance on irrigated

food production. Concentrations of hydropower plants within river basins

experiencing similar rainfall and runoff patterns. Limited electricity trade

between major river basins.

9.7; 9.9;

Box9.5

Cascading and compounding risks of loss of

life, livelihoods and infrastructure in human

settlements

Extreme heat; ﬂoods; drought; sea level rise

and associated coastal hazards; compound

climate hazards (e.g., coinciding heat and

drought)

Coastal and low-lying urban areas and those in dryland regions with

rapidly growing populations. People living in informal settlements.

Increased magnitude of heat waves due to urban heat island effects.

Climate shocks to municipal revenues (e.g., from water). Unaffordable

maintenance of transport and protective infrastructure with increasing

climate impacts. Greater water resource demand from urban and

non-urban populations and key economic sectors.

9.9

1303

Africa Chapter 9

Northern

Central

Eastern

Western

Southern

Evidence

* water conservation

and efficiency

Sustainable water management *

Food fibre

and other ecosystem

products

Health, well-being

and communities

Poverty, livelihoods and

sustainable development

Terrestrial, freshwater,

ocean and coastal

ecosystems

Water and sanitation

Cities, settlements and

key infrastructure

Synthesis of adaptation options for Africa Feasibility Dimensions

Environmental

Technological

Institutional

Social

Economic

Effectiveness

Observations

per region

Sectors Adaptation options

= insufficient evidence

Assessment score

Agroforestry

Sustainable agricultural practices

Sustainable agricultural intensification

Climate information services

Financial investment

Crop management

Livestock management

Fisheries management

Health governance and planning

Health advisory services and education

Resilient infrastructure and technologies

Risk spreading and sharing

Human migration

Livelihood diversification

Ecosystem restoration and conservation

Ecosystem governance and planning

Alternative water supply

Bulk water infrastructure

Integrated water management

Water governance and planning

Urban governance and planning

Social infrastructure

Infrastructure and built environment

MediumLow

High

= not applicablena

Figure9.7 | Assessment of the feasibility and effectiveness of observed climate adaptation responses under current climate conditions for 24 categories of

adaptation responses across regions of Africa. The assessment comprised evaluation of each adaptation category along six dimensions: for feasibility these were economic

viability, environmental sustainability, social validity, institutional relevance, and technological availability; and for effectiveness this was potential for risk reduction (considering current

climate conditions) (Williams etal., 2021). Fifty-six experts on the African region were consulted using a structured, expert-driven elicitation process to increase the coverage and

robustness of the continent-wide adaptation feasibility and effectiveness assessment in Williams etal. (2021). Assessment included both peer-reviewed articles and grey literature.

(Nziguheba et al., 2015; Ritzema et al., 2017). Yet many of these

options currently face low institutional and technological feasibility

(Figure9.7). Social and economic feasibility is higher, but barriers

include high cost of farm inputs (land, capital and labour), lack of

access to timely weather information and lack of water resources can

make this option quite challenging for African smallholder farmers

(Sections9.8.1; 9.11.4; Kihila, 2017; Williams etal., 2019b).

Crop management includes adjusting crop choices, planting times, or the

size, type and location of planted areas (Altieri etal., 2015; Nyagumbo

et al., 2017; Dayamba etal., 2018). This option faces environmental,

institutional and technological barriers to feasibility. Social and

economic barriers to implementation are fewer. Factors such as tenure

and ownership rights, labour requirements, high investment costs and

lack of skills and knowledge on how to use the practices are reported

to hinder implementation of crop management options by smallholder

farmers (Muller and Shackleton, 2013; Nyasimi etal., 2017). For instance,

when improved seed varieties are available, high price limits access for

rural households (Amare etal., 2018; see Sections9.8.3; 9.8.4).

Human migration was assessed to have high potential for risk

reduction (Cross-Chapter Box MIGRATE in Chapter 7, Box 9.8; Rao

et al., 2019; Sitati et al., 2021). However, it had low feasibility for

economic, institutional and technological dimensions, with limited

evidence on environmental feasibility. Institutional factors such

as the implementation of top-down policies have been reported as

limiting options for coping locally, resulting in migration (Brockhaus

et al., 2013). Limited ﬁnancial and technical support for migration

limits the extent to which it can make meaningful contributions to

climate resilience (Djalante etal., 2013; Trabacchi and Mazza, 2015).

International and domestic remittances are an important resource that

can help aid recovery from climate shocks, but inadequate ﬁnance

and banking infrastructure can limit cash transfers (Box 9.8). Male

migration can increase burdens of household and agricultural work,

1304

Chapter 9 Africa

especially for women (Poudel etal., 2020; Rao etal., 2020; Zhou etal.,

2020). The more agency migrants have (that is, degree of voluntarity

and freedom of movement), the greater the potential beneﬁts for

sending and receiving areas (high agreement, medium evidence)

(Cross-Chapter BoxMIGRATE in Chapter 7; Box9.8)

Adaptation options within a number of categories, including sustainable

agriculture practices, agricultural intensiﬁcation, ﬁsheries management,

health advisory services and education, social infrastructure,

infrastructure and built environment, and livelihood diversiﬁcation,

were observed to reduce socioeconomic inequalities (Williams etal.,

2021). Whether adaptation options reduce inequality can be a key

consideration enhancing acceptability of policies and adaptation

implementation (Box9.1; Section9.11.4; Islam and Winkel, 2017).

9.3.2 Adaptation Co-Beneﬁts and Trade-Offs with

Mitigation and SDGs

Synergies between the adaptation to climate change and progress

towards the SDGs present potential co-beneﬁts for realising multiple

objectives towards climate resilient development in Africa, increasing

the efﬁciency and cost-effectiveness of climate actions (Cohen etal.,

2021). However, designing adaptation policy under conditions of

scarcity, common to many African countries, can inadvertently lead to

trade-offs between adaptation options, as well as between adaptation

and mitigation options, can reinforce inequality, and fail to address

underlying social vulnerabilities (Kuhl, 2021).

Adaptation options, such as access to climate information, provision

of climate information services, growing of early maturing varieties,

agroforestry systems, agricultural diversiﬁcation and growing of

drought-resistant varieties of crops may deliver co-beneﬁts, providing

synergies that result in positive outcomes. For instance, in sub-

Saharan African drylands including northern Ghana and Burkina Faso

and large parts of the Sahel, migration as a result of unfavourable

environmental conditions closely linked to climate change has

often provided opportunities for farmers to earn income (SDG 1)

and mitigate the effects of climate-related ﬂuctuations in crop and

livestock productivity (SDG 2) (Zampaligré etal., 2014; Antwi-Agyei

etal., 2018; Wiederkehr etal., 2018). Renewable energy can mitigate

climate effects (SDG 13), improve air quality (SDG 3), wealth and

development (SDGs 1, 2).

Different types of irrigation including drip and small-scale irrigation can

contribute towards increased agricultural productivity (SDG 2), improved

income (SDG 1) and food security (SDG 2) and increase resilience to

long-term changes in precipitation (SDG 13) (Bjornlund etal., 2020).

In Kenya and Tanzania, small-scale irrigation provides employment

opportunities and income to both farmers and private businesses (SDGs

8 and 9) (Lefore etal., 2021; Simpson etal., 2021c). Land management

practices including the use of fertilizers and mulching have also been

highlighted as adaptation options improving soil fertility for better

yields (SDG 2) and delivering opportunities to reduce the climate

change effects (SDG 13) (Muchuru and Nhamo, 2019).

Climate-smart agriculture (CSA) offers opportunities for smallholder

farmers to increase productivity (SDG 2), build adaptive capacity while

reducing the emission of GHGs (SDG 13) from agricultural systems

(Lipper et al., 2014; Mutenje et al., 2019). CSA practices including

conservation agriculture, access to climate information, agroforestry

systems, drip irrigation, planting pits and erosion control techniques

(Partey etal., 2018; Antwi-Agyei etal., 2021) can improve soil fertility,

increase yield and household food security (Zougmoré et al., 2016;

Zougmoré etal., 2018), thereby contributing to the realisation of SDG

2 in Africa (Mbow etal., 2014).

In contrast, adaptation actions may induce trade-offs with mitigation

objectives, as well as other adaptation and developmental outcomes,

delivering negative impacts and compromising the attainment of

the SDGs. For example, increased deployment of renewable energy

technologies can drive future land use changes (Frank etal., 2021) and

threaten important biodiversity areas if poorly deployed (Rehbein etal.,

2020). The use of early maturing or drought-tolerant crop varieties may

increase resilience (SDGs 1, 2), but adoption by smallholder farmers

can also be hindered by affordability of seed. Cultivation of biodiesel

crops also can hinder food security (SDG 2) at local and national

levels (Tankari, 2017; Brinkman etal., 2020). Additionally, the use

offertilizers in intense systems can result in increased environmental

degradation (Akinyi et al., 2021). When farmers migrate, it puts

pressure on inadequate social services provision and facilities at

their destination (SDG 8) and leads to reduced farm labour and a

deterioration of the workforce and assets (SDG 2) (Gemenne and

Blocher, 2017a), which negatively affects farm operations and non-

migrants, particularly women, elderly and children, at the point of

origin (Nyantakyi-Frimpong and Bezner-Kerr, 2015; Ahmed etal., 2016;

Otto etal., 2017; Eastin, 2018). Farmers may also miss critical periods

during the farming season that eventually makes them food insecure

(SDG 2) and vulnerable to climate change (SDG 13) (Antwi-Agyei etal.,

2018). Migrants should be supported to reduce their overall shocks

to climate vulnerability at the points of origin and destination. Small-

scale irrigation infrastructure if not managed properly, may lead to

negative environmental effects and compromise the integrity of

riparian ecosystems (SDG 15) (Loucks and van Beek, 2017) and serve

as breeding grounds for malaria-causing mosquitoes (SDG 3) (Attu and

Adjei, 2018).

9.4 Climate Resilient Development

Climate resilient development (CRD) is a process of implementing

GHG mitigation and adaptation measures to support sustainable

development for all (Denton et al., 2014; Andrijevic et al., 2020;

Owen, 2020; Cornforth etal., 2021). It emphasises equity as a core

element of sustainable development as well as conditions for inclusive

and sustained economic growth, shared prosperity and decent work

for all, taking into account different levels of national development

and capacities as encoded in the SDGs (Section 9.3.2; Chapter 18

Section 18.1). This section identiﬁes ﬁve key dimensions of CRD for

Africa: climate ﬁnance, governance, cross-sectoral and transboundary

solutions, adaptation law, and climate services and literacy.

1305

Africa Chapter 9

9.4.1 Climate Finance

Access to adequate ﬁnancial resources is crucial for climate change

adaptation (Cross-Chapter Box FINANCE in Chapter 17). Since the

Copenhagen Accord (UNFCCC, 2009), and then extended by the Paris

Agreement (UNFCCC Paris Agreement, 2015 see Article 4.4, and also 4.8,

4.9), developed countries are expected to scale up climate ﬁnance for

developing countries toward a collective goal of USD100billion per year

by 2020, with a balanced allocation between adaptation and mitigation.

9.4.1.1 How Much Adaptation Finance is Needed?

There is limited research providing quantitative estimates of

adaptation costs across Africa. Adaptation costs in Africa have been

estimated at USD 7–15 billion per year by 2020 (Schaeffer et al.,

2013), corresponding to USD5–11 per capita per year. The African

Development Bank estimates costs of near-term adaptation needs

identiﬁed in the Intended NDCs (INDCs) of African countries as

USD7.4 billion per year from 2020, recognising INDCs describe only

a limited subset of adaptation needs (AfDB, 2019). Many African

countries, particularly Least Developed Countries (LDCs), express

a stronger demand for adaptation ﬁnance—a study of ﬁnancial

demands in INDCs for 16 African countries suggests a ratio around

2:1 for adaptation to mitigation ﬁnance with demand for Eritrea and

Uganda approximately 80% for adaptation (Zhang and Pan, 2016).

Adaptation costs in Africa are expected to rise rapidly as global

warming increases (high conﬁdence). A meta-analysis of adaptation

costs identiﬁed in 44 NDCs and National Adaptation Plans (NAPs)

from developing countries estimated a median adaptation cost around

USD 17 per capita per year for 2020–2030 (Chapagain et al., 2020).

Adaptation cost estimates for Africa increase from USD20–50 billion

per year for Representative Concentration Pathway (RCP) 2.6 in 2050

(around 1.5°C of warming), to USD18–60billion per year for just over

2°C, to USD100–437billion per year for 4°C of global warming above

pre-industrial levels (Schaeffer etal., 2013; UNEP, 2015; Chapagain etal.,

2020). Focusing on individual sectors, the average country-level cost is

projected to be USD 0.8billion per year for adapting to temperature-

related mortality under 4°C global warming (Carleton etal., 2018), with

cumulative energy costs for cooling demand projected to reach USD

51billion by 2°C and USD 486billion by 4°C global warming (Parkes

et al., 2019). Transport infrastructure repair costs are also projected

to be substantial (Section 9.8.2) More precise estimates are limited

by methodological difﬁculties and data gaps for costing adaptation,

uncertainties about future levels of global warming and associated

climate hazards, and ethical choices such as the desired level of

protection achieved (Fankhauser, 2010; Hallegatte etal., 2018; UNFCCC,

2018) (Cross-Chapter Box FINANCE in Chapter 17). As such, existing

estimates are expected to substantially underestimate eventual costs

with adaptation costs possibly 2–3 times higher than current global

estimates by 2030, and 4–5times higher by 2050 (UNEP, 2016a).

9.4.1.2 Beneﬁt–Cost Ratios in Adaptation

Although analysts face challenges related to the nature of climate

change impacts (Sussman etal., 2014) and data limitations (Li etal.,

2014) when estimating all costs and beneﬁts for adaptation measures in

speciﬁc contexts, adaptation generally is cost-effective (high conﬁdence).

The Global Commission on Adaptation estimated the beneﬁts and costs

of ﬁve illustrative investments and found beneﬁt–cost ratios ranging

from 2:1 to 10:1. However, it also noted that ‘actual returns depend on

many factors, such as economic growth and demand, policy context,

institutional capacities and condition of assets’ (The Global Commission

on Adaptation, 2019). A review of ex-ante cost–beneﬁt analyses for 19

adaptation-focused projects in Africa ﬁnanced by the Green Climate

Fund (GCF) shows beneﬁt–cost ratios in a similar range. Using a

10% discount rate, as used by many of GCF’s accredited entities, the

beneﬁt–cost ratio for individual projects ranges from 0.9:1 to 7.3:1, the

median beneﬁt–cost ratio is 1.8:1 and total ratio across all 19 projects is

2.6:1. When using lower discount rates, as some entities do for climate

projects, the beneﬁt–cost ratio is even higher, reﬂecting the front-loaded

costs and back-loaded beneﬁts of many adaptation investments. Using

a 5% discount rate, the overall beneﬁt–cost ratio of the GCF projects

is 3.5:1, with a range from 1:1 to 11.5:1 and a median ratio of 2.4:1

(Breitbarth, 2020). In addition, many proposals have activities for which

further beneﬁts were not estimated due to the difﬁculty of attributing

beneﬁts directly to the intervention. The beneﬁts of adaptation measures

for infrastructure and others with clear market impacts are often easier

to estimate than for policy interventions and where markets may not

exist, such as ecosystem services (Li etal., 2014).

9.4.1.3 How Much Finance is Being Mobilised?

The amounts of ﬁnance being mobilised internationally to support

adaptation in African countries are billions of US dollars less than

adaptation cost estimates, and ﬁnance has targeted mitigation more

than adaptation (high conﬁdence). The Organisation for Economic Co-

operation and Development (OECD (2020) estimates an average of

USD 17.3 billion per year in public ﬁnance targeting mitigation and

adaptation from developed countries to Africa in 2016–2018, with

adaptation expected to be a small share of this amount. Of the global

total, only 21% in 2018 targeted adaptation (there is no breakdown

provided for Africa). Analysis of OECD data that is reported by the

funders, covering bilateral and multilateral funding sources, estimated

international public ﬁnance (grants and concessional lending) committed

to Africa for climate change for 2014–2018 at USD49.9 billion: 61%

(30.6billion) for mitigation, 33% (16.5billion) for adaptation and 5%

(2.7billion) for both objectives simultaneously (Figure9.8a; Savvidou

etal., 2021). This equates to an average of USD3.8 billion per year

targeting adaptation (Savvidou etal., 2021). In per capita terms, only

two countries (Djibouti and Gabon) were supported with more than

USD15 per person per year, most were supported with less than USD5

per person per year (Savvidou etal., 2021).

The multilateral development banks (MDBs) report 43% of their climate-

related commitments to sub-Saharan Africa in 2018 targeted adaptation

(EBRD etal., 2021). Sources other than international public ﬁnance are

more difﬁcult to track and there is limited data on Africa (Cross-Chapter

Box FINANCE in Chapter 17). Considering a wider range of ﬁnance

types (including private ﬂows and domestic mobilisation), an estimated

annual average of roughly USD19billion in climate ﬁnance for 2017–

2018 went to sub-Saharan Africa, of which only 5% was for adaptation

(CPI, 2019; Adhikari and Safaee Chalkasra, 2021). The mobilisation of

private ﬁnance by developed country governments, through bilateral and

1306

Chapter 9 Africa

Climate finance commitments targeting African countries and regions

Multilateral

development

banks

Climate funds

Other

multilaterals

Multilateral sources

Bilateral sources

Adaptation and mitigation

simultaneously

2,742

Adaptation

16,489

World Bank

Ireland

Canada

Sweden

Norway

Germany

United States

United Kingdom

France

EU Institutions (excl. EIB)

European Bank for

Reconstruction and Development

Other

Netherlands

African Development Bank

European Investment Bank

Green Climate Fund

Global Environment Facility

Climate Investment Funds

Adaptation Fund

International Fund for

Agricultural Development

5,825

153

231

308

273

697

900

1,313

1,572

1,466

441

624

150

2,612

188

1,041

376

178

127

754

Eastern

Africa

5,630

Western

Africa

4,816

Regional

allocations

2,663

Central

Africa

1,443

Southern

Africa

2,059

Northern

Africa

2,619

(a) Total adaptation-related finance (commitments) to African countries and regions, by source and recipient regions, 2014-2018

(b) Trend of adaptation-related finance

commitments to African regions over time

Adaptation-related

finance

1,000

2,000

3,000

4,000

5,000

commitments by country, 2014–2018

Kenya

Ethiopia

3,323

3 216

Morocco

5,916

Tunisia1,871

Nigeria

1,897

Uganda

1,650

Mozambique932

Algeria

53 0

Libya

Sudan

135

Egypt

6,906

Mauritania

189

Niger

666

Chad

193

Mali

775

Democratic

Republic of the

Congo

843

Namibia

221

South Africa

1,814 98 Lesotho

64 Eswatini

Angola

215

Tanzania

1,775

Malawi759

671

Zambia

Botswana

164 Zimbabwe

121

Somalia

166

Cameroon

850

101

South Sudan

Senegal 2,008

966 Rwanda

Burundi426

158

Togo

801

Ghana

Benin

588

825

Côte d’Ivoire

Burkina

Faso 732

Equatorial

Guinea

Congo

118

Gabon

208

Central

African Republic

Liberia 330

Sierra Leone 136

Guinea 311

Guinea-Bissau 157

Eritrea

Djibouti

157

Gambia 346

including financial commitments

that were reported separately from

allocations to individual countries

Regional allocations

5,936

Millions of USD

(constant prices)

Millions of USD (constant prices)

20182017201620152014

Western

Africa

Southern

Africa

Northern

Africa

Eastern

Africa

Regional

allocations

Central Africa

Total allocations

49,876

Adaptation

(33.1%)

Mitigation

(61.4%)

Adaptation

and mitigation

(5.5%)

Millions of USD

(constant prices)

Total

allocations

Figure9.8 | Total adaptation-related ﬁnance (commitments) to African countries and regions from 2014–2018 (USD millions, constant prices) as reported

to OECD.

(a) Flows of committed ﬁnance targeting adaptation by source and recipient region;

(b) trend over time in international development ﬁnance commitments targeting adaptation in Africa; and

(c) country-level shares of total climate ﬁnance commitments that targeted adaptation or mitigation or both simultaneously. Source: Savvidou etal. (2021).

1307

Africa Chapter 9

multilateral ﬁnancial support, is lower in Africa relative to other world

regions. Globally, in 2016–2018, Africa made up only 17% of mobilised

private ﬁnance relevant for climate change (OECD, 2020).

Strong differences exist among African sub-regions. Finance commitments

targeting adaptation increased from 2014–2018 for east and west Africa

but decreased in central Africa (Savvidou etal., 2021) (Figure 9.8b).

Climate-related ﬁnance was >50% for adaptation in 19countries, while

26 received >50% for mitigation (Savvidou etal., 2021).

African countries expect grants to play a crucial role in supporting

adaptation efforts because loans add to already high debt levels that

(a) Sectoral distribution of adaptation finance commitments to Africa 2014–2018

(b) Disbursement ratios for Africa compared to global average

region

Agriculture (30%) 5,715 Water supply and sanitation (20%) 3,770

Other multisector (12%) 2,221

General environment

protection (9%) 1,818

Agricultural

development

1,450

Agricultural policy

and administrative

management

1,401

Agricultural

land resources

472

Livestock

269

Agri-

cultural

research

226

Water supply - large systems

996

Water sector policy and

administrative management

976

Sanitation - large systems

868

Water supply

and sanitation -

large systems

494

Other

435

Rural development

903

Urban

development

and management

503

Disaster

Risk

Reduction

489

Other 325

Environmental policy

and administrative

management

1283

Bio-diversity

239

Agricultural

water resources

1,082

Other

813

Other

296

Other social

infrastructure

and services (4%)

Disaster

preparednes (4%)

Transport

and storage (3%)

Government and

civil society (2%)

Development

food

assistance (2%)

Other sectors (15%)

80%60%40%20%

Ratio of disbursements to commitments

100%80%60%40%20%0

Ratio of disbursements to commitments

Mitigation

56%

64%

Adaptation

46%

51%

Total

development 96%

33%

67%

71%

15%

48%

33%

85%

Western Africa

Southern Africa

Regional allocations

Northern Africa

Eastern Africa

Central Africa

(% of amounts committed)

Values in millions of USD

Adaptation finance commitments for Africa focused most on agriculture and water,

and disbursement ratios for climate-related finance were very low

World

Africa

Figure9.9 | Adaptation ﬁnance for Africa has focused most on agriculture and water, and disbursement ratios for climate-related ﬁnance are very low

(a) The amounts of ﬁnance targeting adaptation committed to different sectors across Africa from 2014–2018 in millions of USD as reported to OECD and including multilateral

development banks (Savvidou etal., 2021).

(b) Disbursement ratios (disbursements expressed as percentage of commitments) for ﬁnance targeting mitigation and adaptation, and for total development ﬁnance; showing

disbursement ratios for Africa compared to global average; and

(c) disbursement ratios for adaptation ﬁnance broken down by each African sub-region for 2014–2018 (for all funders reporting to OECD except multilateral development banks).

Source: Savvidou etal. (2021).

1308

Chapter 9 Africa

exacerbate ﬁscal challenges, especially in light of high sovereign debt

levels from the COVID-19 pandemic (Bulow etal., 2020; Estevão, 2020).

From 2014–2018, more ﬁnance commitments targeting adaptation

in Africa were debt instruments (57%) than grants (42%) (Savvidou

etal., 2021).

For Africa combined, the sectors targeted with most support for

adaptation are agriculture and water supply and sanitation, which

account for half of total adaptation ﬁnance from 2014–2018

(Figure9.9a). The sectoral distribution has changed little over these

years, suggesting adaptation planners and funders are maintaining a

relatively narrow view of where support is needed and how to build

climate resilience (Savvidou etal., 2021).

However, to understand actual expenditure on adaptation, it is necessary

to look at disbursements (that is, the amounts paid out compared to

committed amounts). Low ratios of disbursements to commitments

suggest difﬁculties in project implementation. Disbursement ratios for

climate-related ﬁnance from all funders other than MDBs (for which

data is not published) in Africa are very low (Figure9.9b; Savvidou etal.,

2021). Only 46% of 2014–2018 commitments targeting adaptation

were dispersed (Savvidou etal., 2021). Regions faring worst are north

Africa (15%), central Africa (33%) and west Africa (33%) (Figure9.9c).

These disbursement ratios for adaptation and mitigation ﬁnance in

Africa are lower than the global average (Savvidou etal., 2021), which

suggests greater capacity problems in implementing climate-related

projects and, in turn, means lost opportunities to build resilience and

adaptive capacity and a wider gap in adaptation ﬁnance for Africa

(Omari-Motsumi etal., 2019).

9.4.1.4 What Are the Barriers and Enabling Conditions for

Adaptation Finance?

The present situation reﬂects not only an insufﬁcient level of ﬁnance

being mobilised to support African adaptation needs (Section9.4.1)

but also problems in accessing and using funding that is available.

The direct-access modality introduced by the Adaptation Fund

and GCF, whereby national and regional entities from developing

countries can be accredited to access funds directly, is aimed at

reducing transaction costs for recipient countries, increasing national

ownership and agency for adaptation actions, and enhancing decision-

making responsibilities by national actors, thereby contributing to

strengthening local capacity for sustained and transformational

adaptation (CDKN, 2013; Masullo etal., 2015). Indeed, direct-access

projects from the Adaptation Fund tend to be more community

focused than indirect-access projects (Manuamorn and Biesbroek,

2020). Country institutions in Africa, however, are struggling to be

accredited for direct access because of the complicated, lengthy

and bureaucratic processes of accreditation, which requires, for

example, strong institutional and ﬁduciary standards and capacity

to be in place (Brown etal., 2013; Omari-Motsumi etal., 2019). As

of December 2019, over 80% of all developing countries had no

national direct access entities (DAEs) (Asfaw etal., 2019). Capacity

to develop fundable projects in Africa is also inadequate. An analysis

of proposals submitted to the GCF up to 2017 revealed that, while

African countries were able to submit proposals to the GCF, they

had the lowest percentage of approvals (39%) compared to all other

regions (Fonta etal., 2018). This suggests the quality of proposals

and therefore the capacity to develop fundable proposals remains

inadequate in the region.

Even when accredited, some countries experience signiﬁcant institutional

and ﬁnancial challenges in programming and implementing activities to

support concrete adaptation measures (Omari-Motsumi etal., 2019). Low

disbursement ratios suggest inadequate capacity to implement projects

once they are approved (Savvidou etal., 2021). Systemic barriers have

been highlighted in relation to the multilateral climate funds, including

funds not providing full-cost adaptation funding, capacity barriers in

the design and implementation of adaptation actions (including the

development of fundable project proposals) and barriers in recognising

and enabling the involvement of sub-national actors in the delivery and

implementation of adaptation action (Omari-Motsumi etal., 2019). As

of 2017, most GCF disbursements to Africa (61.9%) were directed to

support national stakeholders’ engagement with regards to readiness

activities, with only 11% directed to support DAEs in implementation

of concrete projects/pipeline development (Fonta etal., 2018). While

supporting readiness activities is important for strengthening country

ownership and institutional development, research suggests adaptation

ﬁnance needs to shift towards implementation of concrete projects and

more pipeline development if the goal of transformative and sustained

adaptation in Africa is to be realised (Fonta et al., 2018; Omari-

Motsumi etal., 2019). The source of these problems needs to be better

understood so that the prospects for future climate-related investments

can be improved and institutional strengthening and targeted project

preparation can be supported (Omari-Motsumi etal., 2019; Doshi and

Garschagen, 2020; Savvidou etal., 2021).

Some progress has been made in supporting developing countries

to enhance their adaptation actions. The process to formulate and

implement NAPs was established by parties under the UNFCCC to

support developing countries in identifying their vulnerabilities, and

determine their medium- and long-term adaptation needs (UNFCCC

Paris Agreement, 2015). NAPs provide a means of developing and

implementing strategies and programmes to address those needs. In

2016, the parties agreed the GCF would fund up to USD3million per

country for adaptation planning instruments, including NAPs. However,

accessing funding through the GCF for NAP formulation is challenging

(Fonta etal., 2018) and, as of October 2020, 4years after the decision

to fund NAPs, only six African countries had completed their NAPs

(UNFCCC NAP central). The next step is to convert adaptation planning

documents into programming pipeline projects that are fundable

and implementable, which presents a signiﬁcant barrier to enhanced

adaptation action (Omari-Motsumi etal., 2019).

Adaptation ﬁnance has not been targeted more towards more

vulnerable countries (Barrett, 2014; Weiler and Sanubi, 2019; Doshi

and Garschagen, 2020; Savvidou etal., 2021). Reasons for this include

fast-growing middle-income countries offering larger gains in emission

reductions, so ﬁnance has favoured mitigation in these economies,

even within sub-Saharan Africa, and as more climate ﬁnance uses debt

instruments, mitigation projects are further preferred because returns

are perceived to be more certain (Rai etal., 2016; Lee and Hong, 2018;

Carty etal., 2020; Simpson etal., 2021c).

1309

Africa Chapter 9

Many adaptation interventions for most vulnerable countries and

communities provide no adequate ﬁnancial return on investments

and can therefore only be funded with concessional public ﬁnance

(Cross-Chapter BoxFINANCE in Chapter 17). Yet, public funds alone

are insufﬁcient to meet rapidly growing adaptation needs. Public

mechanisms can help leverage private sector ﬁnance for adaptation by

reducing regulatory, cost and market barriers through blended ﬁnance

approaches, public–private partnerships, or innovative ﬁnancial

instruments and structuring in support of private sector requirements

for risk and investment returns, such as green bonds (Cross-Chapter

BoxFINANCE in Chapter 17). Sub-national actors can be core agents

to conceptualise, drive and deliver adaptation responses, and unlock

domestic resources in the implementation of adaptation action (CoM

SSA, 2019; Omari-Motsumi etal., 2019), provided they are sufﬁciently

resourced and their participation and agency are supported.

Many African countries are at high risk of debt distress, especially due

to the COVID-19 pandemic, and will need to decrease their debt levels

to have the ﬁscal space to invest in climate resilience (Estevão, 2020;

Dibley etal., 2021). As of mid-2021, the G20’s Debt Service Suspension

Initiative is providing temporary relief for repayment of bilateral credit,

but this has largely not been taken up by private lenders (Dibley etal.,

2021; World Bank, 2021). The total external debt-servicing payments

combined for 44 African countries in 2019 were USD75billion (World

Bank, 2019), far exceeding discussed levels of near-term climate

ﬁnance. Aligning debt relief with Paris Agreement goals could provide

an important channel for increased ﬁnancing for climate action, for

example, by allowing African countries to use their debt-servicing

payments to ﬁnance climate change mitigation and adaptation (Fenton

etal., 2014). Governments can disclose climate risks when taking on

sovereign debt, and debt-for-climate resilience swaps could be used

to reduce debt burdens for low-income countries while supporting

adaptation and mitigation (Dibley etal., 2021).

9.4.2 Governance

9.4.2.1 Governance Barriers

Overcoming governance barriers is a precondition to ensure successful

adaptation and CRD (Pasquini et al., 2015; Owen, 2020). Despite

the ambitious climate targets across African countries and renewed

commitments in recent years (Zheng etal., 2019; Ozor and Nyambane,

2020), governance barriers include, among others, slow policy

implementation progress (Shackleton et al., 2015; Taylor, 2016),

incoherent and fragmented approaches (Zinngrebe et al., 2020;

Nemakonde etal., 2021), inadequate governance systems to manage

climate ﬁnance (Granoff etal., 2016; Banga, 2019), poor stakeholder

participation (Sherman and Ford, 2014), gender inequalities (Andrijevic

et al., 2020), unaligned development and climate agendas (Musah-

Surugu etal., 2019; Robinson, 2020), elite capture of climate governance

systems (Kita, 2019), hierarchical and complex state bureaucracy

(Meissner and Jacobs, 2016; Biesbroek et al., 2018) and weak, non-

existent or fragmented sub-national institutions (Paterson etal., 2017;

Musah-Surugu et al., 2019). Further, adaptation planning involves

cross-cutting themes, multiple actors and institutions with different

objectives, jurisdictional authority and levels of power and resources,

yet there is often a lack of coordination, clear leadership or governance

mandates (Shackleton etal., 2015; Leck and Simon, 2018) and unequal

power relations between African countries and developed countries can

hinder progress on governance of ﬁnancial markets, budget allocations

and technology transfer to address addressing climate technology gaps

in Africa (Rennkamp and Boyd, 2015; Olawuyi, 2018).

Policy implementation can be slow due to the absence of support

mechanisms and dependency on funding by international partners

(Leck and Roberts, 2015; Ozor and Nyambane, 2020). In many countries,

commitment to climate policy objectives is low (Naess etal., 2015),

particularly in light of competing development imperatives and post-

COVID-19 recovery efforts (Caetano etal., 2020), although COVID-19

recovery efforts offer signiﬁcant opportunities for health, economic

and climate resilience co-beneﬁts (Sections 9.4.3; 9.11.5; Cross-

Chapter BoxCOVID in Chapter 7). Another challenge relates to long-

term planning and decision making which is hampered by uncertainty

related to future socioeconomic and GHG emissions scenarios (Coen,

2021), political cycles and short-term political appointment terms

(Pasquini etal., 2015).

Lack of community agency in climate governance affects the capacity

for citizen-led climate interventions in Africa (Antwi-Agyei etal., 2015;

Mersha and Van Laerhoven, 2016). This is attributed partly to low civic

education, limited participation power of citizens and tokenism due

to perceived lack of immediate beneﬁts (Odei Erdiaw-Kwasie etal.,

2020), as well as low rates of climate change literacy in many regions

(Section9.4.3; Simpson etal., 2021a). Participation in climate policy

also extends to the private sector, which has been relatively uninvolved

in adaptation discussions to date (Crick etal., 2018).

Africa requires substantial resources and support to adapt to the

unavoidable consequences of climate change, a pertinent climate

justice concern for governments. However, the mechanisms needed to

redress current power imbalances, structural and systemic inequality

are often absent (Saraswat and Kumar, 2016; see Section 9.11.4)

and policies that underpin environmental justice concerns, including

distributive justice, participation, recognition and capability (Shi etal.,

2016; Chu etal., 2017) are also needed.

9.4.2.2 Good Governance

Good governance can contribute to positive climate outcomes and

CRD in Africa through long-term planning, development-focused policy

environments, the development of robust and transformational policy

architecture, inclusive participation and timely implementation of NDCs

(Bataille etal., 2016; Werners etal., 2021; see Table9.3 for examples).

African governments are developing and revising ambitious adaptation

policies that are enforceable and aligned with wider societal

development goals, including an enabling environment for ﬁnance and

investment in the jobs and skills development necessary to support

a just transition (Section9.4.5; ILO, 2019). If appropriately designed,

such institutions offer the opportunity to foster adaptive governance

that is collaborative, multi-level and decentralised, offering integration

of policy domains, ﬂexibility and an emphasis on non-coerciveness and

adaptation (Ruhl, 2010).

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Chapter 9 Africa

Coordination across multiple sectors, supported with leadership from

the highest levels of government, has shown to improve implementation

effectiveness and anticipated scaling up (Rigaud etal., 2018). This high-

level engagement promotes the inclusion of climate resilience and

adaptation targets in national planning and budgeting. Financial and

capacity support is essential (Adenle etal., 2017; UNEP, 2021), as is

the tracking of national progress towards development goals (Box9.6).

In Africa, climate governance occurs in a context of deep inequality

and asymmetric power relations—both within countries and between

countries—making adequate mechanisms for multi-stakeholder

participation essential (Sapiains etal., 2021). This requires the creation

of avenues for the voices of marginalised groups in policy processes

and enabling policy environments that can catalyse inclusive action

and transformational responses to climate change (Totin etal., 2018;

Revi et al., 2020; Ziervogel et al., 2021), safeguarding protection

against the climate harms of the most vulnerable in society, particularly

of women and children (see also Box9.1). Community-based natural

resource management in pastoral communities was observed to

improve institutional governance outcomes through involving

community members in decision making, increasing the capacity of

these communities to respond to climate change (Reid, 2014).

Speciﬁc indicators can be included in the performance metrics and

monitoring frameworks for each sector, policy intervention and budget

planning cycle (Wojewska etal., 2021). Many countries in Africa are also

revamping their institutional coordination mechanisms to reﬂect an all-

of-government approach and partnership with non-state stakeholders

with diverse capabilities and expertise (see examples from Rwanda

and Zambia in Table9.3). This includes Cape Town’s drought response

in 2017/2018 where non-state actors actively partnered with the state

response around water management/savings practices (Simpson etal.,

2020a; 2020b; Cole etal., 2021b).

9.4.3 Cross-sectoral and Transboundary Solutions

Climate change does not present its problems and opportunities

conveniently aligned with traditional sectors, so mechanisms are

needed to facilitate interactions and collaborations between people

Table9.3 | Characteristics and examples of governance that contribute towards CRD in Africa.

Governance characteristic Example

Long-term development planning

Countries are mainstreaming adaptation into their long-term development cycles (UNFCCC Adaptation Committee, 2019). For example, Burkina Faso’s

National Adaptation Plan elaborates its perspective to 2050 and links to its development pathways (Government of Burkina Faso, 2015). Many African

countries are also enhancing the adaptation components of their long-term low emissions strategies.

Climate justice and

inequality-focused policies

Climate policies can be designed to include speciﬁc policy mechanisms (e.g., carbon taxes, renewable energy subsidies) to maximise developmental

gains while reducing inequality (Andrijevic etal., 2020). For example, revenues from a carbon tax can be used to increase social assistance

programmes that beneﬁt poor people and reduce their vulnerability to climate change (Hallegatte etal., 2016). Climate risk management can be

integrated into social protection and assistance programmes, such as public works programmes that increase climate resilience (Section9.11).

Interlinkages between adaptation

and development pathways

Cross-sectoral and multi-level governance approaches can harness synergies with the SDGs, Paris Agreement and Agenda 2063 aspirations, helping

to counter the adaptation deﬁcit, promote sustainable resource use and contribute to poverty reduction (Niang etal., 2014; IPBES, 2018; Roy etal.,

2018b). Ghana, Namibia, Rwanda and Uganda all link adaptation with disaster risk reduction in their NDCs (UNFCCC Adaptation Committee, 2019).

High-level engagement

Climate policies, traditionally overseen by environment ministries, are increasingly receiving priority from ﬁnance and planning ministries. Zambia’s

Climate Change Secretariat is currently led by the Ministry of Finance (Government of the Republic of Zambia, 2010), while Tanzania’s environmental

division sits in the ofﬁce of the Vice-President (Governmet of the United Republic of Tanzania, 2011).

All-of-government approach

In Kenya, the Climate Change Directorate is the secretariat for the National Climate Change Commission, serving as an overarching mechanism

to coordinate sectoral and county-level action (Government of the Republic of Kenya, 2018). In South Africa, the National Committee on Climate

Change, the Intergovernmental Committee on Climate Change and the Presidential Climate Change Commission have been established to enhance

intergovernmental and multi-sectoral coordination on climate action (Climate Action Tracker, 2021).

Participatory engagement

Polycentric, bottom-up and locally implemented approaches are more able to include the emergence of new actors (e.g., city networks, multinational

companies and sub-state entities), new instruments and levels (soft law instruments or transnational dynamics) and new guiding principles and

values (fairness, transparency and co-participation) (Leal Filho etal., 2018; Sapiains etal., 2021). Case studies include the community-based,

participatory scenario planning approach used in Malawi to generate information for farmers from seasonal forecasts, as well as the integration

of climate risk into Lusaka’s Strategic Plan through engagement with city planners (Conway and Vincent, 2021; Vincent and Conway, 2021). Many

innovative solutions have been designed to promote participation, such as Pamoja Voices toolkits in pastoralist communities in northern Tanzania

(Greene etal., 2020).

Inclusive and diverse stakeholders

Kenya’s Climate Change Directorate has a designated team to integrate gender into its national climate policies (Murray, 2019), while Seychelles’

National Climate Change Council has allocated a seat exclusively for a youth candidate (Government of The Seychelles, 2020). Tanzanian

Climate-Smart Agriculture Alliance supports the integration of farmers and builds strategic alliances to support climate processes (Nyasimi etal.,

2017).

Partnerships

Ghana, Kenya, Uganda and Zambia are developing anticipatory scenarios for low-carbon CRD pathways for the agricultural sector, aimed at informing

input into national climate policy (Balié etal., 2019). This science to policy to practice interface is bridged through the inclusion of policymakers,

practitioners and academics (Dinesh etal., 2018). In Lusaka, Durban and other African cities, processes of engagement and learning have built the

trust and capacities needed to inform city-scale, climate-resilient decisions and associated actions (Taylor etal., 2021a; Taylor etal., 2021b).

Nationally Determined

Contributions (NDC)

implementation

Rwanda has developed an indicator-based monitoring, reporting and veriﬁcation (MRV) framework for tracking its NDC implementation and

associated ﬁnancial ﬂows (Government of Republic of Rwanda, 2020). Zambia has also integrated gender indicators into its NDC implementation

plan and is incorporating gender considerations into its MRV framework (Murray, 2019).

1311

Africa Chapter 9

working in widely different sectors (Simpson etal., 2021b). Traditional

risk assessments typically only consider one climate hazard and one

sector at a time, but this can lead to substantial misestimation of risk

because multiple climate risks can interact to cause extreme impacts

(Zscheischler etal., 2018; Simpson etal., 2021b).

Because multiple risks are interlinked and can cascade and amplify

risk across sectors, cross-sectoral approaches that consider these

interlinkages are essential for CRD, especially for managing trade-offs

and co-beneﬁts among SDGs, mitigation and adaptation responses

(Liu etal., 2018a).

In Africa, placing cross-sectoral approaches at the core of CRD provides

signiﬁcant opportunities to deliver large beneﬁts and/or avoided

damages across multiple sectors including water, health, ecosystems

and economies (very high conﬁdence) (Boxes 9.5; 9.6; 9.7). They can

also prevent adaptation or mitigation action in one sector exacerbating

risks in other sectors and resulting in maladaptation, for example, from

large-scale dam construction or large-scale afforestation (e.g., water–

energy–food nexus and large-scale tree planting efforts) (Boxes 9.3;

9.5).

Cross-sectoral or ‘nexus’ approaches can improve the ability of

decision makers to foresee and prevent major climate impacts. Barriers

to developing nexus approaches arise from rigid sectoral planning,

regulatory and implementation procedures, entrenched interests, and

power structures and established sectoral communication structures.

Opportunities for overcoming these barriers include creating a

dedicated home for co-development of nexus risk assessment

and solutions, promoting co-leadership of projects by multiple

sectors, speciﬁc budget allocations for nexus projects, facilitating

and coordinating services, compiling useful strategies into toolkits,

ameliorating inequitable power relations among participants and

measuring progress on nexus approaches through metrics (Palmer

etal., 2016; Baron etal., 2017).

Beyond cross-sectoral collaboration, international cooperation is vital

to avert dangerous climate change as its impacts reach beyond the

jurisdiction of individual states. International good practice and regional

agreements, protocols and policies together recognise that regional

integration, cooperative governance and beneﬁt-sharing approaches

are cornerstones of effective resource security and climate change

responses in Africa (Jensen and Lange, 2013; World Bank, 2017a;

Dombrowsky and Hensengerth, 2018). Natural resource development,

particularly governance of shared river basins, exempliﬁes opportunities

for governance responses for African nations that can be cooperative,

regionally integrated and climate resilient.

In Africa, climate vulnerability crosses geopolitical divides as regional

clusters of fragile and high vulnerability countries exist, emphasising

the need for transboundary cooperation (Birkmann etal., 2021; Buhaug

and von Uexkull, 2021). Natural resource security is increasingly reliant

on transboundary governance, regional integration and cooperation

(Namara and Giordano, 2017). There are 60 international or shared river

basins on the continent, a function of colonial divides and topography,

with some basins shared by four or more countries (UNECA, 2016;

Popelka and Smith, 2020). Climate changes which result in impact

and risk pathways across country boundaries and regions (although

with different levels of impact) accelerate the urgency for integrated

approaches to manage and beneﬁt from shared resources and promote

their security for populations and economies (Namara and Giordano,

2017; Frame etal., 2018; Carter etal., 2021). At the same time, natural

resources such as water generate economic beneﬁts shared across

boundaries, such as hydroelectric power generation and regional food

security (Dombrowsky and Hensengerth, 2018).

Poor governance, particularly at the transboundary level, can undermine

water security and climate change is likely to add new challenges to pre-

existing dynamics, emphasising the necessity of formal transboundary

arrangements (Jensen and Lange, 2013; UNECA, 2016). Further, it can

constrain access to critical ﬁnancial resources at a time when it is

needed most. This is particularly the case when climate impact pathways

manifest at the transboundary level (Challinor et al., 2018; Simpson

etal., 2021b), but where the need to protect sovereign interests can

block regionally integrated institutional arrangements that are pivotal

for accessing the multilateral climate funds for transboundary climate

investments that include resilient infrastructure and greater water

beneﬁts across Africa’s shared river basins (Cross-Chapter BoxINTEREG

in Chapter 16; Carter etal., 2021).

In response, the African Development Bank is supporting two of the

most climate-vulnerable and larger African river basins to leverage GCF

and Global Environment Facility (GEF) funds to ﬁnance Programmes for

Integrated Development and Adaptation to Climate Change (PIDACC).

PIDACC ﬁnance is approved at the multinational level in the Niger basin

which is shared by nine west and central African States (AfDB, 2018c;

GCF, 2018a), while a PIDACC proposal is currently under development

for the Zambezi basin (Zambezi Watercourse Commission, 2021).

Stakeholders across Africa are recognising the scale and severity of

transboundary risks to water. Such risks are two-fold in nature, arising

both from potential impacts due to climate change and from responses

to climate change (Simpson et al., 2021b). This awareness among

stakeholders is leading to increasingly progressive approaches to natural

resource development that can also reduce risk across boundaries

within regions.For example, river basin organisations in Southern Africa

such as the Orange-Senqu and the Okavango River Basin Commissions

are revising treaties considered to pre-date the interrelated issues of

climate change, growing populations and water scarcity (OKACOM,

2020). In parts of west Africa, where climate change is characterised by

reduction of precipitation (Barry etal., 2018), regionally integrated and

climate-resilient economic investments for water resource development

are enabled by the Senegal River Basin Organisation (OMVS) which

emphasises programme and project development, ﬁnancing and

implementation in ensuing work plans (World Bank, 2020e), as does

the Nile Basin Initiative (NBI) in north and east Africa (Schmeier, 2017;

Blumstein and Petersen-Perlman, 2021).

Enhanced transboundary governance arrangements suggest that

countries are joining forces to coherently manage and protect natural

resources (Spalding-Fecher et al., 2014; AfDB, 2021). Underlying

governance issues and political economy interests block or advance

such transitions to regionally integrated resource management and

beneﬁt-sharing, the market drivers of water security (AMCOW, 2012;

1312

Chapter 9 Africa

Soliev etal., 2015). Angola, for example, outlines regional adaptation

as a priority and one of its unconditional adaptation strategies (which

is already funded) is enhancing resilience in the Benguela ﬁsheries

system, a project shared with Namibia and South Africa (GEF and FAO,

2021). Another example is The Great Green Wall for the Sahara and

Sahel Initiative, which was launched in 2007 with the aim of tackling

land degradation in Africa (UNCCD, 2020). This transboundary project,

led by the African Union Commission, is being implemented in more

than 20 countries across Africa’s Sahel region, in cooperation with

international partners including UNCCD, GEF and the World Bank.

Approximately USD10billion have been mobilised and/or promised

for this initiative (UNCCD, 2020). Such statements demonstrate

the increasing identiﬁcation of transboundary risks and approaches

to manage and adapt to them as areas of ‘common concern’ that

require cooperative adaptation actions. Accelerating strengthened

transboundary water and climate governance needs to integrate these

climate drivers of compromised water security. The role of institutions

such as OMVS and the NBI have demonstrated they can inﬂuence

economic behaviour among riparian countries of shared river basins

highlighting that institutions are an integral part of climate governance

in evolving economic systems (Hodgson, 2000).

9.4.4 Climate Change Adaptation Law in Africa

9.4.4.1 The Rise of Climate Change Adaptation Law

Robust legislative frameworks, both climate change speciﬁc and non-

speciﬁc, can foster adaptive responses to climate change, particularly

in LDCs (Nachmany etal., 2017). As discussed in Chapter 17, there

are many reasons for this. The successful implementation of policy

objectives across the continent is often contingent upon or at least

supported by an underlying legislative framework (Averchenkova and

Matikainen, 2017; Scotford etal., 2017). There are also wider systemic

and structural reasons for developing climate change legislation,

including the promotion of coordination within government, its policy

entrenching role, its symbolic value and its potential to support climate

ﬁnance ﬂows (Nachmany etal., 2017; Scotford and Minas, 2019).

Legal systems, however, also have the potential to be maladaptive.

Laws may be brittle, often assuming and reinforcing a static state, and

the boundary of the law may not align to the relevant location, scale or

impact (Craig, 2010; Arnold and Gunderson, 2013; Wenta etal., 2019).

This necessitates the review and revision of existing laws to remove

such barriers and foster adaptive management (Craig, 2010; Ruhl,

2010; Cosens etal., 2017) and, where necessary, the promulgation of

new laws.

There has been a rise in framework and sectoral climate change laws

across Africa, as illustrated in Figure 9.10. The map illustrates the

two framework statutes which have been promulgated in Benin and

Kenya, as well as the three framework bills which have been drafted

in Nigeria, South Africa and Uganda. There are also discussions taking

place in Zimbabwe and Ghana regarding the potential development of

a draft framework climate change bill. A review of the climate change

framework laws indicates evidence of cross-pollination in design across

African jurisdictions, creating the potential for a unique and regionally

Progress in development of climate change

framework law in Africa

Framework Bill under discussion

Framework Bill in draft form

Framework Law enacted

Law contains dedicated

climate change references

or considerations

No or limited information available

Cape Verde

São Tome and Principe

St. Helena

Mauritius

Réunion

Comoros

Mayotte

Seychelles

Figure9.10 |  Progress in development of climate change framework law

in Africa derived from an analysis of public databases of African laws,

data drawn from Government of Niger (1998); Government of Liberia (2002);

Government of Algeria (2004); Government of Tanzania (2004); Government of

Central African Republic (2008); Government of Lesotho (2008); Government of Togo

(2008); Government of Guinea Bissau (2011); Government of Ivory Coast (2012);

Government of Rwanda (2012); Government of Sierra Leone (2012); Government of

Cape Verde (2014); Government of Morocco (2014); Government of Mozambique

(2014); Government of Madagascar (2015); Government of the Seychelles (2015);

Government of Gabon (2016); Government of Kenya (2016); Government of Mali

(2016); Government of Zambia (2016); Government of Malawi (2017); Government

of Nigeria (2017); Government of Benin (2018); Government of Ghana (2018);

Government of South Africa (2018); Government of Uganda (2018); Government of

Zimbabwe (2019) sources quoted as of September 2019.

appropriate body of law with a strong focus on adaptation responses

(Rumble, 2019). As discussed in Chapter 17, however, there remains the

need for in-country expert input on how the domestic legal landscape

may inﬂuence their operation, and for each jurisdiction to independently

interrogate its adaptation needs and objectives (Scotford etal., 2017).

Numerous African states have also included dedicated climate change-

related provisions within various existing statutes that regulate

the environment or disaster management. For example, Tanzania’s

Environmental Management Act 20 of 2004 contains dedicated

provisions to address climate change. Rwanda’s Law on Environment

48/2018 also contains detailed provisions on mainstreaming climate

change into development planning processes, education on climate

change, vulnerability assessments and the promotion of measures

to enhance adaptive capacity. Some countries have also developed

laws dedicated to a speciﬁc aspect of adaptation. For example, the

Conservation and Climate Adaptation Trust of Seychelles Act 18 of 2015

establishes a trust fund to ﬁnance climate change adaptation responses

in Seychelles. Similarly, many countries including Algeria, Burkina Faso,

1313

Africa Chapter 9

Djibouti, Ghana, Namibia, Malawi, Mauritius, Madagascar, Mozambique,

Tanzania and South Africa have dedicated disaster management laws.

At this stage, it is still too early to determine whether these laws

are having any substantive inﬂuence in strengthening resilience and

reducing vulnerability and, as discussed in Chapter 17, this is identiﬁed

as a knowledge gap requiring further research.

9.4.4.2 Common Themes in Framework Laws

Laws are now being developed to formalise and entrench institutional

structures, specifying their mandate, function, membership and related

procedures. A useful example of such an approach can be found in the

Nigerian Climate Change Bill which establishes the National Climate

Council on Climate Change headed and chaired by the Vice-President,

with a wide membership of ministers, the Chairmen of the Governors’

Forum and Association of Local Governments, as well as the private

sector and non-governmental organisation (NGO) representatives.

Climate change framework laws can play an instrumental role in

achieving mainstreaming by directing relevant actors to integrate

adaptation considerations into existing mandates, operations and

planning instruments (Rumble, 2019). By way of example, the

South African Draft Climate Change Bill contains a general duty to

‘coordinate and harmonise the policies, plans, programmes and

decisions of the national, provincial and local spheres of government’

to achieve, among other things, the climate change objectives of the

Bill and national adaptation objectives.

Another common theme is the requirement to develop national climate

change adaptation strategies and plans. Many laws further entrench

their longevity by requiring them to be subject to strong community

participation and consultation, as demonstrated by the Kenyan Climate

Change Act and the Nigerian Climate Change Bill.

9.4.4.3 Local Climate Change Laws and Indigenous Knowledge

Systems

The Paris Agreement acknowledges, in Article 7.5, that adaptation

should be based on and guided by, among other things, ‘traditional

knowledge, knowledge of indigenous peoples and local knowledge

systems’. The accumulated knowledge within Indigenous knowledge

systems is particularly important as it can assist governments in

determining how the climate is changing, how to characterise these

impacts and provide lessons for adaptation (Salick and Ross, 2009).

In this context, Indigenous knowledge systems can play an important

role in the effective design of local laws (Mwanga, 2019), as well

as national laws. Doing so can contribute to the success of climate

change response strategies, including enhancing local participation

and the implementation of community-based and ecosystem-based

adaptations (Chanza and de Wit, 2016; Mwanga, 2019). For example,

the Makorongo Village Forest Management By-Law in Tanzania codiﬁes

local customary practices relating to forest management and sustainable

harvesting with associated dual adaptation and mitigation beneﬁts and

includes all villagers in the decision-making processes relating to forest

management (Mwanga, 2019). The inclusion of beneﬁcial Indigenous

knowledge systems within local by-laws is contingent on the active

involvement of members of the Indigenous community and awareness

of climate change considerations within the local sphere of government,

and a willingness to foster such practices (Mwanga, 2019).

In addition to the advancement of Indigenous knowledge in adaptive

responses, it has been suggested that the protection of the rights of

Indigenous Peoples can have adaptive beneﬁts, in particular through

the protection of land tenure rights (Ayanlade and Jegede, 2016). It

has been argued that doing so will protect Indigenous Peoples’ lands

and resources from overconsumption, secure the recognition of their

cultural stewardship over the environment, provide the ﬁnancial

incentive for land stewardship and promote the application of their

unique knowledge on the sustainable development of that land

and its preservation (Jaksa, 2006; Ayanlade and Jegede, 2016). Not

only can a lack of protection of Indigenous legal tenure undermine

these objectives, but a number of African laws may actively work

against them. For example, a review of Tanzanian and Zambian laws

highlighted existing provisions that empowered the state to terminate

or criminalise the occupation of vacant, undeveloped or fallow lands,

which undermined the occupation by Indigenous peoples of forests

and other uncultivated lands (Ayanlade and Jegede, 2016).

9.4.5 Climate Services, Perception and Literacy

Policy actors across Africa perceive that human-caused climate

change is already impacting their locales through a range of negative

socioeconomic and environmental effects (Pasquini, 2020; Steynor and

Pasquini, 2020). They are highly concerned about and motivated to

address these impacts (Hambira and Saarinen, 2015; Pasquini, 2020).

Transformative responses to the impacts of climate change facilitate

CRD and are informed by perceptions of climate variability and change

and climate change literacy (Figure9.11).

9.4.5.1 Climate Information and Services

Climate services (CS) broadly include the generation, tailoring and

provision of climate information for use in decision making at all levels

of society (Street, 2016; Vaughan etal., 2018). There is a range of climate

service providers in Africa, including primarily National Meteorological

and Hydrological Services (NMHS) and partner institutions,

complemented by NGOs, the private sector and research institutions

(Snow etal., 2016; Harvey et al., 2019), which offer the potential for

public–private partnerships (Winrock, 2018; Harvey etal., 2019).

International development funding has progressed the provision of

CS and, together with technological advances and capacity-building

initiatives, has increased the reliability of CS across Africa (Vogel

etal., 2019). Most CS investments have been towards the agricultural

sector, with other focal sectors, including pastoralism, health, water,

energy and disaster risk reduction, having only small CS initiatives

directed towards them (Nkiaka etal., 2019; Carr etal., 2020). Despite

this focus and investment, however, there remains a mismatch

between the supply and uptake of CS in Africa as information is

often inaccessible, unaffordable, not relevant to context or scale,

and is poorly communicated (Singh etal., 2018; Antwi-Agyei etal.,

2021) (Table9.4; Sections9.4.1.5.1 and 9.13.4.1). Observational data

required for effective regional CS, including trend analyses, seasonal

1314

Chapter 9 Africa

climate assessment, modelling and model evaluation, is sparse and

often of poor quality (Figure9.11) and usually requires payment which

renders it unaffordable (Winrock, 2018).

A number of these challenges can be addressed through the transdis-

ciplinary co-production of CS (Alexander and Dessai, 2019; Vogel etal.,

2019; Carter etal., 2020). Co-production of CS involves climate in-

formation producers, practitioners and stakeholders, and other knowl-

edge holders participating in equitable partnerships and dialogues to

collaboratively identify climate-based risk and develop scale-relevant

climate information to address this risk (Table9.4) (Vincent et al.,

2018; Carter etal., 2020).

The importance of climate services and climate change literacy

for more transformative responses to climate change in

Africa

(a)

Agreement/

no agreement of

perception and local

temperature records

No studies

No data

Agreement

No agreement

Agreement/

no agreement of

perception and local

precipitation records

Climate Change

Literacy Rate

No data

20–29%

30–39%

40–49%

50–59%

60–69%

No studies

No data

Agreement

No agreement

(b)

Perception of change

affects risk perception

and urgency

Transformative

Climate Response Climate services

provide information that

informs response

Experience and

perception of changes

Climate change

literacy

Figure9.11 |  Climate services and climate literacy are important for informing transformative responses to climate change (including adaptation and

mitigation responses)

(a) The importance of climate services and climate change literacy for more transformative responses to climate change in Africa adapted from Simpson etal. (2021a). Climate

services promote climate resilient development by providing climate information for adaptation decision making (Street, 2016; Vaughan etal., 2018). Scalable uptake of climate

services relies partly on climate risk perception of users, which is largely driven in Africa by experience and perception of local climate changes (Jacobs and Street, 2020; Steynor

etal., 2020b; Steynor and Pasquini, 2020). Perception of climate change can occur without knowledge of its human-induced causes and its effects (Lee etal., 2015; Alemayehu

and Bewket, 2017; Andrews and Smirnov, 2020). This can lead to coping responses to climate change which fall short of adaptation. Climate change literacy encompasses being

aware of climate change and its anthropogenic causes and, together with climate services, can strengthen responses to climate change through better understanding of future risk

(IPCC, 2019b; Simpson etal., 2021a).

(b, c) Percentage of studies that have recorded that perception of temperature changes and precipitation changes agreed with local meteorological or climate records across 33

African countries (size of bubble indicates number of studies per country for both b and c. In b, agreement with temperature changes is indicated for all studies within a country in

red, and articles indicating no agreement in orange; while in c, agreement with precipitation changes is indicated per country in dark blue and articles indicating no agreement in

light blue. A total of 144studies assessed across the 33countries).

(d) Country-level rates of climate change literacy for 33 African countries (i.e., percentage of the population that have heard about climate change and think that human activity

is wholly or partly the cause of climate change) Simpson etal. (2021a).

1315

Africa Chapter 9

Table9.4 | Challenges and opportunities for Climate Services in Africa for the supply and uptake of climate services.

Challenges Opportunities/solutions References Examples of programmes that address these

challengesa

Supply of Climate Services

Poor infrastructure (e.g.,

non-functioning observational networks;

limited Internet bandwidth; lack of

climate modelling capacity; issues of

keeping pace with changing technology)

– International funding for observation

networks, data rescue and data sharing

– Regular NMHS budgets from

governments

– Public–private partnerships

Snow etal. (2016); World Bank

Group (2016); Winrock (2018);

Cullmann etal. (2020); Meque

etal. (2021)

East Africa and the West African Sahel (ENACTS

programme)

Working with NMHS to provide enhanced services by

overcoming the challenges of data quality, availability and

access.

Creating of reliable climate information suitable for national

and local decision-making using station observations and

satellite data to provide greater accuracy in smaller space

and time scales.

Fragmented delivery of Climate Services

– Greater collaboration between the NMHS

and sector-speciﬁc specialists to create a

central database of sector-based climate

services

Winrock (2018); Hansen etal.

(2019a)

Rwanda (RCSA programme)

Improving CS and agricultural risk management at local and

national government levels in the face of a variable and

changing climate.

Mismatch in time scales: short-term

information more desirable (e.g.,

seasonal predictions as opposed to

decadal or end of century projections)

– Co-production of climate service products

Jones etal. (2015); Vincent

etal. (2018); Hansen etal.

(2019a); Carr etal. (2020);

Sultan etal. (2020)

Burkina Faso (BRACED project)

Strengthening technical and communication capacities

of national meteorological services to enable partners

to jointly develop forecasts tailored to support

agro-pastoralists.

Development funding interventions

operate on time scales that inhibit

or restrict effective adaptation and

neglect to build in considerations

for sustainability post the funded

intervention

– Co-production of climate service products

– Endogenously driven climate services

(services that are developed by regional

actors, not by remote, usually developed

nation actors)

Vincent etal. (2018); Vogel

etal. (2019) Vincent etal.

(2020a)

Burkina Faso (BRACED project)

Actors recognised the need to ensure continuation of CS

post-project. Burkina Faso NMHS (ANAM) and National

Council for Emergency Assistance and Rehabilitation

(CONASUR) budgeted for the continued communication of

CS and training of focal weather intermediaries. Local radio

stations agreed to continue transmitting CS.

Use of Climate Services

Insufﬁcient access to usable data,

including station data, and information

suited to the decision context (including

accessibility limitations based on gender

and social inequalities)

– Capacity development initiatives for

Climate Services providers, intermediaries

(including extension agents, NGO workers

and others) and users

– User needs assessments

– Consistent monitoring and evaluation of

Climate Services interventions

Jones etal. (2015); Winrock

(2018); Hansen etal. (2019a);

Hansen etal. (2019c); Mercy

Corps (2019); Nkiaka etal.

(2019); Carr etal. (2020);

Cullmann etal. (2020);

Gumucio etal. (2020); Sultan

etal. (2020)

Figure9.11

Kenya, Ethiopia, Ghana, Niger and Malawi (ALP

Programme)

Co-production of relevant information for decision making

and planning at seasonal time scales. The methods and

media for communication and messages differ between

different users. Strong emphasis on participation by women.

Limited capacity of users to understand

or request appropriate Climate Services

products

– Co-production of climate service products

– Capacity development

Snow etal. (2016); Singh etal.

(2018); Vincent etal. (2018);

Nkiaka etal. (2019); Daniels

etal. (2020)

Cities in Zambia, Namibia, Mozambique, Zimbabwe,

Botswana, Malawi and South Africa (FRACTAL programme)

Repeated interactions between each represented sector

to learn and more completely understand the different

contexts of each represented party and build understanding

through an ethic of collaboration for solving climate-related

problems in each unique city.

Lack of user trust in the information

– Co-production of climate service products

– Combine scientiﬁc and Indigenous

forecasts

– Demonstrate added value of the climate

service

Vincent etal. (2018); Nkiaka

etal. (2019); Vaughan etal.

(2019); Vogel etal. (2019);

Nyadzi etal. (2021)

Tanzania (ENACTS programme)

Co-production to inform malaria decisions systematically

and change relationships, trust, and demand in a manner

that had not been realised through previous singular and

siloed approaches.

Socioeconomic, and institutional

barriers (limited professional mandates,

ﬁnancing limitations, institutional

cooperation)

– Regular NMHS budgets from

governments

– Public–private partnerships

– Supportive institutions, policy frameworks

and individual capacity and agency

Snow etal. (2016); World Bank

Group (2016); Winrock (2018);

Harvey etal. (2019); Vincent

etal. (2020b)

Notes:

(a) Reproduced from Carter etal. (2020) with permission.

1316

Chapter 9 Africa

However, the effectiveness of co-production processes are hindered

by aspects such as inequitable power relationships between different

types of knowledge holders (e.g., scientists and practitioners),

inequitable distribution of funding between developed country and

African partners that favours developed country partners, an inability

to develop sustained trust relationships as a result of short-funding

cycles, a lack of ﬂexibility due to product-focused engagements and the

scalability of co-production to enable widespread reach across Africa

as the process is usually context speciﬁc (high conﬁdence) (Vincent

etal., 2018; Vogel etal., 2019; 2020a).

Despite these challenges, the inclusive nature of co-production has

had a positive inﬂuence on the uptake of CS into decision making

where it has been applied (Table9.4; Figure9.12; Vincent etal., 2018;

Vogel etal., 2019; Carter etal., 2020; Chiputwa etal., 2020) (medium

conﬁdence), through sustained inter/transdisciplinary relationships

and capacity development (Norström etal., 2020), strategic ﬁnancial

investment, fostering of ownership of resulting products and the

combining of scientiﬁc and other knowledge systems (Carter et al.,

2020; Steynor etal., 2020a). There is high conﬁdence that together

with improved institutional capacity building and strategic ﬁnancial

investment, CS can help African stakeholders adapt to projected

climate risks (Figure9.11).

9.4.5.2 Community Perceptions of Climate Variability and

Change

Perceptions of climate variability and change affect whether and how

individuals and institutions act, and thus contribute to the success or

failure of adaptation policies related to weather and climate (Silvestri

etal., 2012; Arbuckle etal., 2015; Simpson etal., 2021a).

A recent Afrobarometer study covering 34 African countries found 67%

of Africans perceive climate conditions for agricultural production to

have worsened over time, and report drought as the main extreme

weather event to have worsened in the past decade (Selormey etal.,

2019). Of these participants, across all socioeconomic strata, 71% of

those who were aware of the concept of climate change agreed that it

needs to be stopped, but only 51% expressed conﬁdence about their

ability to make a difference. East Africans (63%) were almost twice as

likely as north Africans (35%) to report that the weather for growing

crops had worsened. Additionally, people engaged in occupations

related to agriculture (farming, ﬁshing or forestry) were more likely to

report negative weather effects (59%) than those with other livelihoods

(45%) (Selormey etal., 2019). Similar perceptions have been reported

among a diversity of rural communities in many sub-Saharan African

countries (Mahl etal., 2020; Simpson etal., 2021a).

Rural communities, particularly farmers, are the most studied

groups for climate change perception. They perceive the climate

to be changing, most often reporting changes in rainfall variability,

increased dry spells, decreases in rainfall and increased temperatures

or temperature extremes. They perceive these changes to bring a range

of negative socioeconomic and environmental effects (Alemayehu and

Bewket, 2017; Liverpool-Tasie etal., 2020; Simpson etal., 2021a). In

some cases, farmers’ perceptions of changes in weather and climate

frequently match climate records for decreased precipitation totals,

increased drought frequency, shorter rainy season and rainy season

delay, and increased temperatures (Figure9.11; Rurinda etal., 2014;

Boansi etal., 2017; Ayanlade etal., 2018), but not in all cases or not for

all perceived changes, with common discrepancies in perceived lower

rainfall totals (Alemayehu and Bewket, 2017; Ayal and Leal Filho, 2017;

Simpson etal., 2021a).

Farming experience, access to extension services and increasing

age are the most frequently cited factors positively inﬂuencing the

perceptions of climate changes (Alemayehu and Bewket, 2017; Oduniyi

and Tekana, 2019). Personal experience of climate-related changes

and their impacts appears to be an important factor inﬂuencing

perceptions through shaping negative associations, for example,

experience of ﬂash ﬂoods (Elshirbiny and Abrahamse, 2020) or direct

effect on economic activity, indicating that perception is not restricted

to crop farmers (Liverpool-Tasie etal., 2020). However, perceptions

show common misconceptions about the causes of climate change,

which has implications for climate action (Elshirbiny and Abrahamse,

2020), highlighting the importance of climate change literacy.

9.4.5.3 Climate Change Literacy

Understanding the human cause of climate change is a strong

predictor of climate change risk perception (Lee etal., 2015) and a

critical knowledge foundation that can affect the difference between

coping responses and more informed and transformative adaptation

(Figure9.11; Oladipo, 2015; Mutandwa etal., 2019). At a minimum,

climate change literacy includes both having heard of climate change

and understanding it is, at least in part, caused by people (Simpson

etal., 2021a). However, large inequalities in climate change literacy

exist between and within countries and communities across Africa.

The average national climate change literacy rate in Africa is only 39%

(country rates range from 23–66%) (Figure9.11). Of 394 sub-national

regions surveyed by Afrobarometer, 8% (37 regions in 16countries)

have a climate change literacy rate lower than 20%, while only 2%

(8 regions) score higher than 80%, which is common across European

countries (Simpson et al., 2021a). Striking differences exist when

comparing sub-national units within countries. Climate change literacy

rates in Nigeria range from 71% in Kwara to 5% in Kano, and within

Botswana from 69% in Lobatse to only 6% in Kweneng West (Simpson

etal., 2021a). Education is the strongest positive predictor of climate

change literacy, particularly tertiary education, but poverty decreases

climate change literacy and climate change literacy rates average

12.8% lower for women than men (Simpson etal., 2021a).

As the identiﬁed factors driving climate change literacy overlap

with broader developmental challenges on the continent, policies

targeting these factors (e.g., increased education) can potentially yield

co-beneﬁts for both climate change adaptation as well as progress

towards SDGs, particularly education and gender equality (Simpson

etal., 2021a). Progress towards greater climate change literacy affords

a concrete opportunity to mainstream climate change within core

national and sub-national developmental agendas in Africa towards

more CRD pathways. Synergies with CS can also overcome gendered

deﬁcits, for example, although women are generally less climate

change aware and more vulnerable to climate change than men in

1317

Africa Chapter 9

Selected examples of the co-production of climate services and the sectors involved

Agriculture Flood risk

Cities Gender

Health

Disaster Risk

Management Livestock

Energy Transport

Fishing Water

Climate finance

ture

ities

ender

Hea

saster

anagemen

estock

ransp

ater

limate

inance

BURKINAFASO

1 2 3

BOTSWANA

ZIMBABWE

6 9

MOZAMBIQUE

8 9

SOUTH AFRICA

ETHIOPIA

513 17

UGANDA

2 8

21 22 24

ZAMBIA

NAMIBIA

RWANDA

410

KENYA

2513 16 18

20 2119 23 24

CHAD

2SUDAN

SENEGAL

TANZANIA

2421

711 14 1512

MALAWI

6 9 14

Figure9.12 | The inclusive nature of co-production has had a positive inﬂuence on the uptake of climate services into decision making in Africa. Selected

examples of the co-production of climate services and the sectors involved. Icons indicate sectors and numbers show the programmes under which the co-production engagements

occurred. Programmes listed are (1) AMMA-2050: Combining Scenario Games, Participatory Modelling and Theatre Forums to Co-produce Climate Information for Medium-term

Planning, (2,3) BRACED: Sharing Lessons on Promoting Gender Equality through a ‘Writeshop’, (4) RCSA: Bringing Climate Services to People Living in Rwanda’s Rural Areas, (5)

ALP: Participatory Scenario Planning for Local Seasonal Climate Forecasts and Advisories, (6) Climate Risk Narratives: Co-producing Stories of the Future, (7) ENACTS: Developing

Climate Services for Malaria Surveillance and Control in Tanzania, (8) FATHUM: Forecast for Anticipatory Humanitarian Action, (9) FRACTAL: Learning Labs, Dialogues and Embedded

Researchers in Southern African Cities, (10) FONERWA: Climate Risk Screening Tool, (11) MHEWS: Multi-hazard Early Warning System for Coastal Tanzania, (12) Resilient Transport

Strategic Assessment for Dar es Salaam, (13) RRA: Climate Attribution for Extreme Weather Events in Ethiopia and Kenya, (14) UMFULA: Co-producing Climate Information for

Medium-term Planning in the Water-Energy-Food Nexus, (15) IRRP: Building Resilience in Tanzania’s Energy Sector Planning, (16) PRISE: Co-exploring Relevant Evidence for Policy

Change in Kenya, (17) NMA ENACTS: An Example of a Co-produced Climate Service Fit for Purpose, (18) REACH: Improving Water Security for the Poor in Turkana County, Kenya,

(19) DARAJA: Co-designing Weather and Climate Information Services for and with Urban Informal Settlements in Nairobi and Dar es Salaam, (20) ForPAc: Co-producing Approaches

to Forecast-based Early Action for Drought and Floods in Kenya, (21) HIGHWAY: Co-produced Impact-based Early Warnings and Forecasts to Support Fishing Communities on Lake

Victoria, (22) HyCRISTAL: Using Video to Initiate Farmer Dialogue with Local Government in Mukono, Uganda, (23) SCIPEA: Co-produced Seasonal Forecasts for More Effective

Management of Hydropower Supply in Kenya, (24) Weather Wise: Co-producing Weather and Climate Radio Content for Farmers, Fishermen and Pastoralists in East Africa. See

Carter etal. (2020) for details and outcomes of each engagement. Source: Carter etal. (2020).

1318

Chapter 9 Africa

Box9.1 | Vulnerability Synthesis

Vulnerability in Africa is socially, culturally and geographically differentiated among climatic regions, countries and local communities, with

climate change impacting the health, livelihoods and food security of different groups to different extents (Gan etal., 2016; Onyango etal.,

2016a; Gumucio etal., 2020). This synthesis emphasises intersectionality within vulnerable groups as well as their position within dynamic

social and cultural contexts (Wisner, 2016; Kuran etal., 2020), and highlights the differential impacts of climate change and restricted

adaptation options available to vulnerable groups across African countries (see also Cross-Chapter BoxGENDER in Chapter 18).

Vulnerability and exposure to the impacts of climate change are complex and affected by multiple, interacting non-climatic processes,

which together inﬂuence risk, including socioeconomic processes (Lwasa etal., 2018; UNCTAD, 2020), resource access and livelihood

changes (Jayne etal., 2019b) and intersectional vulnerability among social groups (Figure Box9.1.1; Rao etal., 2020). Socioeconomic

processes encompass broader social, economic and governance trends, such as expanded investment in large energy and transportation

infrastructure projects (Adeniran and Daniell, 2020), rising external debt (Edo etal., 2020), changing role of the state in social development

(Wunsch, 2014), environmental management (Ramutsindela and Büscher, 2019) and conﬂict, as well as those emanating from climate

change mitigation and adaptation projects (Beymer-Farris and Bassett, 2012; van Baalen and Mobjörk, 2018; Simpson etal., 2021b).

These macro trends shape both urban and rural livelihoods, including the growing diversiﬁcation of rural livelihoods through engagement

in the informal sector and other non-farm activities, and are mediated by complex and intersecting factors like gender, ethnicity, class,

age, disability and other dimensions of social status that inﬂuence access to resources (Luo etal., 2019). Research increasingly highlights

the intersectionality of multiple dimensions of social identity and status that are associated with greater susceptibility to loss and damage

(Caparoci Nogueira etal., 2018; Li etal., 2018).

Arid and semi-arid countries in the Sahelian belt and the greater Horn of Africa are often identiﬁed as the most vulnerable regions on the

continent (Closset etal., 2017; Serdeczny etal., 2017). Particularly vulnerable groups include pastoralists (Wangui, 2018; Ayanlade and

Ojebisi, 2019), ﬁshing communities (Belhabib etal., 2016; Muringai etal., 2019a), small-scale farmers (Ayanlade etal., 2017; Mogomotsi

etal., 2020; see Section9.8.1) and residents of formal and informal urban settlements (see Section9.9). Research has identiﬁed key

macro drivers, as well as multiple dimensions of social status that mediate differential vulnerability in different African contexts. For

example, the contemporary vulnerability of small-scale rural producers in semi-arid northern Ghana has been shaped by colonial economic

transformations (Ahmed etal., 2016), more recent neoliberal reforms reducing state support (Fieldman, 2011) and the disruption of local

food systems due to increasing grain imports (Nyantakyi-Frimpong and Bezner-Kerr, 2015). Age interacts with other dimensions of social

status, shaping differential vulnerability in several ways. Projected increases in mean temperatures and longer and more intense heat

waves (Figure Box9.1.1) may increase health risks for children and elderly populations by increasing risks associated with heat stress

(Bangira etal., 2015; Cairncross etal., 2018). Temperature extremes are associated with increased risk of mortality in Ghana, Burkina

Faso, Kenya and South Africa, with greatest increases among children and the elderly (Bangira etal., 2015; Amegah etal., 2016; Omonijo,

2017; Wiru etal., 2019; see Section9.10.2.3.1).

Rural African women are often disadvantaged by traditional, patriarchal decision-making processes and lack of access to land—issues

compounded by kinship systems (that, is matrilineal or patrilineal), migrant status, age, type of household, livelihood orientation and

disability in determining their adaptive options (Ahmed et al., 2016; see Section9.8.1; 9.11.1.2; Box9.8). Differential agricultural

productivity between men and women is about 20–30% or more in dryland regions of Ethiopia and Nigeria (Ghanem, 2011) and

challenges women’s ability to adapt to climate change. Limited access to agricultural resources and limited beneﬁts from agricultural

policies, compounded by other social and cultural factors, make women more vulnerable to climatic risks (Shukla etal., 2021). Kinship

systems can contribute to their vulnerability and capacity to adapt. Women in matrilineal systems have greater bargaining power and

have access to more resources than those in patrilineal systems (Chigbu, 2019; Robinson and Gottlieb, 2021; See section 9.8.1; 9.11.1.2).

1319

Africa Chapter 9

Changing Patterns of Resource Access and

Ownership

 Large-scale land acquisitions and transformation

(Hufe and Heuermann 2017) (9.6; 9.8).

 Growing inequality in rural land distribution and

declining land availability within smallholder systems

(Jayne et al. 2019) (9.8).

 Land fragmentation and land use intensification

among smallholder farmers (Cholo et al 2018;

Clay and Zimmerer 2020; Rasmussen et al. 2018)

(9.6; 9.8).

 Fragmentation of dryland landscapes, constricted

livestock mobility, and sedentarization among

pastoralists (Mabhuye 2018; Suleiman and Young

2013) (9.6; 9.8).

Livelihood Diversification and Change

 Growing engagement in rural, peri-urban and urban

informal sector activities (Adom 2014; Allard 2017;

Potts 2008; Chihambakwe et al. 2019; Dolislager et

al. 2021) (9.9)).

 Rural deagrarianization with landless and land poor

entering low return non-farm activities (Asfaw et al.

2017; Bryceson 2019; Headey and Jayne 2014)

(9.8; 9.11).

 Stress-related and opportunistic rural out-migration

and mobility (see Migration CCB) (Kaczan and

Orgill-Meyer, 2020; Tierney et al. 2017; Waha et al.

2017; Serdeczny eta l 2017; Lassailly-Jacob and

Peyraut 2016) (Box 9.8).

 Livelihood diversification among smallholder farmers

and fishing communities (9.8)

 Increasing variability and overall decline in catches

in marine and inland fisheries, eroding rural

diversification options for some (Lammers et al.

2020; Lowe et al. 2019) (9.8)

Human dimensions of climate change vulnerability in Africa

Colonial Legacies and Postcolonial

Development Pathways

 Dependency on commodity exports and

volatility of extractive economies

(UNCTAD 2019).

Unintended consequences of investments in

large-scale energy, water, and infrastructure

projects (Adeniran and Daniell 2020;

Higginbottom et al. 2021).

Rising external debt and debt service costs

(Edo et al. 2020) (9.11)

Rapid urbanization (9.9; Box 9.8).

Governance

Uneven progress toward democratic

decentralization and civil society

development (Dickovick and Wunsch, 2014;

Makara, 2018) (9.4.2).

Securitization of environmental governance

(Ramutsindela and Büscher 2019) (9.4.2).

Civil conflict, inadequate peacebuilding and

conflict resolution structures (Adetula et al.

2016; van Baalen and Mobjörk, 2018;

Box 9.9).

Corruption and ‘illicit’ financial flows

(UNCTAD 2020) (9.4.2)

Adaptation and Mitigation Actions

Top down and exclusionary mitigation

strategies (Beymer-Ferris and Bassett 2012)

 Pathways of urban growth (Lwasa et al.

2018; van der Zwaan et al. 2018) (9.4.2)

Social protection (9.11)

 Unequal access to coping mechanisms

bolstered by locally-driven, inclusive and

gender responsive adaptation (Eriksen et al.

2011; Ng’ang’a and Crane 2020)



Age: Elderly populations and young children are most vulnerable to health consequences of heat

waves, poor air quality, and climate disasters (Cairncross et al. 2018 (Drivdal 2016; Buyana et al.

2019) (Box 9.1). These groups might not get appropriate food, their mobility might be reduced,

education options impaired, and their dependence on others, especially women caregivers may

increase (Popoola, 2021) (Box 9.1; 9.8)

Gender: Women farmers have limited access to state agro-advisory extension services and

financial resources, and experience fewer benefits from technology adoption (Cundill et al. 2021;

Theis et al. 2017) (9.3; 9.8). Discriminatory health policies, poverty, and cultural norms including

employment and household roles increase the vulnerability of women to extreme weather events

and impair their adaptive capacity (Ajibade et al. 2013; Djoudi and Brockhaus 2011;

Frick-Trzebitzky et al. 2017) (9.7; 9.8; 9.10; 9.11).

Ethnicity: Ethnicity may be a factor that limits the range of adaptation options of some groups,

either due to historical marginalization or cultural preference for specific livelihood orientations

(Nielsen and Reenberg 2010; Azong and Kelso 2021; Tesfamariam and Zinyengere 2017).

Physical ability: People with disabilities are more likely to be excluded from provision of

agricultural, health and education services, and livelihood options that could reduce vulnerability

(Lunga et al. 2019; Alexander 2020; Kuper et al. 2016).

Migrant status: Many international migrants in the region experience greater cultural and economic

barriers to more resilient livelihoods (Anderson 2017; Adepoju 2019; Anderson et al. 2017), and

frequently reside in poorly serviced areas that are more exposed to climate hazards (see Migration

CCB; Box 9.8).

Wealth: Poor households are less capable of coping with climate shocks (Drivdal 2016; Buyana et

al. 2019; Grasham et al. 2019) and frequently are more exposed to hazards through inadequate

infrastructure, service provision, and dwelling in high-risk areas (Box 9.8; 9.11).

Examples of intersectional vulnerability:

Age-wealth intersection: many children in poor households in urban informal settlements face

severe health and educational consequences when flooding halts education and produces acute

infectious disease risks (Drivdal 2016).

Age-gender-ethnicity intersection: elder women experienced heightened vulnerability under

patriarchal cultural conditions (Azong and Kelso 2021).

Gender-wealth intersection: women from poor households were denied access to healthcare

unless accompanied by a man willing to donate blood (Ajibade et al. 2013).

Socio-Economic Processes Intersectional and Compounding Vulnerabilities Among Social Groups

Effect of driver on vulnerabilityincreases vulnerabilitydecreases vulnerability

Vulnerability

Exposure

Response

Hazard

Risk

bi-directional uni-directional

aggregate

Ability

Migrant status

Wealth

Ethnicity Gender

Age

Resource Access and Livelihood Changes

Figure Box 9.1.1 |  Factors contributing to the progression of vulnerability to climate change in African contexts considering socioeconomic

processes, resource access, livelihood changes, and intersectional vulnerability among social groups. This ﬁgure reﬂects a synthesis of vulnerability across

sections of this chapter and highlights how the interactions of multiple dimensions of vulnerability compound each other to increase overall vulnerability (Potts, 2008;

Box9.1 (continued)

1320

Chapter 9 Africa

Nielsen and Reenberg, 2010; Akresh etal., 2011; Eriksen etal., 2011; Beymer-Farris and Bassett, 2012; Davis etal., 2012; Adom, 2014; Akello, 2014; Headey and Jayne,

2014; Otzelberger, 2014; Wunsch, 2014; Conteh, 2015; Huntjens and Nachbar, 2015; Spencer, 2015; Adetula etal., 2016; Djoudi etal., 2016; Kuper etal., 2016; Stark

and Landis, 2016; Allard, 2017; Anderson, 2017; Asfaw etal., 2017; Hufe and Heuermann, 2017; Hulme, 2017; Paul and wa Gĩthĩnji, 2017; Rao etal., 2017; Serdeczny

etal., 2017; Tesfamariam and Zinyengere, 2017; Tierney etal., 2017; Waha etal., 2017; Chihambakwe etal., 2018; Cholo etal., 2018; Jenkins etal., 2018; Keahey, 2018;

Lwasa etal., 2018; Makara, 2018; Nyasimi etal., 2018; Petesch etal., 2018; Schuman etal., 2018; Theis etal., 2018; van Baalen and Mobjörk, 2018; van der Zwaan etal.,

2018; Adepoju, 2019; Adzawla etal., 2019b; Bryceson, 2019; Grasham etal., 2019; Jayne etal., 2019a; Lowe etal., 2019; Lunga etal., 2019; OGAR and Bassey, 2019;

Onwutuebe, 2019; Ramutsindela and Büscher, 2019; Sulieman and Young, 2019; Torabi and Noori, 2019; Adeniran and Daniell, 2020; Alexander, 2020; Clay and Zimmerer,

2020; Devonald etal., 2020; Dolislager etal., 2020; Edo etal., 2020; Kaczan and Orgill-Meyer, 2020; Lammers etal., 2020; World Bank, 2020b; Asiama etal., 2021; Azong

and Kelso, 2021; Birgen, 2021; Paalo and Issifu, 2021; Simpson etal., 2021b).

Knowledge gaps on Vulnerability in Africa and Uneven Acces to Resources

The differential impacts of climate change and adaptation options available to vulnerable groups in Africa are a critical knowledge gap.

More research is needed to examine the intersection of different dimensions of social status on climate change vulnerability in Africa

(Thompson-Hall etal., 2016; Oluwatimilehin and Ayanlade, 2021). More analysis of vulnerability based on gender and other social and

cultural factors is needed to fully understand the impacts of climate change, the interaction of divergent adaptive strategies, as well as

the development of targeted adaptation and mitigation strategies, for example, for women in patrilineal kinship systems, people living

with disabilities, youth, girls and the elderly. Finally, there is an urgent need to build capacity among those conducting vulnerability

assessments, so that they are familiar with this intersectionality lens.

Additional information and capacity development through education and early warning systems could enhance vulnerable groups’ ability

to cope and adapt their livelihoods (Jaka and Shava, 2018). However, some groups of people may struggle to translate information into

actual changes (Makate etal., 2019; McOmber etal., 2019). Lack of access to assets and social networks, for example, among older

populations, are critical limitations to locally driven or autonomous adaptation and limit potential beneﬁts from planned adaptation

actions (e.g., adoption of agricultural technologies or effective use of early warning systems).

There is an urgent need for societal and political change to realise potential beneﬁts for these vulnerable groups in the long term (Nyasimi

etal., 2018). There is a need for gender-sensitive climate change policies in many African countries and gender-responsive policies,

implementation plans and budgets for all local-level initiatives (Wrigley-Asante etal., 2019).

Box9.1 (continued)

Africa, they are generally more likely to adopt climate-resilient crops

when they are climate change aware and have exposure to extension

services (Acevedo etal., 2020; Simpson etal., 2021a).

9.5 Observed and Projected Climate Change

This section assesses observed and projected climate change over Africa.

In Working Group I of the IPCC AR6 (WGI), four chapters make regional

assessments of observed and projected climate change (Doblas-Reyes

etal., 2021; Gutiérrez etal., 2021; Ranasinghe etal., 2021; Seneviratne

et al., 2021), which facilitates a more nuanced assessment in this

section of climate and ocean phenomena that impact African systems.

9.5.1 Climate Hazards in Africa

Temperature increases due to human-caused climate change are

detected across Africa and many regions have warmed more rapidly

than the global average (Figure9.13a; Ranasinghe et al., 2021). A

signal of increased annual heatwave frequency has already emerged

from the background natural climate variability over the whole

continent (Figure9.14; Engdaw etal., 2021). However, detection of

statistically signiﬁcant rainfall trends is evident in only a few regions

(Figure9.13b), and in some regions different observed precipitation

datasets disagree on the direction of rainfall trends (Panitz etal., 2013;

Sylla etal., 2013; Contractor etal., 2020). The uncertainty of observed

rainfall trends results from a number of sources, including high

interannual and decadal rainfall variability, different methodologies

used in developing rainfall products, and the lack of and poor quality

of rainfall station data (Figure9.15; Gutiérrez etal., 2021).

With increased GHG emissions, mean temperature is projected to

increase over the whole continent, as are temperature extremes

over most of the continent (Figure9.16a, b). Increased mean annual

rainfall is projected over the eastern Sahel, eastern east Africa and

central Africa (Figures9.14; 9.16c). In contrast, reduced mean annual

rainfall and increased drought (meteorological and agricultural) are

projected over southwestern southern Africa and coastal north Africa,

with drought in part as a result of increasing atmospheric evaporative

demand due to higher temperatures (Figure9.16e; Ukkola etal., 2020;

Ranasinghe etal., 2021; Seneviratne etal., 2021). The frequency and

intensity of heavy precipitation are projected to increase across most of

Africa, except northern and southwestern Africa (Figures9.14; 9.16d).

Most African countries are expected to experience high temperatures

unprecedented in their recent history earlier in this century than generally

wealthier, higher latitude countries (high conﬁdence). As low latitudes

1321

Africa Chapter 9

have lower internal climate variability (e.g. low seasonality), the low-

latitude African countries are projected to be exposed to large increases

in frequency of daily temperature extremes (hotter than 99.9% of their

historical records) earlier in the 21st century compared to generally

wealthier nations at higher latitudes (Harrington et al., 2016; Chen

etal., 2021; Doblas-Reyes etal., 2021; Gutiérrez etal., 2021). Although

higher warming rates are projected over high latitudes during the ﬁrst

half of this century, societies and environments in low-latitude, low-

income countries are projected to become exposed to unprecedented

climates before those in high latitude, developed countries (Frame

etal., 2017; Harrington etal., 2017; Gutiérrez etal., 2021). For example,

beyond 2050, in central Africa and coastal west Africa, 10months of

every year will be hotter than any month in the period 1950–2000

under a high emissions scenario (RCP8.5) (Harrington et al., 2017;

Gutiérrez etal., 2021). Ambitious, near-term mitigation will provide the

largest reductions in exposure to unprecedented high temperatures

for populations in low-latitude regions, such as across tropical Africa

(Harrington etal., 2016; Frame etal., 2017).

9.5.1.1 Station Data Limitations

Sustained station observation networks (Figure9.15) are essential

for the long-term analysis of local and regional climate trends,

including for temperature and rainfall, as well as: the calibration of

satellite-derived climate products; development of gridded climate

datasets using interpolated and blended station–satellite products

that form the baseline from which climate change departures are

measured; development and running of early warning systems;

climate projection and impact studies; and extreme event attribution

studies (Harrison etal., 2019; Otto etal., 2020).

However, production of salient climate information in Africa is

hindered by limited availability of and access to weather and climate

data, especially in central and north Africa (Figure9.15; Coulibaly

etal., 2017; Hansen et al., 2019a). Existing weather infrastructure

remains suboptimal for development of reliable early warning

systems (Africa Adaptation Initiative, 2018; Krell etal., 2021). For

example, it is estimated only 10% of the world’s ground-based

observation networks are in Africa, and that 54% of Africa’s surface

weather stations cannot capture data accurately (Africa Adaptation

Initiative, 2018; World Bank, 2020d). Some programmes are trying to

address this issue, including the trans-African hydro-meteorological

observatory (van de Giesen etal., 2014), the West African Science

Service Centre on Climate Change and Adaptive Land Management

(WASCAL) (Salack etal., 2019), the Southern African Science Service

Centre for Climate Change, Adaptive Land Management (SASSCAL)

(Kaspar etal., 2015) and the AMMA-CATCH National Observation

Service and Critical Zone Exploration Network (Galle etal., 2018).

However, the sustainability of observation networks beyond the

life of these programmes is uncertain as many African National

Meteorological and Hydrology Services experience structural, ﬁnancial

and technical barriers to maintaining these systems (Section9.4.5).

Observed climate trends calculated for 1980–2015

(a) Temperature trend

(b) Precipitation trend

Figure9.13 | Temperature increases due to human-caused climate change are detected across Africa and many regions have warmed more rapidly than the

global average. Mean observed trends in (a) average temperature (°C per decade) and (b) average precipitation in (mm per decade) for 1980–2015. Trends were calculated with

respect to the climatological mean over 1980–2015. The Climate Research Unit Time Series data (CRU TS) are used to compute temperature trends using 2-m temperature and the

Global Precipitation Climatology Centre data (GPCC) precipitation trends. Regions with no cross-hatching indicate statistically signiﬁcant trends over this period and regions in grey

indicate insufﬁcient data. The ﬁgures are derived from Gutiérrez etal. (2021).

1322

Chapter 9 Africa

Summary of confidence in direction of projected change in climate impact drivers in Africa

1 = Contrasted regional signal: drying in western portions and wettening in eastern portions

2 = Likely increase over the Ethiopian Highlands

3 = Medium confidence of decrease in frequency and increase in intensity

4 = Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat

5 = Substantial parts of the ESAF and MDG coasts are projected to prograde if present-day ambient shoreline change rates continue

High confidence of increase

Medium confidence of increase

Low confidence in direction of change

Medium confidence of decrease

High confidence of decrease

– = Not broadly relevant

Already emerged in the historical period

Emerging by 2050 at least in scenarios RCP8.5/SSP5-8.5

Climate impact drivers

Heat

and cold

Snow

and ice

Coastal

and oceanic

Wind Other

Wet

and dry

Mean air temperature

Extreme heat

Cold spell

Frost

Mean precipitation

River flood

Heavy precipitation & pluvial flood

Landslide

Aridity

Hydrological drought

Agricultural & ecological drought

Fire weather

Mean wind speed

Severe wind storm

Tropical cyclone

Sand and dust storm

Snow, glacier and ice sheet

Hail

Relative sea level

Coastal flood

Coastal erosion

Marine heatwave

Ocean acidity

Air pollution weather

Regions

* North Africa is not an

official region of IPCC

R6, but assessment

here is based upon the

frican portions of the

Mediterranean region.

MED*

SAH

WAF

CAF

NEAF

SEAF

WSAF ESAF MDG

Radiation at surface

Atmospheric CO2 at surface

North Eastern Africa (NEAF) –1, 2111 4

South Eastern Africa (SEAF) 1111 3 4

Western Africa (WAF) – –

111

East Southern Africa (ESAF) –

3 4, 5

Madagascar (MDG) –4, 5

North Africa (MED)* –

West Southern Africa (WSAF) – – 4

Central Africa (CAF) – – 4

Sahara (SAH) – – 4

Figure9.14 | Summary of conﬁdence in the direction of projected change in climate impact drivers (CIDs) in Africa. Projected changes represent the aggregate

changes characteristic for mid-century for a range of scenarios, including: medium emission scenarios RCP4.5, SSP3-4.5, Scenario A1B from Special Report on Emissions Scenarios

(SRES), or higher emissions scenarios (e.g., RCP8.5, SSP5-RCP8.5), within each AR6 WGI region (inset map) approximately corresponding to global warming levels between 2°C

and 2.4°C (for CIDs that are independent of sea level rise). CIDs are drivers of impacts that are of climatic origin (that is, physical climate system conditions including means and

extremes) that affect an element of society or ecosystems. The table also includes the assessment of observed or projected time-of-emergence of the CID change signal from the

natural interannual variability if found with at least medium conﬁdence (dots). Emergence of a climate change signal or trend refers to when a change in climate (the ‘signal’)

becomes larger than the amplitude of natural or internal variations (the ‘noise’). The ﬁgure is a modiﬁed version of Table12.3 in Chapter 12 of WGI (Ranasinghe etal., 2021), please

see this chapter for deﬁnitions of the various climate impact drivers and the basis for conﬁdence levels of the assessment. Please note these WGI regions do not directly correspond

to the regionalisation in this chapter nor do we assess climate risks for Madagascar.

9.5.2 North Africa

9.5.2.1 Temperature

9.5.2.1.1 Observations

Mean and seasonal temperatures have increased at twice the global rate

over most regions in north Africa due to human-induced climate change

(Ranasinghe et al., 2021; Figures 9.13a and; 9.14) (high conﬁdence).

Increasing temperature trends have been particularly strong since the

1970s (between 0.2°C per decade and 0.4°C per decade), especially in

the summer (Tanarhte etal., 2012; Donat etal., 2014a; Lelieveld etal.,

2016). Similar warming signals have been observed since the mid-1960s

over the Sahara and the Sahel (Fontaine et al., 2013; Moron etal.,

2016). Trends in mean maximum (TX) and minimum (TN) temperatures

range between +2°C and +3°C per century over north Africa, and the

frequencies of hot days (TX >90th percentile, TX90p) and tropical nights

(TN >20°C), as well as the frequencies of warm days and nights, roughly

follow these mean TX and TN trends (Fontaine etal., 2013; Moron etal.,

2016; Ranasinghe etal., 2021; Seneviratne et al., 2021). Warm spell

duration has increased in many north African countries (Donat etal.,

2014a; Filahi etal., 2016; Lelieveld etal., 2016; Nashwan etal., 2018)

and heatwave magnitude and spatial extent have increased across north

Africa since 1980, with an increase in the number of events since 2000

that is beyond the level of natural climate variability (Russo etal., 2016;

Ceccherini etal., 2017; Engdaw etal., 2021).

1323

Africa Chapter 9

9.5.2.1.2 Projections

At 1.5°C, 2°C and 3°C of global warming above pre-industrial levels,

mean annual temperatures in north Africa are projected to be on

average, 0.9°C, 1.5°C and 2.6°C warmer than the 1994–2005 average,

respectively (Figure 9.16a). Warming is projected to be stronger in

summer than winter (Lelieveld etal., 2016; Dosio, 2017). The number

of hot days is likely to increase by up to 90% by the end of the century

under RCP8.5 (global warming level [GWL] 4.4°C) (Gutiérrez etal.,

2021; Ranasinghe etal., 2021) and hot nights and the duration of

warm spells to increase in the ﬁrst half of the 21st century in both

intermediate and high-emission scenarios (Patricola and Cook, 2010;

Vizy and Cook, 2012; Lelieveld etal., 2016; Dosio, 2017; Filahi etal.,

2017). Heatwaves are projected to become more frequent and intense

even at 1.5°C of global warming (Gutiérrez etal., 2021; Ranasinghe

et al., 2021). Children born in 2020, under a 1.5°C-compatible

scenario will be exposed to 4–6 times more heatwaves in their

lifetimes compared to people born in 1960; this exposure increases to

9–10times more heatwaves for emission reduction pledges, limiting

global warming to 2.4°C (Thiery etal., 2021).

9.5.2.2 Precipitation

9.5.2.2.1 Observations

Mean annual precipitation decreased over most of north Africa

between 1971–2000 (Donat etal., 2014a; Hertig etal., 2014; Nicholson

etal., 2018; Zittis, 2018), with a gradual recovery to normal or wetter

conditions in Algeria and Tunisia since 2000 and over Morocco since

2008 (Nouaceur and Murărescu, 2016). Since the 1960s days with more

than 10 mm of rainfall have decreased and the number of consecutive

dry days have increased in the eastern parts of north Africa, while in the

western parts of north Africa heavy rainfall and ﬂooding has increased

(Donat et al., 2014a). Aridity, the ratio of potential evaporation to

precipitation, has increased over the Mediterranean and north Africa

due to signiﬁcant decreases in precipitation (Greve etal., 2019).

9.5.2.2.2 Projections

Mean annual precipitation is projected to decrease in north Africa at

warming levels of 2°C and higher (high conﬁdence) with the most

pronounced decreases in the northwestern parts (Figures9.13a and;

9.14; Schilling etal., 2012; Filahi etal., 2017; Barcikowska etal., 2018;

Ranasinghe etal., 2021). Meteorological drought over Mediterranean

north Africa in CMIP5 and CMIP6 models are projected to increase

in duration from approximately 2 months during 1950–2014 to

approximately 4months in the period 2050–2100 under RCP8.5 and

Large regions of Africa lack regularly reporting and quality-controlled weather station data

(a) Distribution of weather stations since 1950

Stations that were

still active in 2017

(b) Number of weather stations since 1950

19901980197019601950

2020

20102000

1,800

1,600

1,400

1,200

1,000

Figure9.15 | Large regions of Africa lack regularly reporting and quality-controlled weather station data. This ﬁgure shows stations in Africa with quality-controlled

station data used in developing the Rainfall Estimates on a Gridded Network (REGEN) interpolated rainfall product (Harrison etal., 2019). (a) A spatial representation of stations

across the continent since 1950 shown as black dots and red crosses, where red crosses represent stations that were still active in 2017. (b) The decline in operational stations or

stations with quality-controlled data since circa1998, which is largely a function of declining networks in a subset of countries. Figure is derived from Carter etal. (2020).

1324

Chapter 9 Africa

Projected changes

of climate variables and hazards

(relative to 1995–2014 average)

at 1.5°C, 2°C and 3°C of global warming

above pre-industrial (1850–1900)

16 46 75 90 105

(b)

Change in the number of days

per year above 35°C

13160

+ 1.5°C + 3.0°C+ 2.0°C

-20 10 50 70 80

(c)

Mean annual precipitation change (%)

-30 -10 3004060

-5 25 55 70

(d)

Change in heavy precipitation represented by

annual maximum 5-day precipitation change (%)

-20 10 40

-50 -20 40 70 85

(e)

Change in drought represented by six-month

standardised precipitation index change (%)

-65 -35 10 25 55

-5

1.0 2.0 2.5 3.0

(a)

Mean temperature change (°C)

0 0.5 1.5

0.8 1.4 1.9 2.2 > 2.5

(f)

Mean sea surface temperature change (°C)

0.5 1.1 1.6

Figure9.16 | Projected changes of climate variables and hazards at 1.5°, 2° and 3° of global warming above the pre-industrial period (1850–1900).

1325

Africa Chapter 9

SSP5-85 (Ukkola et al., 2020). Extreme rainfall (monthly maximum

1-day rainfall – RX1day) in the region is projected to decrease (Donat

etal., 2019).

During 1984–2012, north Africa experienced a decreasing dust trend

with north African dust explaining more than 60% of global dust

variations (Shao etal., 2013). Dust loadings and related air pollution

hazards (from ﬁne particles that affect health) are projected to

decrease in many regions of the Sahara as a result of decreased wind

speeds (Evan etal., 2016; Ranasinghe etal., 2021).

9.5.3 West Africa

9.5.3.1 Temperature

9.5.3.1.1 Observations

Observed mean annual and seasonal temperatures have increased

1–3°C since the mid-1970s with the highest increases in the Sahara and

Sahel (Figures9.13a; Cook and Vizy, 2015; Lelieveld etal., 2016; Dosio,

2017; Nikiema etal., 2017; Gutiérrez etal., 2021; Ranasinghe et al.,

2021) and positive trends in mean annual maximum (TX) and minimum

(TN) of 0.16°C and 0.28°C per decade, respectively (Mouhamed etal.,

2013; Moron etal., 2016; Russo etal., 2016; Barry etal., 2018). The

frequency of very hot days (TX>35°C) and tropical nights has increased

by 1–9days and 4–13 nights per decade between 1961–2014 (Moron

et al 2016), and cold nights have become less frequent (Fontaine etal.,

2013; Mouhamed etal., 2013; Barry etal., 2018). In the 21st century,

heatwaves have become hotter, longer and more extended compared

to the last two decades of the 20th century (Mouhamed etal., 2013;

Moron etal., 2016; Russo etal., 2016; Barbier etal., 2018).

9.5.3.1.2 Projections

At 1.5°C, 2°C and 3°C of global warming above pre-industrial levels,

mean annual temperatures in west Africa are projected to be on

average, 0.6°C, 1.1°C and 2.1°C warmer than the 1994–2005 average,

respectively (Figure9.16a). Under mid- and high-emission scenarios

end of century summer temperatures are projected to increase by 2°C

and 5°C, respectively (Sylla etal., 2015a; Russo etal., 2016; Dosio,

2017). The annual number of hot days is projected to increase at all

global warming levels with larger increases at higher warming levels

(Figure9.16b). By 2060 the frequency of hot nights is projected to

be almost double the 1981–2010 average at GWL 2°C (Dosio, 2017;

Bathiany etal., 2018; Gutiérrez etal., 2021; Ranasinghe etal., 2021).

Heatwave frequency and intensity are projected to increase under all

scenarios, but limiting global warming to 1.5°C leads to a decreased

heatwave magnitude (–35%) and frequency (–37%) compared to 2°C

global warming (Dosio, 2017; Weber etal., 2018; Nangombe etal.,

2019). Children born in 2020, under a 1.5°C-compatible scenario will

be exposed to 4–6times more heatwaves in their lifetimes compared

to people born in 1960; this exposure increases to 7–9times more

heatwaves at GWL 2.4°C (Thiery etal., 2021).

The number of dangerous heat days (TX >40.6°C) is projected to

increase from approximately 60 per year in 1985–2005 to approximately

110, 130 and 140 under RCP2.6, RCP4.5 and RCP8.5, respectively, in

the 2060s and to 105, 145 and 196 in the 2090s (Rohat etal., 2019).

Over tropical west Africa, heat-related mortality risk through increased

heat and humidity is 6–9times higher than the 1950–2005 average at

GWL 2°C, 8–15times at GWL 2.65°C and 15–30times at GWL 4.12°C

(Ahmadalipour and Moradkhani, 2018) (Coffel etal., 2018). The number

of potentially lethal heat days per year is projected to increase from <50

during 1995–2005 to 50–150 at GWL 1.6°C, 100–250 at GWL 2.5°C

and 250–350 at GWL 4.4°C, with highest increases in coastal regions

(Mora etal., 2017). Increasing urbanisation concentrates this exposure

in cities, such as Lagos, Niamey, Kano and Dakar (Section9.9.3.1; Coffel

etal., 2018; Rohat etal., 2019).

9.5.3.2 Precipitation

9.5.3.2.1 Observations

Negative trends in rainfall accompanied by increased rainfall variability

were observed between 1960s–1980s over west Africa (Nicholson

et al., 2018; Thomas and Nigam, 2018), caused by a combination

of anthropogenic aerosols and GHGs emitted between the 1950s

and1980s (Booth etal., 2012; Wang etal., 2016; Giannini and Kaplan,

2019; Douville etal., 2021). Declining rainfall trends ended by 1990

due to the growing inﬂuence of GHGs and reduced cooling effect

of aerosol emissions, with a trend to wetter conditions emerging in

the mid-1990s accompanied by more intense, but fewer precipitation

events (Sanogo etal., 2015; Sylla etal., 2016; Kennedy etal., 2017;

Barry etal., 2018; Bichet and Diedhiou, 2018a; 2018b; Thomas and

Nigam, 2018). A shift to a later onset and end of the west African

monsoon is also reported in west Africa and Sahel (low conﬁdence)

(Chen et al., 2021; Ranasinghe et al., 2021). Between 1981–2014

Changes shown here are relative to the 1995–2014 period. Rows are

(a) Mean temperature change (°C);

(b) Change in the number of days per year above 35°C (days);

(d) Heavy precipitation change represented by annual maximum 5-day precipitation (%);

(e) Change in drought represented by the six-month standardised precipitation index (SPI) (%) – negative changes indicate areas where drought frequency, intensity and/or

duration is projected to increase and positive changes show the opposite;

(f) Mean sea surface temperature change (°C). All ﬁgures are derived from the WGI Interactive Atlas and show results from between 26 to 33 CMIP6 (Coupled Model Intercomparison

Project) global climate models depending on the climate variable. CMIP6 models include improved representations of physical, biological, and chemical processes as well as higher

spatial resolutions compared to previous CMIP5 models (Eyring etal., 2021). Robustness of the projected change signal is indicated by hatching – no overlay indicates high model

agreement, where at least 80% of models agree on sign of change; diagonal lines (/) indicate low model agreement, where fewer than 80% of models agree on sign of change.

NOTE: Model agreement is computed at a gridbox level and is not representative of regionally aggregated results over larger regions (Gutiérrez etal., 2021).

1326

Chapter 9 Africa

the Gulf of Guinea and the Sahel have experienced more intense

precipitation events (Panthou etal., 2014; Bichet and Diedhiou, 2018a;

Panthou etal., 2018) and the frequency of mesoscale storms has tripled

(Taylor etal., 2017; Callo-Concha, 2018). Extreme heavy precipitation

indices show increasing trends from 1981–2010 (Barry etal., 2018),

increasing high ﬂow events in large Sahelian rivers as well as small

to mesoscale catchments leading to pluvial and riverine ﬂooding

(Douville et al., 2021). Meteorological, agricultural and hydrological

drought in the region has increased in frequency since the 1950s

(medium conﬁdence) (Seneviratne etal., 2021).

9.5.3.2.1 Projections

West African rainfall projections show a gradient of precipitation decrease

in the west and increase in the east (medium conﬁdence) (Figure9.14;

Dosio etal., 2021; Gutiérrez etal., 2021; Ranasinghe etal., 2021). This

pattern is evident at 1.5°C of global warming and the magnitude of

change increases at higher warming levels (Figure9.16c; Schleussner

etal., 2016b; Kumi and Abiodun, 2018; Sylla etal., 2018). A reduction in

length of the rainy season is projected over the western Sahel through

delayed rainfall onset by 4–6days at global warming levels of 1.5°C

and 2°C (Kumi and Abiodun, 2018; Douville etal., 2021; Gutiérrez etal.,

2021). Although there are uncertainties in rainfall projections over the

Sahel (Klutse etal., 2018; Gutiérrez etal., 2021), CMIP6 models project

monsoon rainfall amounts to increase by approximately 2.9% per

degree of warming (Jin etal., 2020; Wang etal., 2020a), therefore, at

higher levels of warming and towards the end of the century, a wetter

monsoon is projected in the eastern Sahel (medium conﬁdence).

The frequency and intensity of extremely heavy precipitation are projected

to increase under mid- and high-emission scenarios (Figures9.13a; 9.14;

Sylla etal., 2015b; Diallo etal., 2016; Akinsanola and Zhou, 2019; Giorgi

etal., 2019; Dosio etal., 2021; Li etal., 2021; Seneviratne etal., 2021).

However, heavy rainfall statistics from global and regional climate models

may be conservative as very-high-resolution, convection-permitting

climate models simulate more intense rainfall than these models (Stratton

etal., 2018; Berthou etal., 2019; Han etal., 2019; Kendon etal., 2019).

At 2°C global warming, west Africa is projected to experience a drier,

more drought-prone and arid climate, especially in the last decades of

the 21st century (Sylla etal., 2016; Zhao and Dai, 2016; Klutse et al.,

2018). The duration of meteorological drought in the western parts of

West Africa is projected to increase from approximately 2months during

1950–2014 to approximately 4months in the period 2050–2100 under

RCP8.5 and SSP5-8.5 (Ukkola etal., 2020). Increased intensity of heavy

precipitation events combined with increasing drought occurrences will

substantially increase the cumulative hydroclimatic stress on populations

in west Africa during the late 21st century (Giorgi etal., 2019).

9.5.4 Central Africa

9.5.4.1 Temperature

9.5.4.1.1 Observations

Mean annual temperature across central Africa has increased by

0.75°C–1.2°C since 1960 (Aloysius etal., 2016; Gutiérrez etal., 2021).

The number of hot days, heatwaves and heatwave days increased

between 1979–2016 (Hu et al., 2019) and cold extremes have

decreased (Figure9.14; Aguilar etal., 2009; Seneviratne etal., 2021).

Uncertainties associated with the poor ground-based observation

networks in the region and associated observational uncertainties

(Section9.5.1.1) result in an assessment of medium conﬁdence in an

increase in the number of heat extremes over the region.

9.5.4.2 Projections

At 1.5°C, 2°C and 3°C of global warming above pre-industrial levels,

mean annual temperatures in central Africa are projected to be on

average, 0.6°C, 1.1°C and 2.1°C warmer than the 1994–2005 average,

respectively (Figure9.16a). By the end of the century (2070–2099),

warming of 2°C (RCP4.5 ) to 4°C (RCP8.5) is projected over the region

(Aloysius etal., 2016; Fotso-Nguemo etal., 2017; Diedhiou etal., 2018;

Mba etal., 2018; Tamoffo etal., 2019) and the number of days with

maximum temperature exceeding 35°C is projected to increase by

150days or more at GWL 4.4°C (Gutiérrez etal., 2021; Ranasinghe

etal., 2021). According to CMIP6 and CORDEX (Coordinated Regional

Climate Downscaling Experiment) models, the annual average number

of days with maximum temperature exceeding 35°C will increase

between 14–27days at GWL 2°C and 33–59days at GWL 3°C above

the 61–63 days for 1995 –2014 (Gutiérrez et al., 2021; Ranasinghe

et al., 2021) (high conﬁdence). The number of heatwave days is

projected to increase and extreme heatwave events may last longer

than 180days at GWL 4.1°C (Dosio, 2017; Weber etal., 2018; Spinoni

etal., 2019). Children born in 2020, under a 1.5°C-compatible scenario

will be exposed to 6–8 times more heatwaves in their lifetimes

compared to people born in 1960; this exposure increases to 7–9times

more heatwaves at GWL 2.4°C (Thiery etal., 2021). The number of

potentially lethal heat days per year is projected to increase from <50

during 1995–2005 to 50–75 at GWL 1.6°C, 100–150 at GWL 2.5°C

and 200–350 at GWL 4.4°C (Mora etal., 2017).

9.5.4.2 Precipitation

9.5.4.2.1 Observations

The severe lack of station data over the region leads to large uncertainty

in the estimation of observed rainfall trends and low conﬁdence in

changes in extreme rainfall (Figure 9.13b; Creese and Washington,

2018; Gutiérrez etal., 2021; Ranasinghe etal., 2021). There is some

evidence of drying since the mid-20th century through decreased mean

rainfall and increased precipitation deﬁcits (Gutiérrez et al., 2021),

as well as increases in meteorological, agricultural and ecological

drought (medium conﬁdence) (Seneviratne et al., 2021). However,

there is spatial heterogeneity in annual rainfall trends between 1983–

2010 ranging from −10 to +39 mm per year (Maidment etal., 2015),

1327

Africa Chapter 9

with a decline in mean seasonal April–June precipitation of −69 mm

per year in most regions except in the northwest (Zhou etal., 2014;

Hua etal., 2016; Klotter etal., 2018; Hu etal., 2019). Southern and

eastern central Africa were identiﬁed as drought hotspots between

1991–2010 (Spinoni etal., 2014).

9.5.4.2.2 Projections

Under low emission scenarios and at GWL 1.5°C and GWL 2°C there

is low conﬁdence in projected mean rainfall change over the region

(Figure9.16c). At GWL 3°C and GWL 4.4°C, an increased mean annual

rainfall of 10–25% is projected by regional climate models (Coppola

etal., 2014; Pinto etal., 2015) and the intensity of extreme precipitation

will increase (high conﬁdence) (Figure9.16c, d; Sylla etal., 2015a;

Diallo etal., 2016; Dosio etal., 2019; Gutiérrez etal., 2021; Ranasinghe

etal., 2021; Seneviratne etal., 2021). This is projected to increase the

likelihood of widespread ﬂood occurrences before, during and after the

mature monsoon season (Figure9.14).

Convection-permitting simulations (4.5 km spatial resolution) simulate

increased dry spell length not apparent at coarser resolutions, suggesting

drying in addition to more intense extreme rainfall (Stratton et al.,

2018). Although reduced drought frequency is indicated in Figure9.16e,

the SPI metric does not account for the effect of increased temperature

on drought (increased moisture deﬁcit), and metrics that account for

this indicate slightly increased drought frequency or no change (Spinoni

etal., 2020). Therefore, there is low conﬁdence in projected changes of

drought frequency over the region (Figure9.14).

9.5.5 East Africa

9.5.5.1 Temperature

9.5.5.1.1 Observations

Mean temperatures over the region have increased by 0.7°C–1°C

from 1973 to 2013, depending on the season (Ayugi and Tan, 2018;

Camberlin, 2018). Increases in TX and TN are evident across the region

accompanied by signiﬁcantly increasing trends of warm nights, warm

days and warm spells (Russo etal., 2016; Gebrechorkos etal., 2019;

Nashwan and Shahid, 2019). The greatest increases are found in

northern and central regions.

9.5.5.1.2 Projections

At 1.5°C, 2°C and 3°C of global warming above pre-industrial levels,

mean annual temperatures in east Africa are projected to be on

average, 0.6°C, 1.1°C and 2.1°C warmer than the 1994–2005 average,

respectively (Figure9.16a). Highest increases are projected over the

northern and central parts of the region and the lowest increase

over the coastal regions (Otieno and Anyah, 2013; Dosio, 2017). The

magnitude and frequency of hot days are projected to increase from

GWL 2°C and above with larger increases at higher GWLs (Figure9.16a,

b; Dosio, 2017; Bathiany etal., 2018; Dosio etal., 2018; Kharin etal.,

2018). At GWL 4.6°C a number of east African cities are projected to

have an up to 2000-fold increase in exposure to dangerous heat (days

>40.6 °C) compared to 1985–2005 including Blantyre-Limbe, Lusaka

and Kampala (Mora etal., 2017; Rohat etal., 2019). Children born in

2020, under a 1.5°C-compatible scenario will be exposed to 3–5times

more heatwaves in their lifetimes compared to people born in 1960;

this exposure increases to 4–9times more heatwaves at GWL 2.4°C

(Thiery etal., 2021). The number of potentially lethal heat days per

year is projected to increase from <50 during 1995–2005 to <50 at

GWL 1.6°C, 50–120 at GWL 2.5°C and 150–350 at GWL 4.4°C with

largest increases at the coast (Mora etal., 2017), highlighting the new

emergence of dangerous heat conditions in these areas.

9.5.5.2 Precipitation

9.5.5.2.1 Observations

Over equatorial east Africa the short rains (October–November–

December) have shown a long-term wetting trend from the 1960s until

present (Manatsa and Behera, 2013; Nicholson, 2015; 2017), which is

linked with western Indian Ocean warming and a steady intensiﬁcation

of Indian Ocean Walker Cell (Liebmann etal., 2014; Nicholson, 2015).

In contrast, the long rainfall season (March–April–May) has experienced

a long-term drying trend between 1986 and 2007, with rainfall declines

in each of these months and a shortening of the wet season (Rowell etal.,

2015; Wainwright et al., 2019). Unlike previous decades, since around

2000, the long rains have exhibited a signiﬁcant relationship with the El

Niño-Southern Oscillation (ENSO) (Park etal., 2020), as multiple droughts

have occurred during recent La Niña events and when the western to

central Paciﬁc sea surface temperature gradient was La Niña-like (Funk

etal., 2015; Funk etal., 2018a). Wetter-than-average rainfall years within

this long-term drying trend are often associated with a stronger amplitude

of the Madden–Julian Oscillation (Vellinga and Milton, 2018).

In the northern, summer rainfall region (June–September), a decline

in rainfall occurred in the 1960s and rainfall has remained relatively

low, while interannual variability has increased since the late 1980s

(Nicholson, 2017); the cause of this drying trend is uncertain.

Since 2005, drought frequency has doubled from once every 6 to

once every 3 years and has become more severe during the long

and summer rainfall seasons than during the short rainfall season

(Ayana etal., 2016; Gebremeskel Haile etal., 2019). Several prolonged

droughts have occurred predominantly within the arid and semi-arid

parts of the region over the past three decades (Nicholson, 2017).

9.5.5.2.2 Projections

Higher mean annual rainfall, particularly in the eastern parts of east

Africa are projected at GWL 1.5°C and 2°C by 25 CORDEX models

(Nikulin et al., 2018; Osima et al., 2018). The additional 0.5°C of

warming from 1.5°C increases average dry spell duration by between

two and four days, except over southern Somalia where this is reduced

by between 2–3 days (Hoegh-Guldberg et al., 2018; Nikulin et al.,

2018; Osima etal., 2018; Weber etal., 2018).

During the short rainy season, a longer rainfall season (Gudoshava

et al., 2020) and increased rainfall of over 100 mm on average is

1328

Chapter 9 Africa

projected over the eastern Horn of Africa and regions of high/complex

topography at GWL 4.5°C (Dunning etal., 2018; Endris etal., 2019;

Ogega etal., 2020).

During the long rainy season, there is low conﬁdence in projected

mean rainfall change (Gutiérrez etal., 2021). Although some studies

report projected increased end of century rainfall (Otieno and Anyah,

2013; Kent etal., 2015), the mechanisms responsible for this are not

well-understood and a recent regional model study has detected no

signiﬁcant change (Cook etal., 2020b). Projected wetting is opposite

to the observed drying trends, giving rise to the ‘east African rainfall

paradox’ (Rowell etal., 2015; Wainwright etal., 2019). In other parts

of east Africa, no signiﬁcant trend is evident (Ogega et al., 2020),

agreement on the sign of change is low, and in some regions, CMIP5

and CORDEX data show opposite signs of change (Lyon etal., 2017;

Lyon and Vigaud, 2017; Osima etal., 2018; Kendon etal., 2019; Ogega

etal., 2020).

Heavy rainfall events are projected to increase over the region at

global warming of 2°C and higher (high conﬁdence) (Nikulin etal.,

2018; Finney etal., 2020; Ogega etal., 2020; Li etal., 2021). Drought

frequency, duration and intensity are projected to increase in Sudan,

South Sudan, Somalia and Tanzania but decrease or not change over

Kenya, Uganda and the Ethiopian Highlands (Liu etal., 2018c; Nguvava

etal., 2019; Haile etal., 2020; Spinoni etal., 2020).

9.5.6 Southern Africa

9.5.6.1 Temperature

9.5.6.1.1 Observations

Mean annual temperatures over the region increased by between

1.04°C and 1.44°C over the period 1961–2015 depending on the

observational dataset (Gutiérrez et al., 2021) and, in northern

Botswana and Zimbabwe, they have increased by 1.6°C–1.8°C

between 1961–2010 (Engelbrecht et al 2015). The annual number of

hot days have increased in southern Africa over the last four decades

(Ceccherini etal., 2017; Kruger and Nxumalo, 2017a; 2017b) and there

is increasing evidence of increased heat stress impacting agriculture

and human health (Section9.10.2). The occurrence of cold extremes,

including frost days, have decreased (Figure9.14; Kruger and Nxumalo,

2017b).

9.5.6.1.2 Projections

At 1.5°C, 2°C and 3°C of global warming above pre-industrial levels,

mean annual temperatures in southern Africa are projected to be

on average, 1.2°C, 2.3°C and 3.3°C warmer than the 1994–2005

average respectively (Figure9.16a). The annual number of heatwaves

is projected to increase by between 2–4 (GWL 1.5°C), 4–8 (GWL 2°C)

and 8–12 (GWL 3°C) and hot and very hot days are virtually certain to

increase under 1.5°C and 2°C of global warming (Engelbrecht etal.,

2015; Russo etal., 2016; Dosio, 2017; Weber etal., 2018; Seneviratne

etal., 2021). Cold days and cold extremes are projected to decrease

under all emission scenarios with the strongest decreases associated

with low mitigation (Iyakaremye etal., 2021). Children born in 2020,

under a 1.5°C-compatible scenario will be exposed to 3–4 times

more heatwaves in their lifetimes compared to people born in 1960,

although in Angola this is 7–8times; at GWL 2.4°C this exposure

increases to 5–9times more heatwaves (>10times in Angola) (Thiery

etal., 2021).

9.5.6.2 Precipitation

9.5.6.2.1 Observations

Mean annual rainfall increased over parts of Namibia, Botswana and

southern Angola during 1980–2015 by between 128 and 256 mm

(Figure9.13b). Since the 1960s, decreasing precipitation trends have

been detected over the South African winter rainfall region (high

conﬁdence) and the far eastern parts of South Africa (low conﬁdence)

(Engelbrecht et al., 2009; Kruger and Nxumalo, 2017b; Burls etal.,

2019; Lakhraj-Govender and Grab, 2019; Gutiérrez et al., 2021;

Ranasinghe etal., 2021). The frequency of dry spells and agricultural

drought in the region has increased over the period 1961–2016 (Yuan

etal., 2018; Seneviratne etal., 2021), the frequency of meteorological

drought increased by between 2.5–3 events per decade since 1961

(Spinoni et al 2019) and the probability of the multi-year drought over

the southwestern cape of South Africa increased by a factor of three

(95% conﬁdence interval 1.5–6) in response to global warming (Otto

etal., 2018). The number and intensity of extreme precipitation events

have increased over the last century (Kruger and Nxumalo, 2017b;

Ranasinghe etal., 2021; Sun et al., 2021), and in the Karoo region

of southern South Africa, long-term station data show an increasing

trend in annual rainfall of greater than 5 mm per decade over the

period 1921–2015 (Kruger and Nxumalo, 2017b).

9.5.6.2.2 Projections

Mean annual rainfall in the summer rainfall region is projected to

decrease by 10–20%, accompanied by an increase in the number of

consecutive dry days during the rainy season under RCP8.5 (Kusangaya

et al., 2014; Engelbrecht et al., 2015; Lazenby et al., 2018; Maúre

etal., 2018; Spinoni etal., 2019). The western parts of the region are

projected to become drier, with increasing drought frequency, intensity

and duration likely under RCP8.5 (high conﬁdence) (Figures9.16c, e;

9.14; Engelbrecht etal., 2015; Liu etal., 2018b; 2018c; Ukkola etal.,

2020), including multi-year droughts (Zhao and Dai, 2016; Dosio,

2017).

Dryness in the summer rainfall region is expected to increase at 1.5°C

and higher levels of global warming (Hoegh-Guldberg etal., 2018) and

together with higher temperatures will enhance evaporation from the

region’s mega-dams and reduce soil-moisture content (Section9.7.1;

Engelbrecht etal., 2015). Increases in drought frequency and duration

are projected over large parts of southern Africa at GWL 1.5°C (Liu

et al., 2018b; 2018c; Seneviratne et al., 2021) and unprecedented

extreme droughts (compared to the 1981–2010 period) emerge at

GWL 2°C (Spinoni et al., 2021). Meteorological drought duration is

projected to increase from approximately 2months during 1950–2014

to approximately 4months in the mid-to-late-21st century future under

RCP8.5 (Ukkola etal., 2020). Heavy precipitation in the southwestern

1329

Africa Chapter 9

region is projected to decrease (Donat etal., 2019) and increase in the

eastern parts of southern Africa at all warming levels (Li etal., 2021;

Seneviratne etal., 2021).

9.5.7 Tropical Cyclones

There is limited evidence of an increased frequency of Category 5

tropical cyclones in the southwestern Indian Ocean (Fitchett etal., 2016;

Ranasinghe etal., 2021; Seneviratne etal., 2021) and more frequent

landfall of tropical cyclones over central to northern Mozambique

(Malherbe et al., 2013; Muthige et al., 2018). There is a projected

decrease in the number of tropical cyclones making landfall in the

region at 1°C, 2°C and 3°C of global warming, however, they are

projected to become more intense with higher wind speeds so when

they do make landfall the impacts are expected to be high (medium

conﬁdence) (Malherbe etal., 2013; Muthige etal., 2018; Ranasinghe

etal., 2021).

9.5.8 Glaciers

Total glacial area on Mount Kenya decreased by 121×103 m2 (44%)

during 2004–2016 (Prinz etal., 2016), Kilimanjaro from 4.8 km2 in 1984

to 1.7 km2 in 2011 (Cullen etal., 2013) and in the Rwenzori Mountains

from ~2 km2 in 1987 to ~1 km2 in 2003 (Taylor etal., 2006). Declining

glacial areas in east Africa are linked to rising air temperatures (Taylor

etal., 2006; Hastenrath, 2010; Veettil and Kamp, 2019), and in the

case of Kilimanjaro and Mount Kenya, declining precipitation and

atmospheric moisture (Mölg etal., 2009a; 2009b; Prinz etal., 2016;

Veettil and Kamp, 2019).

Glacial ice cover is projected to disappear before 2030 on the Rwenzori

Mountains (Taylor etal., 2006) and Mount Kenya (Prinz etal., 2018)

and by 2040 on Kilimanjaro (Cullen etal., 2013). The loss of glaciers is

expected to result in a loss in tourism revenues, especially in mountain

tourism (Wang and Zhou, 2019).

9.5.9 Teleconnections and Large-Scale Drivers of African

Climate Variability

The ENSO, Indian Ocean Dipole (IOD) and Southern Annular Mode

(SAM) are the primary large-scale drivers of African seasonal and

interannual climate variability. The diurnal temperature range tends to

be greater during La Niña than El Niño in northeastern Africa (Hurrell

etal., 2003; Donat etal., 2014a), and in southern Africa, the El Niño

warming effect has been stronger for more recent times (1979–2016)

compared to earlier period (1940–1978) (Lakhraj-Govender and Grab,

2019). In east Africa, ENSO and IOD exert an interannual control

on particularly October–November–December (short rains) and

June–July–August–September seasons. In southern Africa, El Niño is

associated with negative rainfall and positive temperature anomalies

with the opposite true for La Niña. The SAM exerts control on rainfall

in the southwestern parts of the region and a positive SAM mode is

often associated with lower seasonal rainfall in the region (Reason and

Rouault, 2005). The SAM shows a systematic positive trend over the

last ﬁve decades (Niang etal., 2014).

There is no clear indication that climate change will impact the

frequencies of ENSO and IOD (Stevenson etal., 2012; Endris et al.,

2019), although there is some indication that extreme ENSO events

and extreme phases of the IOD, particularly the positive phase, may

become more frequent with implications for extreme events associated

with these features, such as drought (Collins etal., 2019; Cai et al.,

2021; Seneviratne et al., 2021). Under high-emission scenarios, a

positive trend in SAM is projected to continue through the 21st century,

however, under low emission scenarios, this trend is projected to be

weak or even negative given the potential for ozone hole recovery

(Arblaster etal., 2011).

9.5.10 African Marine Heatwaves

Marine heatwaves are periods of extreme warm sea surface

temperature that persist for days to months and can extend up to

thousands of kilometres (Hobday etal., 2016; Scannell etal., 2016),

negatively impacting marine ecosystems (Section9.6.1.4).

The number of marine heatwaves doubled in mediterranean north

Africa and along the Somalian and southern African coastlines from

1982–2016 (Frölicher et al., 2018; Oliver et al., 2018; Laufkötter

et al., 2020), very likely as a result of human-caused climate

change (Seneviratne et al., 2021). Marine heatwave intensity has

increased along the southern African coastline (Oliver etal., 2018).

In the ecologically sensitive region west of southern Madagascar, the

longest and most intense marine heatwave in the past 35years was

recorded during the austral summer of 2017 in the region, it lasted

48days and reached a maximum intensity of 3.44°C above the 35-

year average (Mawren etal., 2021). Satellite-derived measurements

of coastal marine heatwaves may under-report their intensity as

measured against coastal in situ measurements (Schlegel et al.,

2017).

Sea surface temperatures around Africa are projected to increase by

0.5°C–1.3°C for 1.5°C global warming and increase by 1.3°C–2.0°C

for 3°C global warming (Figure9.16 f). Globally, 87% of observed

marine heatwaves have been attributed to human-caused global

warming, and at 2°C of global warming, nearly all marine heatwaves

would be attributable to heating of the climate caused by human

activities (Frölicher etal., 2018; Laufkötter etal., 2020). Increases in

frequency, intensity, spatial extent and duration of marine heatwaves

are projected for all coastal zones of Africa. At 1°C and 3.5°C of

global warming, the probability of marine heatwave days is between

4–15times and 30–60 times higher compared to the pre-industrial

(1861–1880) 99th percentile probability, with highest increases over

equatorial and sub-tropical coastal regions (Figure9.16; Frölicher etal.,

2018). These events are expected to overwhelm the ability of marine

organisms and ecosystems to adapt to these changes (Section9.6.1;

Frölicher etal., 2018). Reducing emissions and limiting warming to

lower levels reduces risk to these systems (high conﬁdence) (Hoegh-

Guldberg etal., 2018).

1330

Chapter 9 Africa

Box9.2 | Indigenous knowledge and local knowledge

This box aims to map the diversity of Indigenous Knowledge and local knowledge systems in Africa and highlights the potential of

this knowledge to enable sustainability and effective climate adaptation. This box builds on the framing of the IPCC system for which

‘indigenous knowledge (IK) refers to the understandings, skills and philosophies developed by societies with long histories of interaction

with their natural surroundings’ (IPCC, 2019b), while ‘local knowledge (LK) refers to the understandings and skills developed by individuals

and populations, speciﬁc to the place where they live’ (Cross-Chapter BoxINDIG in Chapter 18; IPCC, 2019b).

Early warning systems and indicators of climate variability

In most African Indigenous agrarian systems, local communities integrate IK to anticipate or respond to climate variability (Mafongoya

etal., 2017). This holds potential for a more holistic response to climate change, as Indigenous Knowledge and local knowledge (IKLK)

approaches seek solutions that increase resilience to a wide range of shocks and community stresses (IPCC, 2019b). In Africa, IKLK are

exceptionally rich in ecosystem-speciﬁc knowledge, with the potential to enhance the management of natural hazards and climate

variability (high conﬁdence), but there is uncertainty about IKLK for adaptation under future climate conditions.

Common indicators for the quality of the rain season for local communities in Africa include ﬂower and fruit production of local trees

(Nkomwa etal., 2014; Jiri etal., 2015; Kagunyu etal., 2016), insect, bird and animal behaviour and occurrence (Jiri etal., 2016; Mwaniki

and Stevenson, 2017; Ebhuoma, 2020) and dry season temperatures (Kolawole etal., 2016; Okonya etal., 2017). Fulani herders in

west Africa believe that when ‘nests hang high on trees, then rains will be heavy; when nests hang low, rains will be scarce’ (Roncoli

etal., 2002). In South Africa, LK on weather forecasting is based on the hatching of insects, locust swarm movements and the arrival

of migratory birds, which has enabled farmers to make adjustments to cropping practices (Muyambo etal., 2017; Tume etal., 2019).

Most of these IK indicators apply to speciﬁc communities, and are used for short-term forecasting (e.g., event-speciﬁc predictions, such

as a violent storm, and onset rain predictions) (Zuma-Netshiukhwi etal., 2013; Mutula etal., 2014). There is evidence of communities

that rely heavily on IKLK indicators to forecast seasonal variability across the continent (Kagunyu etal., 2016; Mwaniki and Stevenson,

2017; Tume etal., 2019). However, their accuracy is debatable, due to age-old knowledge losing accuracy because of recent changes

in weather conditions (Shaffer, 2014; Adjei and Kyerematen, 2018). There are also some limitations in the transferability of IK across

geographical scales, as its understanding is framed by traditional beliefs and cultural practices, and historical and social conditions of

each community, which vary signiﬁcantly across communities. This has direct implications for the adoption of IKLK in national policy and

planned adaptation by governments. However, in some parts of Africa, evidence of the integration of IKLK and scientiﬁc-based weather

forecasting is increasing (Jiri etal., 2016; Mapfumo etal., 2017; Williams etal., 2020).

Indigenous Knowledge and Local Knowledge and climate adaptation

Communities across Africa have long histories of using IKLK to cope with climate variability, reduce vulnerability and improve the capacity

to cope with climate variability (Iloka Nnamdi, 2016; Mapfumo etal., 2017). The adaptation is mostly incremental, such as customary

rainwater harvesting practices and planting ahead of rains (Ajibade and Eche, 2017; Makate, 2019), which are used to address the

late-onset rains and rainfall variability. Although IKLK adaptation practices implemented by African communities are incremental, such

practices record higher evidence of climate risk reduction compared to practices inﬂuenced by other knowledge types (Williams etal.,

2020). African communities have used IKLK to cope, adapt to and manage climate hazards, mainly ﬂoods, wildﬁres, rainfall variability and

droughts (see Box Table9.2.1; IPCC, 2018b; IPCC, 2019b).

TableBox9.2.1 | Selected studies where Indigenous knowledge and local knowledge have been used to cope with climate variability and climate change impacts in

Africa.

Climate

hazard Adaptation/coping strategy Indigenous group, community,

country Evidence

Floods

Use IK to predict ﬂoods (village

elders acted as meteorologists) and use LK to prepare

coping mechanisms (social capital); place valuable goods

on higher ground, raise the ﬂoor level, leave the ﬁelds

uncultivated when facing ﬂood/drought, Indigenous

earthen walls used to protect homesteads from ﬂooding,

planting of culturally ﬂood-immunising Indigenous plants

Coastal communities in Nigeria; Oshiwambo

communities in the northern region of

Namibia; Matabeleland and Mashonaland

provinces in Zimbabwe; communities in

Nyamwamba watershed, Uganda; subsistent

farmers in Mount Oku and Mbaw, Cameroon;

Akobo in South Sudan

Fabiyi and Oloukoi (2013); Hooli (2016);

Lunga and Musarurwa (2016); Bwambale

etal. (2018); Tume etal. (2019)

1331

Africa Chapter 9

Climate

hazard Adaptation/coping strategy Indigenous group, community,

country Evidence

Wildﬁres Early burning to prevent the intensity of the late-season

ﬁres

Smallholders in Mutoko, Zimbabwe; Khwe and

Mbukushu communities in Namibia Mugambiwa (2018); Humphrey etal. (2021)

Rainfall

variability

Change crop type (from maize to traditional millet and

sorghum); no weeding; forecasting, rainwater harvesting;

women perform rainmaking rituals, seed dressing and crop

maintenance as adaptation measures; mulching

Communities in Accra, Ghana; small-scale

farmers in Ngamiland in Botswana; Malawi;

Zimbabwe; women in Dikgale, South Africa,

agro-pastoral smallholders in Ntungamo,

Kamuli and Sembabule in Uganda

Codjoe etal. (2014); Nkomwa etal. (2014);

Lunga and Musarurwa (2016); Rankoana

(2016b); Mugambiwa (2018); Mﬁtumukiza

etal. (2020); Mogomotsi etal. (2020)

Droughts

Traditional drying of food for preservation (to consume

during short-term droughts); harvesting wild fruits and

vegetables; herd splitting by pastorals

Communities in Accra, Ghana; Malawi;

South Africa, Uganda; smallholder farmers

in Mutoko, Zimbabwe; agro-pastoralists in

Makueni, Kenya; pastoralists in South Omo,

Ethiopia

Egeru (2012); Gebresenbet and Kefale

(2012); Codjoe etal. (2014); Kamwendo and

Kamwendo (2014); Okoye and Oni (2017);

Mugambiwa (2018)

Drought-related

water scarcity

Traditional rainwater harvesting to supplement both

irrigation and domestic water; Indigenous water bottle

technology for irrigation

Smallholder farmers in Beaufort, South Africa Ncube (2018)

IKLK and adaptation/coping strategies in Table Box9.2.1 are supportive measures that communities cannot solely rely upon, but which

can be used to complement other adaptation options to increase community resilience.

African Indigenous language and climate change adaptation

The diversity of African languages is crucial for climate adaptation. Africa has over 30% of the world’s Indigenous languages (Seti etal.,

2016), which are exceptionally rich in ecosystem-speciﬁc knowledge on biodiversity, soil systems and water (Oyero, 2007; Mugambiwa,

2018). Taking into consideration the low level of literacy in Africa, especially among women and girls, Indigenous languages hold great

potential for more effective climate change communication and services that enable climate adaptation (Brooks etal., 2005; Ologeh

etal., 2018; IPCC, 2019b). African traditional beliefs and cultural practices place great value on the natural environment, especially land

as the dwelling place of the ancestors and source of livelihoods (Tarusarira, 2017; see Section9.12).

Limitations of African Indigenous Knowledge and Local Knowledge in climate adaptation

Studies on IKLK and climate change adaptation conducted in various African countries and across ecosystems indicate that Indigenous

environmental knowledge is negatively affected by several factors. Local farmers who depend on this knowledge system for their

livelihoods hold the view that African governments do not support and promote it in policy development. Most government agricultural

extension workers still consider IK to be unscientiﬁc and unreliable (Seaman etal., 2014; Mafongoya etal., 2017). At the national level,

there is a lack of recognition and inclusion of IKLK in adaptation planning by African governments, partly because most of the IK and LK

in African local communities remains undocumented, but also because IKLK are inadequately captured in the literature (Ford etal., 2016;

IPCC, 2019b). This knowledge is predominantly preserved in the memories of the elderly and is handed down orally or by demonstration

from generation to generation. It gradually disappears due to memory gaps, and when those holding the knowledge die or refuse to pass

it to another generation, the knowledge becomes extinct (Rankoana, 2016a). The way in which IK is transmitted, accessed and shared in

most African societies is not smooth (IIED, 2015). IK is also threatened by urbanisation, which attracts rural migrants to urban areas where

IKLK use may be more limited (Fernández-Llamazares etal., 2015). Further, most African societies that use IK were once colonised,

whereby the African Indigenous ways of knowing were devalued and marginalised (Bolden etal., 2018). There are concerns about the

effectiveness of both IK indicators and related adaptation responses by communities in predicting and adapting to weather events under

future climate conditions (Speranza etal., 2009; Shaffer, 2014; Hooli, 2016).

Box9.2 (continued)Box9.2 (continued)

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Chapter 9 Africa

9.6 Ecosystems

9.6.1 Observed Impacts of Climate Change on African

Biodiversity and Ecosystem Services

9.6.1.1 Terrestrial Ecosystems

The overall continental trend is woody plant expansion, particularly

in grasslands and savannas, with woody plant cover increasing at

a rate of 2.4% per decade (see Figure9.17; Stevens etal., 2017;

Axelsson and Hanan, 2018). There is also increased grass cover in

arid regions in southwestern Africa (Masubelele etal., 2014). There

is high agreement that this is attributable to increased CO2, warmer

and wetter climates, declines in burned area and release from

herbivore browsing pressure, but the relative importance of these

interacting drivers remains uncertain (O’Connor etal., 2014; Stevens

etal., 2016; García Criado etal., 2020). Woody encroachment is the

dominant trend in the western and central Sahel, occurring over

24% of the region, driven primarily by shifts in rainfall timing and

recovery from drought (Anchang etal., 2019; Brandt etal., 2019).

Remote sensing studies demonstrate greening in southern Africa

and forest expansion into water-limited savannas in central and

west Africa (Baccini etal., 2017; Aleman et al., 2018; Piao etal.,

2020), with increases in precipitation and atmospheric CO2 the

probable determinants of change (Venter etal., 2018; Brandt etal.,

2019; Zhang etal., 2019). These trends of greening and woody plant

expansion stand in contrast to the desertiﬁcation and contraction

of vegetated areas highlighted in AR5 (Niang etal., 2014), but are

based on multiple studies and longer time series of observations.

Reported cases of desertiﬁcation and vegetation loss, for example,

in the Sahel, appear transitory and localised rather than widespread

and permanent (Dardel etal., 2014; Pandit etal., 2018; Sterk and

Stoorvogel, 2020).

Shifts in demography, geographic ranges, and abundance of plants

and animals consistent with expected impacts of climate change are

evident across Africa. These include uphill contractions of elevational

range limits of birds (Neate-Clegg et al., 2021), changes in species

distributions previously reported in AR5 (Niang etal., 2014) and the

death of many of the oldest and largest African baobabs (Patrut etal.,

2018). An increase in frequency and intensity of hot, dry weather

after wildﬁres has led to a long-term decline in plant biodiversity in

Fynbos since the 1960s (Slingsby etal., 2017). Increasing temperatures

may have contributed to the declining abundance and range size of

South African birds (Milne etal., 2015), including Cape Rockjumper

(Chaetops frenatus) and protea canary (Serinus leucopterus), from

increased risk of reproductive failure (Lee and Barnard, 2016; Oswald

etal., 2020). For hot and dry regions (e.g., Kalahari), there is strong

evidence that increased temperatures are having chronic sublethal

impacts, including reduced foraging efﬁciency and loss of body mass

(du Plessis etal., 2012; Conradie et al., 2019), and are approaching

species physiological limits, with heat extremes driving mass mortality

events in birds and bats (McKechnie etal., 2021). Vegetation change

linked to climate change and increasing atmospheric CO2 has had an

indirect impact on animals. Increased woody cover has decreased the

occurrence of bird, reptile and mammal species that require grassy

habitats (Péron and Altwegg, 2015; McCleery etal., 2018). Decreased

fruit production linked to rising temperatures has decreased the body

condition of fruit-dependent forest elephants by 11% from 2008–2018

(Bush etal., 2020).

Indigenous earth wall

FigureBox9.2.1 |  Indigenous earth walls (hayit) built by Indigenous people in Akobo, Jonglei Region, South Sudan, to protect their houses and

infrastructure from the worst ﬂood in 25years that occurred in 2019. The wall is 1–2 m high. Photo credit: Laurent-Charles Tremblay-Levesque.

Box9.2 (continued)

1333

Africa Chapter 9

There is high agreement that land use activities counteract or exacerbate

climate-driven vegetation change (Aleman etal., 2017; Timm Hoffman

etal., 2019). Decreased woody plant biomass in 11% of sub-Saharan

Africa was attributed to land clearing for agriculture (Brandt etal., 2017;

Ordway etal., 2017). Localised loss of tree cover in Miombo woodlands

and 16.6±0.5Mha of forest loss in the Congo Basin between 2000–2014

was driven largely by forest clearing and drought mortality (McNicol

etal., 2018; Tyukavina etal., 2018).

Vegetation changes interacting with climate and land use change

have impacted ﬁre regimes across Africa. The frequency of weather

conducive for ﬁre has increased in southern and west Africa and is

expected to continue increasing in the 21st century under both RCP2.6

and RCP8.5 (Betts et al., 2015; Abatzoglou et al., 2019). Increased

grass cover in arid regions introduced ﬁre into regions where fuel

was previously insufﬁcient to allow ﬁre spread, such as the arid Karoo

in South Africa (du Toit etal., 2015; Strydom and Savage, 2016). In

contrast, shrub encroachment, increased precipitation (Zubkova etal.,

2019), vegetation fragmentation and cropland expansion have reduced

ﬁre activity in many African grasslands and savannas (Andela and van

der Werf, 2014; Probert etal., 2019). These drivers are expected to

negate the effect of increasing ﬁre weather and ultimately lead to a

reduction in the total burned area under RCP4.5 and RCP8.5 (Knorr

etal., 2016; Moncrieff etal., 2016; Wu etal., 2016).

9.6.1.2 Vegetation Resilience

African ecosystems have a long evolutionary association with ﬁre,

large mammal herbivory and drought (Maurin etal., 2014; Charles-

Dominique et al., 2016). The maintenance of biodiversity depends

on natural disturbance regimes. Natural regrowth of savanna plant

biomass in southern Africa compensated for biomass removal through

human activities (McNicol etal., 2018), and rapid recovery occurred

after the 2014–2016 extreme drought (Abbas et al., 2019). During

the same drought event, browsing and mixed feeder herbivores

were resilient, but grazers declined by approximately 60% and were

highly dependent on drought refugia (Abraham etal., 2019). African

tropical forests remained a carbon sink through the record drought

and temperature experienced in the 2015–2016 El Niño, indicating

resilience in the face of extreme environmental conditions (Bennett

et al., 2021). This is likely due to the presence of drought-tolerant

species and ﬂoristic and functional shifts in tree species assemblages

(Fauset et al., 2012; Aguirre-Gutiérrez et al., 2019). This resilience

indicates that there is the capacity to recover from disturbances

and short-term change. However, resilience has limits and beyond

certain points, change can lead to irreversible shifts to different states

(Figure9.18).

9.6.1.3 Freshwater Ecosystems

Small climatic variations have large impacts on ecosystem function

in Africa’s freshwaters (Ndebele-Murisa, 2014; Ogutu-Ohwayo etal.,

2016). Warming of water temperatures from 0.2°C to 3.2°C occurred in

several lakes over 1927–2014 and has been attributed to human-caused

climate change (Figure9.17; Ogutu-Ohwayo et al., 2016). Increased

temperature, changes in rainfall and reduced wind speed altered the

physical and chemical properties of inland water bodies, affecting

water quality and productivity of algae, invertebrates and ﬁsh (high

conﬁdence). In deeper lakes, warmer surface waters and decreasing

wind speeds reduced shallow waters mixing with nutrient-rich deeper

waters, reducing biological productivity in the upper sunlit zone

(Ndebele-Murisa, 2014; Saulnier-Talbot etal., 2014). In several lakes,

climate change was identiﬁed as causing changes in insect emergence

time (Dallas and Rivers-Moore, 2014) and in loss of ﬁsh habitats

(Natugonza et al., 2015; Gownaris etal., 2016). This set of changes

can harm human livelihoods, for example, from reduced ﬁsheries

productivity (see Section9.8.5; Ndebele-Murisa, 2014; Ogutu-Ohwayo

etal., 2016) and reduced water supply and quality (Section9.7.1).

9.6.1.4 Marine Ecosystems

Anthropogenic climate change is already negatively impacting Africa’s

marine biodiversity, ecosystem functioning and services by changing

physical and chemical properties of seawater (increased temperature,

salinity and acidiﬁcation, and changes in oxygen concentration, ocean

currents and vertical stratiﬁcation) (high conﬁdence) (Hoegh-Guldberg

etal., 2014; 2018). Coastal ecosystems in west Africa are among the

most vulnerable because of extensive low-lying deltas exposed to sea

level rise, erosion, saltwater intrusion and ﬂooding (Belhabib et al.,

2016; UNEP, 2016b; Kifani et al., 2018). In southern Africa, shifting

distributions of anchovy, sardine, hake, rock lobster and seabirds have

been partly attributed to climate change (Crawford etal., 2015; van

der Lingen and Hampton, 2018; Vizy etal., 2018), including southern

shifts of 30 estuarine and marine ﬁsh species attributed to increased

temperature and changes in water circulation from decreased river

inﬂow (Augustyn et al., 2018). Warming sea surface temperatures

inhibiting nutrient mixing have reduced phytoplankton biomass in the

western Indian Ocean by 20% since the 1960s, potentially reducing

tuna catches (Roxy etal., 2016).

Mangroves, seagrasses and coral reefs support nursery habitats for

ﬁsh, sequester carbon, trap sediment and provide shoreline protection

(Ghermandi et al., 2019). Climate change is compromising these

ecosystem services (medium conﬁdence). Marine heatwaves associated

with ENSO events have triggered mass coral bleaching and mortality

over the past 20years (Oliver etal., 2018). Mass coral bleaching in the

western Indian Ocean occurred in 1998, 2005, 2010 and 2015/2016

with coral cover just 30–40% of 1998 levels by 2016 (Obura etal.,

2017; Moustahﬁd etal., 2018). The northern Mozambique Channel

has served as a refuge from climate change and biological reservoir

for the entire coastal east African region (McClanahan etal., 2014;

Hoegh-Guldberg etal., 2018). A southern shift of mangrove species

has been observed in south Africa (Peer etal., 2018) with loss in total

suitable coastal habitats for mangroves and shifts in the distribution of

some species of mangroves and a gain for others (Record etal., 2013).

Mangrove cover was reduced 48% in Mozambique in 2000 from

Tropical Cyclone Eline, with 100% mortality of seaward mangroves

dominated by Rhizophora mucronata (Macamo etal., 2016). Recovery

of mangrove species was observed 14years later in sheltered sites.

There is low conﬁdence these cyclone-induced impacts are attributable

to climate change owing, in part, to a lack of reliable long-term data

sets (Macamo et al., 2016). In west Africa, oil and gas extraction,

deforestation, canalisation and de-silting of waterways have been the

largest factors in mangrove destruction (Numbere, 2019).

1334

Chapter 9 Africa

9.6.2 Projected Risks of Climate Change for African

Biodiversity and Ecosystem Services

9.6.2.1 Projected Biome Distribution

The geography of African biomes is projected to shift due to changes in

atmospheric CO2 concentrations and aridity (Figure9.18). Grassland

expansion into the desert, woody expansion into grasslands and

forest expansion into savannas are projected for areas of reduced

aridity, caused by reduced moisture stress from CO2 fertilisation

under medium (RCP4.5) and high (SRES A2) emissions scenarios

(Heubes et al., 2011; Moncrieff et al., 2016). This greening trend

may slow or reverse with continued temperature increase and/or in

areas of increased aridity (Berdugo etal., 2020). The net impact of

these effects on vegetation is highly uncertain (Trugman etal., 2018;

Cook etal., 2020a; Martens et al., 2021). The maintenance or re-

establishment of natural ﬁre and large mammal herbivory processes

can mitigate projected CO2 and climate-driven changes (Scheiter and

Savadogo, 2016; Stevens etal., 2016). Expansion of croplands and

pastures will reduce ecosystem carbon storage in Africa, potentially

reversing climate- and CO2-driven greening in savannas (Aleman

etal., 2018; Quesada etal., 2018).

Vegetation growth simulated by dynamic vegetation models is often

highly sensitive to CO2 fertilisation. These models project the African

tropical forest carbon sink to be stable or strengthened under scenarios

of future climate change (Huntingford etal., 2013; Martens etal., 2021).

In contrast, statistical modelling suggests it has begun to decline and

will weaken further, decreasing from current estimates of 0.66 tonnes

of carbon removed from the atmosphere per hectare per year to 0.55

tonnes of carbon (Hubau etal., 2020). Increasing rainfall seasonality

and aridity over central Africa (Haensler etal., 2013) threatens the

massive carbon store in the Congo Basin’s Cuvette Centrale peatlands,

estimated at 30.6billion tonnes (Dargie etal., 2019).

9.6.2.2 Terrestrial Biodiversity

Local extinction is when a species is extirpated from a local site.

The magnitude and extent of local extinctions predicted across

Africa increase substantially under all future GWLs (high conﬁdence)

(a) Terrestrial vegetation

(b) Freshwater ecosystems

Functional type switch

Forest cover gain

Forest/woodland/shrub decline

Grass cover gain

Grass cover loss

Shrub/woodland cover gain

Climate driver

Correlated with

climate change driver

Proposed climate change driver

Not reported

Not climate change related

Surface water

temperature change (°C/decade)

-0.2– -0.1

-0.1–0

0–0.1

0.1–0.2

0.2–0.3

0.3–0.4

0.4–0.5

Lake temperature change (°C/decade)

0.05–0.2

0.2–0.4

0.4–0.6

0.6–0.76

Observation type

Satellite

in−situ

Observed changes in vegetation and freshwater ecosystems

Figure9.17 | Widespread changes to African vegetation have been reported, especially increasing woody plant cover in many savannas and grasslands,

with 37% of these changes proposed to be driven by human-caused climate change and increased CO2 (a). The warming of lakes and rivers has been detected across

Africa and is attributed to climate change. Data on vegetation change was gathered from 156studies published between 1989 and 2021(b). Climatic changes, mostly associated

with changes in rainfall, are enhancing grass production in arid grasslands and savannas, and causing grass expansion into semi-desert regions with notable increases in the Sahel

and southern Africa. Tropical forest expansion into mesic savannas is occurring on the fringes of the central African tropical forest. Interactions between land use, climate change

and increasing atmospheric CO2 concentrations are causing a widespread increase in woody plant cover encroachment in tropical savannas and grasslands. Some tree death and

woody cover decline associated with climate and land use change have also been recorded across biomes. Of the reported changes to terrestrial vegetation, 24% were explicitly

linked to climate change and a further 13% were proposed to be driven by climate change. In 48% of studies, no climate driver was mentioned and in 15% climate change was

ruled out as the driver of change. Annual surface water temperatures in African lakes have warmed at a rate of 0.05°C–0.76°C per decade. Both satellite-based measures spanning

1985–2011 and in situ measurements spanning 1927–2014 agree on this warming trend. Other surface waters across Africa warmed from 1979–2018 at a rate of between

0.05°C and 0.5°C per decade (Woolway and Maberly, 2020). Vegetation change data were taken from a larger, global literature survey of existing databases supplemented with

newer studies documenting changes in tree, shrub and grass cover linked to climate and land use change in natural and semi-natural areas (for further details see Section2.4.3.5;

TableSM2.1; TableSM9.2 for Africa vegetation change data and TableSM9.3 for studies reporting lake warming data).

1335

Africa Chapter 9

A schematic representing biome distribution across an aridity gradient in Africa.

Aridity is an important determinant of these biomes, however the distribution of

grasslands, savannas and forests are also strongly shaped by interactions between

disturbance and climate and as such changes in disturbances are also important

determinants of biomes boundaries. Multiple stable biome states are often possible at

the transition between savanna and forest. Shifts in rainfall seasonality are not

depicted here, though through altering disturbance regimes and drought intensity, this

is also expected to be an important factor.

Increases in atmospheric CO

and changes in aridity

are projected to shift the geographic distribution of major biomes across

Africa

SavannaGrasslandShrublandDesert Forest

Forests expand into savannas;

savannas experience densification and tending to

become closed canopy systems.

As CO2 increases the water use efficiency of

trees and grasses increases causing woody

proliferation in arid savannas. This may also

induce expansion of grasses into arid shrublands.

Increasing Aridity Decreasing Aridity

CO2

In areas with increased aridity in addition to rising CO2 an increase in forest die-off

is likely and a slowing in the rate of woody plant encroachment may occur. Arid

shrublands may experience increases in plant die off.

Further expansion of forest into savanna and a significant loss of savanna

grassland to closed canopied forests and thickets. Expansion of savannas into

cooler grasslands. Higher CO2 and decreased aridity will promote grass expansion

into arid shrublands.

creasin

Aridit

Figure9.18 | Increases in atmospheric CO2 and changes in aridity are projected to shift the geographic distribution of major biomes across Africa (high

conﬁdence). Arrows in the diagram indicate possible pathways of biome change from current conditions resulting from changes in CO2 and aridity. Changes need not be gradual

or linear and may occur rapidly if tipping points are crossed. Currently, widespread greening observed in Africa has been at least partially attributed to increasing atmospheric CO2

concentrations. Future projected increases in aridity are expected to cause desertiﬁcation in many regions, but it is highly uncertain how this will interact with the greening effect

of CO2. Inset maps show the projected geographical extent of changes in CO2 concentrations and aridity. CO2 is projected to increase globally under all future emission scenarios.

Aridity index maps show projected change in aridity (calculated as annual precipitation/annual potential evapotranspiration) at around 4°C global warming relative to 1850–1900

(RCP8.5 in 2070–2099) from 34 CMIP5 models (Scheff etal., 2017). Shaded areas indicate regions where >75% of models agree on the direction of change.

(Table9.5; Figure9.19). Above 2°C, the risk of sudden disruption or

loss of local biodiversity increases and becomes more widespread,

especially in central, west and east Africa (Trisos etal., 2020).

Global extinction is when a species is extirpated from all areas. At 2°C

global warming, 11.6% of African species (mean 11.6%, 95% CI 6.8–

18.2%) assessed are at risk of global extinction, placing Africa second

only to South America in the magnitude of projected biodiversity losses

(Urban, 2015). At >2°C, 20% of north African mammals may lose all

1336

Chapter 9 Africa

suitable climates (Soultan et al., 2019), and over half of the dwarf

succulents in South African Karoo may lose >90% of their suitable

habitat (Young etal., 2016). Among the thousands of species at risk,

many are species of ecological, cultural and economic importance such

as African wild dogs (Woodroffe etal., 2017) and Arabica coffee (Moat

etal., 2019).

With increasing warming, there is a lower likelihood species can

migrate rapidly enough to track shifting climates, increasing global

extinction risk and biodiversity loss across more of Africa (high

conﬁdence). Immigration of species from elsewhere may partly

compensate for local extinctions and lead to local biodiversity gains

in some regions (Newbold, 2018; Warren etal., 2018). However, more

regions face net losses than net gains. At 1.5°C global warming,

>46% of localities face net declines in vertebrate species richness

of >10%, with net increases projected for less than 15% of localities

(Barbet-Massin and Jetz, 2015; Newbold, 2018). At >2°C, 9% of

species face complete range loss by 2100, regardless of their dispersal

ability (Urban, 2015). With >4°C global warming, a net loss of >10%

of vertebrate species richness is projected across 85% of Africa

(Barbet-Massin and Jetz, 2015; Mokhatla etal., 2015; Newbold, 2018;

Warren etal., 2018). Mountain top endemics and species in north and

southern Africa are at risk due to disappearing cold climates (Milne

etal., 2015; Garcia etal., 2016; Bentley etal., 2018; Soultan etal.,

2019). For hot regions such as the Sahara, Congo Basin and Kalahari,

no warmer-adapted species are available elsewhere to compensate

for local extinctions, so the resilience of local biodiversity will depend

entirely on the persistence of species (Burrows etal., 2014; Garcia

et al., 2014). The capacity for species to avoid extinction through

behavioural thermoregulation, plasticity or evolution is uncertain but

will become increasingly unlikely under higher warming scenarios

(Conradie etal., 2019).

9.6.2.3 Marine Ecosystems

African coastal and marine ecosystems are highly vulnerable to

climate change (high conﬁdence). At 1.5°C of global warming,

mangroves will be exposed to sedimentation and sea level rise, while

seagrass ecosystems will be most affected by heat extremes (high

conﬁdence) (Hoegh-Guldberg etal., 2018) and turbidity (Wong etal.,

2014). These risks will be ampliﬁed at 2°C and 3°C (virtually certain)

(Hoegh-Guldberg et al., 2018). Over 90% of east African coral

reefs are projected to be destroyed by bleaching at 2°C of global

warming (very high conﬁdence) (Hoegh-Guldberg etal., 2018). At

around 2.5°C global warming, an important reef-building coral

(Diploastrea heliopora) in the central Red Sea is projected to stop

growing altogether (Cantin etal., 2010). By 2.5°C, suitable habitat

of >50% of species are projected to decline for coastal lobster

in east and north Africa, with large declines for the commercially

important lobster species Jasus lalandii in southern Africa (Boavida-

Portugal etal., 2018). More generally, tropical regions, especially

exclusive economic zones in west Africa, are projected to lose large

numbers of marine species and may experience sudden declines with

extratropical regions having potential net increases as species track

shifting temperatures poleward (GarcíaMolinos et al., 2016; Trisos

etal., 2020).

9.6.2.4 Freshwater Ecosystems

Above 2°C global warming, the proportion of freshwater ﬁsh species

vulnerable to climate change increases substantially (high conﬁdence)

(Figure9.19). At 2°C, 36.4% of ﬁsh species are projected to be vulnerable

to local or global extinction by 2100, increasing to 56.4% under 4°C

warming (average of values from (Nyboer et al., 2019; Barbarossa

etal., 2021) (Figure9.19). Global warming reduces available habitat for

freshwater species due to reduced precipitation and increased drought

leading to increasing water temperatures above optimal physiological

limits in ﬂoodplains, estuaries, wetlands, ephemeral pools, rivers and

lakes (Dalu etal., 2017; Kalacska etal., 2017; Nyboer and Chapman,

2018). Along the Zambezi River, projected ﬂow reductions could cause

a 22% reduction in annual spawning habitat and depletion of food

resources for fry and juvenile ﬁsh that could impede ﬁsh migration

and reduce stocks (Kangalawe, 2017; Martínez-Capel et al., 2017;

Tamatamah and Mwedzi, 2020). More aquatic species will have the

capacity to cope with 2°C compared to 4°C global warming, with more

negative effects on physiological performance at 4°C (Dallas, 2016;

Pinceel et al., 2016; Zougmoré etal., 2016; Nyboer and Chapman,

2017; Ross-Gillespie etal., 2018). Endemic, specialised ﬁsh species

will have a lower capacity to adjust to elevated water temperatures

compared to hardier generalist ﬁshes (McDonnell and Chapman, 2015;

Nyboer and Chapman, 2017; Lapointe etal., 2018; Reizenberg etal.,

2019). More work is needed to understand the risk for invertebrates

(Dallas and Rivers-Moore, 2014; Cohen etal., 2016), and to understand

the potential effects of reduced mixing of water and other climate risks

on freshwater biodiversity.

Table9.5 | Risk of local extinction increases across Africa with increasing global warming.

Global warming level

(relative to 1850–

1900)

Taxa

Percentage of species

at a site at risk of local

extinction

Extent across Africa

(percentage of the

land area of Africa)

Areas at risk References

1.5°C Plants, insects,

vertebrates >10% >90%

Widespread. Hot and/or arid regions

especially at risk, including Sahara,

Sahel and Kalahari

Figure9.29b; Newbold (2018);

Warren etal. (2018)

>2°C Plants, insects,

vertebrates >50% 18% Widespread Newbold (2018); Warren etal.

(2018)

>4°C Plants, insects,

vertebrates >50% 45–73%

Widespread. Higher uncertainty

for central African tropical forests

due to lower agreement between

biodiversity models

Fig.9.29c; Newbold (2018);

Warren etal. (2018)

1337

Africa Chapter 9

(a)

The loss of African biodiversity

under future climate change

is projected to be widespread and increasing

substantially with every 0.5°C above the

current (2001–2020) level of global warming

(e) 2.6–3.2°C(d) 1.5–2°C

Species

locally

extinct

100%

75%

50%

25%

0100%75%50%25%

Model agreement

Vulnerable

freshwater

fish

species

100%

75%

50%

25%

0100%75%50%25%

Model agreement

>3.0>1.5>2.0>1.0

Biodiversity

change

100%

-20%

-40%

-60%

-80%

-100%

200%

Global warming (°C)

Figure9.19 | The loss of African biodiversity under future climate change is projected to be widespread and increasing substantially with every 0.5° above

the current (2001–2020) level of global warming (high conﬁdence).

(a) Projected biodiversity loss, quantiﬁed as percentage change in species abundance, range size or area of suitable habitat increases with increasing global warming levels

(relative to 1850–1900). Above 1.5°C global warming, half of all assessed species are projected to lose >30% of their population, range size or area of suitable habitat, with losses

increasing to >40% for >2°C. The 2001–2020 level of global warming is around 1°C higher than 1850 –1900 (IPCC, 2021). Boxplots show the median (horizontal line), 50%

quantiles (box), and points are studies of individual species or of multiple species (symbol size indicates the number of species in a study).

(b–c) The mean projected local extinction of vertebrates, plants and insects within 100 km grid cells increases in severity and extent under increased global warming (relative

to 1850–1900). Local extinction >10% is widespread by 1.5°C. Pixel colour shows the projected percentage of species undergoing local extinction and the agreement between

multiple biodiversity models.

1338

Chapter 9 Africa

9.6.2.5 Climate Change and Ecosystem Services

Direct human dependence on provisioning ecosystem services in

Africa is high (Egoh etal., 2012; IPBES, 2018). For example, natural

forests provided 21% of rural household income across 11 African

countries (Angelsen etal., 2014) and wild-harvested foods (including

ﬁsheries) provide important nutrition to millions of Africans, including

through important micronutrients and increased dietary diversity

(Sections9.8.2.3; 9.8.5; Powell etal., 2013; Baudron etal., 2019a).

Climate change has affected ecosystem services in Africa by reducing

ﬁsh stocks, crop and livestock productivity, and water provisioning due

to heat and drought (see Sections9.8.2.1; 9.8.2.2; 9.8.2.4; 9.8.5.1).

Woody encroachment is decreasing cattle production and water

supply (Smit and Prins, 2015; Stafford et al., 2017), but can also

provide forage for goat production, as well as resins, fuelwood and

charcoal (Reed etal., 2015; Stafford etal., 2017; Charis etal., 2019).

Local communities perceive climate change to have decreased crop

and livestock productivity, reduced wild food availability and reduced

forest resources across Africa (see Sections9.8.2.1; 9.8.2.2; 9.8.2.4;

9.8.2.3; Onyekuru and Marchant, 2014).

With global warming >3°C, and with high population growth and

agricultural expansion (SSP3, 2081–2100), 1.2billion Africans are

projected to be negatively affected by pollution of drinking water from

reduced water quality regulation by ecosystems and 27million people

affected by reduced coastal protection by ecosystems (Chaplin-Kramer

etal., 2019). The number of people affected reduces to 0.4billion and

22 million, respectively, under a sustainable development scenario

with global warming below 2°C (SSP1, 2081–2100). The African

tropical forest carbon sink has been more resilient than Amazonia

to recent warming but may already have peaked, and this service

is predicted to decline with further warming, reducing 14% by the

2030s (Hubau etal., 2020; Sullivan etal., 2020). This declining carbon

storage may be offset by CO2 fertilization (low conﬁdence) (Martens

et al., 2021). Climate change is projected to shift the geographic

distribution of important human and livestock disease vectors (see

Sections9.8.2.4; 9.10.2). Changes in rainfall seasonality compounded

with land privatisation and population growth mayadversely impact

nomadic and semi-nomadic pastoralists who follow shifting patterns

of greening vegetation (Van Der Ree etal., 2015).

9.6.2.6 Invasive Species

Invasive species threaten African ecosystems and livelihoods (Ranasinghe

et al., 2021). For instance, economic impacts were estimated at

USD1billion per year for smallholder maize farmers in east Africa (Pratt

etal., 2017). Climate change is projected to change patterns of invasive

species spread (high conﬁdence). The area of suitable climate for Lantana

camara is projected to contract (Taylor etal., 2012) and to expand for

Prosopis juliﬂora (Sintayehu et al., 2020). Bioclimatic suitability for fall

armyworm, a major threat to maize, is projected to decrease in central

Africa but expand in southern and west Africa (Zacarias, 2020), and to

expand for coffee berry borer (Hypothenemus hampei) in Uganda and

around Mount Kenya (Jaramillo et al., 2011). Climate suitability for

tephritid fruit ﬂies is projected to decrease in central Africa (Hill etal.,

2016). Increased water temperature is projected to favour invasive over

local freshwater ﬁsh populations and shift the range of invasive aquatic

plants in South Africa (Hoveka etal., 2016; Shelton etal., 2018). Alterations

to lake and river connectivity are predicted to modify invasion pathways in

Lake Tanganyika and water hyacinth coverage may increase with warmer

waters in Lake Victoria (Masters and Norgrove, 2010; Plisnier etal., 2018).

9.6.3 Nature-based Tourism in Africa

Nature-based tourism is important for African economies and jobs.

Tourism contributed 8.5% of Africa’s 2018 gross domestic product

(GDP) (World Travel and Tourism Council, 2019a) with wildlife tourism

contributing a third of tourism revenue (USD70.6billion), supporting

8.8million jobs (World Travel and Tourism Council, 2019b).

Climate change is already negatively affecting tourism in Africa (high

conﬁdence). The 2015–2018 Cape Town drought caused severe water

restrictions, reducing tourist arrivals and spending with associated job

losses (Dube etal., 2020). Human-caused climate change increased the

likelihood of the reduced rainfall that caused the drought by a factor

of three (Otto etal., 2018)(Pascale etal., 2020). Extreme heat days

have increased across South African national parks since the 1990s

(van Wilgen etal., 2016). This reduces animal mobility, decreasing

animal viewing opportunities (Dube and Nhamo, 2020). Tourists and

employees also fear heat stress (Dube and Nhamo, 2020). Visitors

to South Africa’s national parks preferred to visit in cool-to-mild

temperatures (Coldrey and Turpie, 2020). Extreme weather conditions

disrupted tourist activities and damaged infrastructure at Victoria

Falls, Hwange National Park, Kruger National Park and the Okavango

Delta (Dube etal., 2018; Dube and Nhamo, 2018; Mushawemhuka

etal., 2018; Dube and Nhamo, 2020). Rainfall variability and drought

alter wildlife migrations, affecting tourist visits to the Serengeti

(Kilungu etal., 2017). Reduced tourism decreases revenue for national

park management (van Wilgen etal., 2016).

Future climate change is projected to further negatively affect nature-

based tourism. Decreased snow and forest cover may reduce visits to

(d–e) The mean projected increase in species of freshwater ﬁsh vulnerable to local extinction within 10 km grid cells for future global warming. Around a third of ﬁsh species are

projected to be vulnerable to extinction by 2°C global warming. Pixel colour shows the projected percentage of species vulnerable to extinction and agreement between multiple

vulnerability models. In (a), data were obtained from 22 peer-reviewed papers published since 2012 investigating the impacts of projected climate change on African biodiversity.

When a paper provided impact projections for several time periods, climate change scenarios or for more than one species, each impact was recorded as an individual biodiversity

impact projection, resulting in a database of 1165 biodiversity impact projections. Data were initially collected by Manes et al. (2021) as part of a larger literature review for

Cross-Chapter Paper 1 on Biodiversity Hotspots and then expanded to include areas outside of African priority conservation areas (see TableSM 9.4). The literature review was

limited to peer-reviewed publications that reported quantiﬁable risks to biodiversity, eliminating non-empirical studies. In (b–c), projections are based on intersecting current

andfuturemodelled species distributions at ~10 km spatial resolution from two recent global assessments of climate change impacts on terrestrial vertebrates (Newbold, 2018;

Warren etal., 2018). In (d-e) projections are based on intersecting future species vulnerabilities from two recent assessments of climate change vulnerability of freshwater ﬁsh

species (Nyboer etal., 2019; Barbarossa etal., 2021).

1339

Africa Chapter 9

Kilimanjaro National Park (Kilungu etal., 2019). Woody plant expansion

in savanna and grasslands reduce tourist’s game viewing experience and

negatively impact conservation revenues (Gray Emma and Bond William,

2013; Arbieu et al., 2017). Visitation rates to South African national

parks, based on mean monthly temperatures, are projected to decline

4% with 2°C global warming (Coldrey and Turpie, 2020). Sea level rise

and increased intensity of storms is projected to reduce beach tourism

due to beach erosion (Grant, 2015; Amusan and Olutola, 2017). Tourism

in the Victoria Falls, Okavango and Chobe hydrological systems may be

negatively affected by heat and increased variability of rainfall and river

ﬂow (Saarinen etal., 2012; Dube and Nhamo, 2019). Increased extreme

heat will increase air turbulence and weight restrictions on aircraft,

which could make air travel more uncomfortable and expensive to

African destinations (Coffel and Horton, 2015; Dube and Nhamo, 2019).

9.6.3.1 Protected Areas and Climate Change

African protected areas store around 1.5% of global land ecosystem

carbon stocks and support biodiversity (Gray etal., 2016; Melillo etal.,

2016; Sala etal., 2018). They also support livelihoods and economies,

such as through nature-based tourism and improved ﬁsheries

(Brockington and Wilkie, 2015; Mavah etal., 2018; Ban etal., 2019).

Climate change and land use change will interact to inﬂuence the

effectiveness of African protected areas (high conﬁdence). Species

representation in the existing African protected area network is

projected to decrease due to species range shifts for mammals, bats,

birds and amphibians (Hole et al., 2009; Baker etal., 2015; Payne

713 Adaptation actions were identified in

52 Nationally Determined Contributions (NDCs)

from African countries as of early 2020

Coastal zone

Cross-cutting area

Disaster Risk Management (DRM)

Education

Energy

Social development

Tourism

Urban

(7) Afforestation

(5) Agroecology

(8) Agroforestry

(12) Climate smart agriculture

(18) Coastal zone

(17) Crops

(3) Cross-cutting area

(5) Disaster Risk Management (DRM)

(28) Ecosystem and biodiversity

(2) Education

(10) Energy

(7) Fisheries and aquaculture

(5) Food security

(6) Irrigation

(22) Land and soil management

(5) Land degradation

(5) Livestock

(9) Reforestation

(1) Social development

(20) Sustainable forest management

(14) Sustainable land management

(1) Tourism

(5) Urban

(5) Water conservation and reuse

(3) Water infrastructure

(15) Water mmanagement

(7) Water supply

(12) Watershed and river basin management

(1) Wetlands

Sectors planning strategies linked to ecosystem-based adaptation

258 or 36% of these

are Ecosystem-based

adaptation (EbA)

actions

Sub-sectors

(number of EbA actions)

Agriculture

Environment

Forestry and

other land use

Water

More than 80%

are in these

four sectors

Sectors

Figure9.20 | Over a third (36%) of all adaptation actions identiﬁed in the NDCs of 52 African countries as of early 2020 were ecosystem-based adaptations

(EbA). Of these actions ±83% fall within the agriculture, land use/forestry, environment and water sectors. The EbA actions identiﬁed from the NDCs span 12 primary sectors and

29 sub-sectors.

and Bro-Jørgensen, 2016; Smith etal., 2016; Phipps et al., 2017).

Species ability to disperse between areas to track shifting climates is

increasingly impaired by land transformation and fencing, which also

impact seasonal wildlife migrations (Lovschal etal., 2017; Sloan etal.,

2017). On land, only 0.5% of the African protected area network is

connected through low-impact landscapes (Ward etal., 2020). Linear

transport infrastructure (e.g., roads, railways, pipelines) and fencing

from proposed ‘development corridors’ are projected to bisect over 400

protected areas and degrade around 1800 more (Laurance etal., 2015).

Climate change could increase human–wildlife conﬂict as resultant

resource shortages cause communities to move into protected areas

for harvesting or livestock grazing, or wildlife to move out of protected

areas and into contact with people (Mukeka etal., 2018; Kupika etal.,

2019; Hambira etal., 2020). See Section9.6.4 for the role of land and

ocean protected areas in climate change adaptation.

9.6.4 Ecosystem-based Adaptation in Africa

Ecosystem-based adaptation (EbA) uses biodiversity and ecosystem

services to assist people to adapt to climate change (Swanepoel and

Sauka, 2019). Africa’s Nationally Determined Contributions (NDCs)

show 36% of adaptation actions identiﬁed by 52 countries are

considered to be EbA (Figure9.20).

EbA can reduce climate impacts and there is high agreement EbA

can be more cost-effective than traditional grey infrastructure

when a range of economic, social and environmental beneﬁts are

1340

Chapter 9 Africa

Table9.6 | The beneﬁcial outcomes of ecosystem-based adaptation (EbA) actions and assessed conﬁdence in these outcomes. Assessment is provided for EbA options in the

four most prevalent EbA sectors identiﬁed in the Nationally Determined Contributions of 52 African countries (Figure9.20). See Chapter 2.6.3 and 3.6.2 of this report for further

assessment of EbA approaches in terrestrial, freshwater and marine systems.

Sector EbA Action(s) Outcome(s) Conﬁdence Source(s)

Agriculture

Conservation agriculture

Improved soil and water conservation High Thierfelder etal. (2017)

Improved agricultural productivity and drought

resilience Medium Pittelkow etal. (2015); Thierfelder etal. (2017); Adenle

etal. (2019)

Diversiﬁed crop varieties Improved agricultural productivity and drought

resilience High Shiferaw etal. (2014); Tesfaye etal. (2016); Thierfelder

etal. (2017)

Environment Ecosystem protection and

restoration

Carbon sequestration and storage High Melillo etal. (2016); Griscom etal. (2017); FAO (2018a)

Stepping stones for species migrating due to climate

change Medium Beale etal. (2013); Roberts etal. (2020)

Increased ecosystem resilience to disturbance High Anthony etal. (2015); Sierra-Correa and Cantera Kintz

(2015); Kroon etal. (2016); Roberts etal. (2017)

Livelihood diversiﬁcation opportunities from

ecotourism, resource harvesting and rangelands

(among others)

Medium Lunga and Musarurwa (2016); Bedelian and Ogutu (2017);

Agyeman (2019); Kupika etal. (2019); Naidoo etal. (2019)

Forestry and

other land use

Restoration/ reforestation

Sustainable forestry and land

management

Restoration of degraded ecosystems and enhanced

carbon sequestration High Mugwedi etal. (2018)

Reducing pressure on forests for food and energy

needs Medium Peprah (2017); Zegeye (2018)

Water Integrated catchment

management

Improved ﬂood attenuation capacity High Bradshaw etal. (2007); Mwenge Kahinda etal. (2016);

Rawlins etal. (2018)

Improved resilience of freshwater ecosystems High Ndebele-Murisa (2014); Natugonza etal. (2015); (2019);

Tamatamah and Mwedzi (2020)

also accounted for (Table 9.6; Baig et al., 2016; Emerton, 2017;

Chausson etal., 2020). This is particularly relevant in Africa where

climate vulnerabilities are strongly linked to natural resource-based

livelihood practices and existing grey infrastructure levels are low in

many regions (Dube etal., 2016; Reid etal., 2019). However, ﬁnancial

constraints limit EbA project implementation (Mumba et al., 2016;

Swanepoel and Sauka, 2019).

Evidence for EbA in Africa is largely case study based and often anecdotal

(Reid et al., 2018). There is high agreement that costs, challenges and

negative outcomes of EbA interventions are still poorly understood (Reid,

2016; Chaplin-Kramer etal., 2019), despite limited evidence for the efﬁcacy

of context-speciﬁc applications at different scales (Doswald etal., 2014).

9.6.4.1 Terrestrial Ecosystems

Improved ecosystem care and restoration are cost-effective for

carbon sequestration while providing multiple environmental, social

and economic co-beneﬁts (Griscom etal., 2017; Shukla etal., 2019).

Protecting and restoring natural forests and wetlands reduces ﬂood

risk across multiple African countries (Bradshaw etal., 2007). In Kenya,

enclosures for rangeland regeneration diversiﬁed income sources,

which could increase the adaptive capacity of local people (Mureithi

etal., 2016; Wairore etal., 2016). Sustainable agroforestry in semi-

arid regions provides income sources from fuelwood, fruit and timber

and reduces exposure to drought, ﬂoods and erosion (Quandt etal.,

2017). Forest protection in Zimbabwe maintains honey production

during droughts, providing food supply options if crops fail (Lunga and

Musarurwa, 2016). Community-based natural resource management

in pastoral communities improved institutional governance outcomes

through involving community members in decision making, increasing

the capacity of these communities to respond to climate change (Reid,

2014).

EbA can also increase ecological resilience. Re-introduction of ﬁre and

large mammals can restore ecosystem services, enhance adaptive

capacity and beneﬁt people by combatting woody encroachment,

restoring grazing and increasing streamﬂow (Asner etal., 2016; Stafford

etal., 2017; Cromsigt etal., 2018). Herbivores can also reduce fuel loads

in areas facing increased ﬁre risk (Hempson etal., 2017).

Protected areas can be ‘stepping stones’ that facilitate climate-induced

species range shifts (Roberts et al., 2020), preserve medicinal plant

diversity despite climate change (Kaky and Gilbert, 2017) and provide

livelihood diversiﬁcation opportunities (Table9.6). Protecting 30% of

sub-Saharan Africa’s land area could reduce the proportion of species

at risk of extinction by around 60% in both low and high warming

scenarios (Hannah etal., 2020). The role of protected areas in EbA can be

strengthened by: (a) increasing coverage of diverse environments and

high carbon storage ecosystems, (b) restoring habitat, (c) maintaining

intact habitat, (d) participatory, equitable conservation and adaptation

strategies; (e) cooperating across borders and (f) adequate monitoring

(Gillson etal., 2013; Rannow etal., 2014; Midgley and Bond, 2015; Pecl

etal., 2017; Dinerstein etal., 2019; Roberts etal., 2020).

9.6.4.2 Freshwater Ecosystems

EbA can mitigate ﬂooding and increase the resilience of freshwater

ecosystems (Table9.6). Adaptation in African freshwater ecosystems is

heavily inﬂuenced by non-climate anthropogenic factors, including land

1341

Africa Chapter 9

use change, water abstraction and diversion, damming and overﬁshing

(Dodds etal., 2013; Kimirei etal., 2020; UNESCO and UN-Water, 2020).

Wetlands and riparian areas support biodiversity, act as natural ﬁltration

systems and serve as buffers to changes in the hydrological cycle, thereby

increasing the resilience of freshwater ecosystems and the people that

rely on them (Ndebele-Murisa, 2014; Musinguzi etal., 2015; Lowe etal.,

2019). However, national adaptation programmes of action, NAPs and

national communications rarely consider the ecological stability of

ecosystems safeguarding the very water resources they seek to preserve

(Kolding etal., 2016). Some countries have mandated the protection

of riparian zones, but implementation is low (Musinguzi etal., 2015;

Muchuru and Nhamo, 2018). Protecting terrestrial areas surrounding Lake

Tanganyika beneﬁted ﬁsh diversity (Britton etal., 2017). Afforestation

reduces water availability but forest restoration and removing invasive

plant species can increase water ﬂows in regions facing water insecurity

from climate change (Chausson et al., 2020; Le Maitre etal., 2020).

Box9.3 | Tree planting in Africa

Due to widespread deforestation and forest degradation (Malhi etal., 2014), future scenarios to limit global warming include large-scale

reforestation and afforestation (Griscom etal., 2017; Bastin etal., 2019). Africa has been targeted through the AFR100 (https://afr100.

org) to plant ~1millionkm2 of trees by 2030 (Bond et al 2019). Maintaining existing indigenous forest and indigenous forest restoration

is a win–win, maximising beneﬁts to biodiversity, adaptation and mitigation (Griscom etal., 2017; Watson etal., 2018; Lewis etal., 2019)

(high conﬁdence).

Yet many areas targeted by AFR100 erroneouslymark Africa’s open ecosystems (grasslands, savannas, shrublands) as degraded and

suitable for afforestation (Figure Box9.3.1; (Veldman etal., 2015; Bond etal., 2019) (high conﬁdence). These ecosystems are not degraded,

they are ancient ecosystems that evolved in the presence of disturbances (ﬁre/herbivory) (Maurin etal., 2014; Bond and Zaloumis, 2016;

Charles-Dominique etal., 2016). Afforestation prioritises carbon sequestration at the cost of biodiversity and other ecosystem services

(Veldman etal., 2015; Bond etal., 2019). Furthermore, it remains uncertain how much carbon can be sequestered as, compared to grassy

ecosystems, afforestation can reduce belowground carbon stores and increase aboveground carbon loss to ﬁre and drought (Yang etal.,

2019; Wigley etal., 2020b; Nuñez etal., 2021). Thus, afforested areas may store less carbon than ecosystems they replace (Dass etal.,

2018; Heilmayr etal., 2020). Afforestation would reduce livestock forage, ecotourism potential and water availability (Gray Emma and

Bond William, 2013; Anadón etal., 2014; Cao etal., 2016; Stafford etal., 2017; Du etal., 2021), and may reduce albedo thereby increasing

warming (Bright etal., 2015; Baldocchi and Penuelas, 2019).

Exotic tree species are often selected for planting (e.g., Pinus spp. or Eucalyptus spp.), but in parts of Africa, they have become invasive

(Zengeya, 2017; Witt etal., 2018), increasing ﬁre hazards and decreasing biodiversity and water resources (Nuñez etal., 2021) (high

conﬁdence). Negative impacts of afforestation on ecosystems are not restricted to plantations of exotic species; they extend to

inappropriate planting of native forest species (Slingsby etal., 2020).

(a)

Savannas at potential risk from afforestation

(b)

Antelope species diversity

Grassy biomes

at risk of

afforestation and

forest expansion

(c)

Cattle distribution

Antelope

species

richness

15–18

10–15

5–10

18–25

0–5

Cattle/km2

FigureBox9.3.1 | Many proposed tree planting plans in Africa present risks to biodiversity and livelihoods, because they are focused on

(a) naturally non-forested ecosystems like savannas, grasslands and shrublands which

(b) host uniquely adapted biodiversity and

(c) offer important ecosystem services like grazing which supports subsistence and commercial agriculture. Figure adapted from Veldman etal. (2015); Bond etal. (2019).

1342

Chapter 9 Africa

Regular, long-term monitoring of African freshwaters would improve

understanding of responses to climate change. General principles for this

type of monitoring were developed for Lake Tanganyika (Plisnier etal.,

2018) and could be applied to develop harmonised, regional monitoring

of African lakes, rivers and wetlands (Tamatamah and Mwedzi, 2020)

9.6.4.3 Marine and Coastal Ecosystems

Marine and coastal ecosystems such as mangroves, seagrass and

coral reefs provide storm protection and food security for coastal

communities (high conﬁdence) (IPCC, 2019d). Restoring reef systems

reduced wave height in Madagascar (Narayan etal., 2016), but there is

limited evidence for the efﬁcacy of coral reef restoration at large scales

with increased warming (Chapter3 Section3.6.3). Populations at risk

from storm surge and/or sea level rise coincide with areas of high

coastal EbA potential from Mozambique to Somalia, and coastlines

of the Gulf of Guinea, Gambia, Guinea-Bissau and Sierra Leone (Jones

etal., 2020). Understanding hotspots of EbA potential is particularly

important for west Africa with some of the highest levels of human

dependence on marine ecosystems at high risk from climate change

and large populations vulnerable to sea level rise (Sections9.9.3.1;

9.8.5.2; Selig etal., 2018; Trisos etal., 2020).

Marine protected areas (MPAs) can yield multiple adaptation beneﬁts,

such as buffering species from extinction and increasing ﬁsh stocks, as

well as storing large amounts of carbon (Edgar etal., 2014; Roberts

etal., 2017; Lovelock and Duarte, 2019). However, this potential of

MPAs will reach limits with increased warming (Roberts etal., 2017).

For example, MPAs cannot prevent coral bleaching at scale and mass

die-offs are well-described from MPAs following climate shocks (Bates

etal., 2019; Bruno etal., 2019). However, prioritising MPA coverage of

climate refugia, such as the Northern Mozambique Channel, may offer

some increased resilience (McClanahan etal., 2014).

9.7 Water

Much of Africa experiences very high hydrological variability in all

components of the water cycle, with important implications for people

and ecosystems. Most of the continent’s water is stored in groundwater

(660,000 km3), which is 20times more than the water stored in the

lakes and 100times more than the annual renewable water resources

(MacDonald etal., 2012). The accessible volume of groundwater via

wells and springs is smaller than these estimates (Xu et al., 2019).

Africa has 63 transboundary river basins (UNEP, 2010), 72 mapped

transboundary aquifers (Nijsten et al., 2018) and 33 transboundary

lakes (ILEC and UNEP, 2016), reﬂecting a highly water-connected and

interdependent socio-ecological system across countries, also extending

to the coastal areas of the continent (see Chapter 4 Section 4.1).

9.7.1 Observed Impacts from Climate Variability and

Climate Change

Climate impacts on water are occurring against a backdrop of

increasing temperatures and changes in rainfall, with increased

seasonal and interannual variability, droughts in some regions, and

increased frequency of heavy rainfall events (see Section9.5). In west

Africa, declines in river ﬂows have been attributed to declining rainfall

and increasing temperature, drought frequency and water demand

(Biao, 2017; Thompson etal., 2017; Descroix etal., 2018). In central

Africa, the Congo river demonstrates inter-decadal shifts but no long-

term trend (Mahe etal., 2013; Alsdorf etal., 2016). However, recently

observed falling water levels in its upper and middle reaches are

attributed to climate change (von Lossow, 2017).

A review of river ﬂow and lake level changes in 82 basins in eastern and

southern Africa regions for 1970–2010 showed mixed trends: 51% had

decreasing trends ranging from 10–49% and 11% increasing trends

ranging from 7–60% (Schäfer etal., 2015). However, in southern Africa

as a whole, river ﬂows have mostly decreased (high conﬁdence) (Dallas

and Rivers-Moore, 2014). In east Africa, large rivers such as the Tana

show increasing ﬂow (1941–2016) related to increased rainfall in the

highlands, with little inﬂuence of ﬂow regulation by a series of dams

(Langat etal., 2017). The Nile river basin has been experiencing a mainly

increasing rainfall trend upstream and decreasing trend downstream

(Onyutha etal., 2016). The observed changes are driven by a complex

coupling of changes in climate, land use and water demand.

Observed climate changes in Africa (see Section9.5) have led to changes

in river ﬂow and runoff (Dallas and Rivers-Moore, 2014; Wolski etal.,

2014) and high ﬂuctuations in lake levels (high conﬁdence) (Natugonza

etal., 2016; Ogutu-Ohwayo etal., 2016; Gownaris etal., 2018). Shallow

lakes respond dramatically to hydrological changes, for example, Lake

Chilwa has dried up completely nine times in the last century (Wilson,

2014), while Lake Chad shrunk by 90% between 1963 and 2000 (Gao

etal., 2011). However, recent analyses indicate that Lake Chad’s water

levels have been stable since 2000 due to inﬁlling from groundwater

resources (Buma et al., 2018; Pham-Duc et al., 2020). Other factors

such as deforestation and increased water use in upstream tributaries

also contribute to lake shrinking (Mvula etal., 2014). Water levels in

Kenya’s mostly shallow rift lakes have been rising since 2010, with some

exceeding historical record high levels (Schagerl and Renaut, 2016;

Olago etal., 2021). The recent 10-year rising trend is partly attributed to

increased rainfall and changing land uses (Onywere etal., 2012; Olago

et al., 2021). Changes in water level ﬂuctuations of 13 African lakes

have been positively correlated with primary and overall production

(Gownaris et al., 2018), and will have important consequences for

freshwater ecosystems and related ecosystem goods and services (see

Sections9.6.1.3; 9.8.5). Other effects of observed climate changes in

Africa include higher episodic groundwater recharge, particularly in

drylands, from heavy rainfall events that are in some cases related to

ENSO and the IOD (Taylor etal., 2013; Fischer and Knutti, 2016; Cuthbert

et al., 2019; Kotchoni et al., 2019; Myhre etal., 2019), reduced soil

moisture, more frequent and intense ﬂoods, more persistent and frequent

droughts (Douville etal., 2021) and the steady decline and projected

disappearance by 2040 of African tropical glaciers (see Section9.5.9).

The mixed signal in river ﬂow trends (increase/decrease/no change)

across Africa mirrors the results seen globally for runoff and streamﬂow

(see Chapter4 Section4.2.3). Hydrological extremes are, however, of

increasing concern. There has been an increase in drought frequency,

severity and spatial extent in recent decades. From 1900–2013, Africa

suffered the largest number of drought events globally and registered

1343

Africa Chapter 9

Box9.4 | African cities facing water scarcity

Many African cities will face increasing water scarcity under climate change (Grasham etal., 2019). The Cape Town and Dodoma cases

illustrate challenges for both surface and groundwater supply and what adaptation responses have been employed.

The Cape Town drought (2015–2018)

The Cape Town drought illustrates how a highly diverse African city and its citizens responded to protracted and unanticipated water

scarcity. Human-caused climate change made the reduced rainfall that caused the drought three times more likely (95% conﬁdence

interval 1.5–6) (Otto etal., 2018; Pascale etal., 2020; Doblas-Reyes et al., 2021). After three consecutive years of low precipitation,

Cape Town braced for a ‘Day Zero’ where large portions of the city would lose water supply (Cole etal., 2021a). The risk of Day Zero

was anticipated to cascade to affect risks to health, economic output and security (Simpson etal., 2021b). The case study highlights

the importance of communication, budgetary ﬂexibility, robust ﬁnancial buffers and insurance mechanisms, disaster planning,

intergovernmental cooperation, nature-based solutions, infrastructure transformations and equitable access for climate adaptation in

African cities facing water scarcity.

A substantial media campaign was launched to inform residents about the severity of the drought and urge water conservation (Booysen

etal., 2019; Hellberg, 2019; Ouweneel etal., 2020). Together with stringent demand management through higher water tariffs, this

communication campaign played an important role in reducing consumption from 540 to 280 litres per household per day (Booysen etal.,

2019; Simpson etal., 2019a). Revenue from water sales contributes 14% of Cape Town’s total revenue, making it the third-largest source

of ‘own’ revenue for the city (Simpson etal., 2019b). However, with an unprecedented reduction in water use, the municipal budget was

undermined (Simpson etal., 2020b). Collecting less revenue created a ﬁnancial shock as the city struggled to recover operating ﬁnance,

even while new capital requirements were needed for the development of expensive new water supply projects (Simpson etal., 2019b).

This ﬁnancial shock was compounded by the economic stress of poor agricultural and tourism performance brought about by the drought

(Shepherd, 2019; Simpson etal., 2021b). As wealthy residents invested in private, off-grid water supplies, the risk of reduced municipal

revenue collections from newly off-grid households aggregated with the risk of reduced tourism, increasing the risk to the reputation

of the incumbent administration (Simpson etal., 2021b). This demonstrates how a population cohort with a high response capability to

water scarcity can reduce risk while simultaneously increasing risks to the municipality and its capacity to provide water to vulnerable

residents (Simpson etal., 2020b). Given that city populations in Africa pay 5–7times more for water than the average price paid in the

USA or Europe (Adamu and Ndi, 2017; Lwasa etal., 2018), municipal ﬁnance needs to delink operating revenue from potential climate

shocks (see Box8.6).

The drought led the municipality to consider a broader diversity of water supply options, including groundwater (CoCT, 2019), developing

city-scale, slow-onset disaster planning (Cole etal., 2021a) and building an enhanced ‘relationship with water’ (CoCT, 2019; Madonsela

etal., 2019). This shift in approach is displayed in the recognition of nature-based solutions as a priority in water resilience-building

efforts (Rodina, 2019) and is signalled in Cape Town’s Water Strategy which aims to become a ‘water sensitive city’ that makes ‘optimal

use of stormwater and urban waterways for ﬂood control, aquifer recharge, water re-use and recreation’ (CoCT, 2019).

The drought required cooperation between multiple spheres of government, and the management of a broad range of stakeholders and

political entities (Nhamo and Agyepong Adelaide, 2019; Cole etal., 2021a). The case highlights how a lack of coordination between

essential organs of state and political entities can reduce response efﬁcacy (Rodina, 2019). Despite signiﬁcant investments in water

security by public and private entities, one-quarter of Cape Town’s population remains in persistent conditions of water stress, emphasising

the challenge and importance of inclusive solutions that address the persistent social and economic stressors which affect vulnerability to

water scarcity (Enqvist and Ziervogel, 2019).

Sustaining intensive groundwater use in a dryland city under climate change: Dodoma, Tanzania

Since 1954, the Makutapora wellﬁeld in semi-arid, central Tanzania has supplied safe water to the city of Dodoma. Substantial rises

in wellﬁeld pumping and population growth have increased freshwater demand in Dodoma and dependence upon the Makutapora

wellﬁeld, currently the sole perennial source of piped water to the city. Yet, there is high uncertainty of groundwater recharge rates

(Nkotagu, 1996; Taylor etal., 2013) which rely on intense seasonal rainfall associated with the ENSO and the IOD modes of climate

variability (e.g., 2 to 7years) to contribute disproportionately to recharge (Taylor etal., 2013; Kolusu etal., 2019).

1344

Chapter 9 Africa

Deﬁning a sustainable pumping rate for the Makutapora wellﬁeld is complicated by the variable and episodic nature of groundwater

replenishment in this dryland environment. For example, groundwater recharge during the 1997/1998 El Niño event, the strongest El Niño

event of the 20th century, accounted for nearly 20% of all of the recharge received from 1955–2010 (Taylor etal., 2013), highlighting the

vital role interannual groundwater storage plays in enabling adaptation to climate variability and change in drylands. The disproportionate

contribution of intense seasonal rainfalls to the replenishment of the Makutapora wellﬁeld, consistent with observations from across

sub-Saharan Africa (Cuthbert etal., 2019), suggests that groundwater in drylands are currently naturally resilient to climate change.

However, it remains unclear whether climate change will strengthen or weaken the inﬂuence of ENSO and IOD on rainfall (Brown etal.,

2020) and thereby affect the predictability of groundwater recharge.

As freshwater demand in Tanzania’s rapidly growing capital is projected to increase substantially in the coming decades, questions

remain as to whether the capacity of the Makutapora wellﬁeld can meet some or all of this demand. Nature-based solutions to improve

the resilience of wellﬁeld abstraction to increased pumpage and climate change include managed aquifer recharge (MAR). The sharing

of general lessons learned from other cities in dryland Africa employing MAR, such as Windhoek in Namibia (Murray etal., 2018), could

prove invaluable.

Box9.4 (continued)

the second largest number of people affected after Asia (Masih etal.,

2014). The likelihood of recent severe climate conditions such as the

multi-year Cape Town drought has increased due to human-caused

climate change (Otto etal., 2018; Pascale etal., 2020; see Box 9.4),

and regional and urban ﬂoods (Yuan etal., 2018; Tiitmamer, 2020) and

droughts (Funk etal., 2018b; Siderius etal., 2018; Uhe etal., 2018) are

expected to increase.

However, between 2010–2020 more people across Africa have been

impacted by ﬂoods (e.g., related to Cyclone Idai in March 2019)

compared to droughts (Lumbroso, 2020). Coastal cities are vulnerable

to ﬂoods related to rainfall and sea level rise (Musa etal., 2014), as

exempliﬁed by the ﬂood disasters experienced in the Niger delta in 2012

which displaced more than 3 million people and destroyed schools,

clinics, markets and electricity installations (Amadi and Ogonor, 2015).

From 2000–2015, the proportion of people exposed to ﬂoods grew by

20–24%, mostly in Africa and Asia, with Mozambique and multiple

countries in West Africa estimated to have had the proportion of their

populations exposed to ﬂooding increase by more than 50% (Tellman

etal., 2021) and these numbers will increase under climate change.

Sectoral impacts from ﬂooding within Africa and globally are further

elaborated on in Sections9.8.2 and 9.8.5.1, Table9.3 and Chapter 4

Section4.3.

9.7.2 Projected Risks and Vulnerability

9.7.2.1 Projected Risks

By 2050, up to 921million additional people in sub-Saharan Africa

could be exposed to climate change-related water stress, while up

to 459million could experience reduced exposure (Dickerson etal.,

2021). This large variance in numbers and direction of change is

related to uncertainties in climate models and non-climate factors

like population growth and water withdrawals (Dickerson et al.,

2021). The baseline for most of the projected risks presented here

is 1971–2000.

In west Africa, signiﬁcant spatial variability in river ﬂow is projected in

the upper reaches of several rivers, with no clear pattern overall (Roudier

etal., 2014) and large uncertainties in estimations of change in runoff

(Roudier etal., 2014; Bodian etal., 2018). In some higher altitude regions,

like the Niger Inland Delta in west Africa, river ﬂows and water levels are

expected to increase (medium conﬁdence) (Aich etal., 2014; Thompson

etal., 2017). In the Lower Niger Basin, combined average annual rainfall

and erosivity for all the climatic models in all scenarios shows increasing

rainfall amounts are projected to result in an increasing average change

in rainfall-runoff erosivity of about 14%, 19% and 24% for the 2030s,

2050s and 2070s, with concomitant increase in soil loss of 12%, 19%

and 21% (Amanambu etal., 2019). In the Volta River system, increasing

wet season river ﬂows (+36% by 2090s) and Volta lake outﬂow (+5%

by 2090s) are anticipated under RCP8.5 (medium conﬁdence) (Awotwi

A etal., 2015; Jin et al., 2018). In the Volta River basin, compared to

1976–2005, drought events are projected to increase by 1.2 events per

decade at around 2°C to 1.6 events per decade at around 2.5°C global

warming, and drought area extent is projected to increase by 24% to

34% (Oguntunde et al., 2017). In central Africa, runoff in the Congo

river system may increase by up to 50% (RCP8.5), especially in the wet

season, enhancing ﬂood risks in the entire Congo Basin, particularly

in the central and western parts (CSC, 2013). Average river ﬂows are

expected to increase in most parts of central Africa, with expected

increases in total potential hydropower production (Ludwig etal., 2013),

but see Box 9.5.

In north Africa, in the upper White Nile basin, Olaka etal. (2019)

project a 25% and 5–10% (RCP4.5) increase in the intensiﬁcation of

future annual rainfall in the eastern and western parts of the Lake

Victoria Basin, respectively, with corresponding variability in future

river discharge ranging from 5% to 26%. In the upper Blue Nile basin,

models also indicate up to 15% increase in runoffs in wet season and

up to −24% decrease in dry season during 2021–2040 (RCP8.5) (Ayele

etal., 2016; Siam and Eltahir, 2017; Meresa and Gatachew, 2018). The

increase of precipitation in the wet season indicates a higher possibility

of ﬂash ﬂoods, while decreased runoffs in dry season further intensify

existing shortage of irrigation water demand (Ayele etal., 2016; Siam

1345

Africa Chapter 9

and Eltahir, 2017; Meresa and Gatachew, 2018). The annual ﬂow and

revenues from hydropower production and irrigated agriculture of the

Blue Nile River at Khartoum are projected to increase under maximum

but are expected to decrease under minimum and median projected

changes in streamﬂow for 2041–2070 and 2071–2100, respectively

(Tariku etal., 2021). The Middle Draa valley in Morocco is expected

to experience more severe droughts and the estimation of the water

balance suggests a lack of supply in the future (Karmaoui etal., 2016).

In east Africa, Liwenga et al. (2015) project warmer and wetter

conditions in the Great Ruaha River region and with increasing

seasonal variation and extremes towards the end of the century. A

similar observation is made for the River Pangani, with mean river

ﬂow being about 10% higher in the 2050s relative to the 1980–1999

period, associated with a 16–18% increase in rainfall in its upper

catchment (Kishiwa etal., 2018). However, at more local scales, the

projections cover a range of slight declines to signiﬁcant increases

in mean annual rainfall amounts (Gulacha and Mulungu, 2017). In

the Tana River basin in Kenya, water yield is projected to increase

progressively under RCP4.5 and RCP8.5 relative to the baseline period

1983–2011 but is characterised by distinct spatial heterogeneity

(Muthuwatta etal., 2018).

In southern Africa, reductions in rainfall over the Limpopo and Zambezi

river basins under 1.5°C and 2°C global warming could have adverse

impacts on hydropower generation, irrigation, tourism, agriculture and

ecosystems (Figure Box9.5.1) (Maúre etal., 2018), although model

projections of strong early summer drying trends remain uncertain

(Munday and Washington, 2019).

Changes in the amplitude, timing and frequency of extreme events

such as droughts and ﬂoods will continue to affect lake levels, rates of

river discharge and runoff and groundwater recharge (high conﬁdence)

(Gownaris etal., 2016; Darko etal., 2019), but with disparate effects

at regional, basin and sub-basin scales, and at seasonal, annual and

longer timescales. The increased frequency of extreme rainfall events

under climate change (Myhre et al., 2019) is projected to amplify

groundwater recharge in drylands (Jasechko and Taylor, 2015; Cuthbert

etal., 2019). However, declining trends in rainfall and snowfall in some

areas of north Africa (Donat etal., 2014b) are projected to continue

in a warming world (Seif-Ennasr etal., 2016), restricting groundwater

recharge from meltwater ﬂows, exacerbating the salinisation and

depletion of groundwater (Hamed etal., 2018) and increasing the risk

of reduced soil moisture (Petrova etal., 2018) in this region where

groundwater abstraction is greatest (Wada etal., 2014).

Lake surface temperatures across Africa are expected to rise in tandem

with increasing global warming. Lake heatwaves, periods of extreme

warm lake surface water temperature, are projected to become hotter

and longer (Figure9.21), with heatwaves more than 300days per year

in many lakes for global warming of 4.2°C (Woolway et al., 2021).

Lake warming is expected to have adverse consequences for aquatic

biodiversity, habitats, water quality and disruption of current lake physical

processes and circulation patterns (Kraemer etal., 2021).

Climate change is projected to increase the intensity of lake heatwaves across Africa

Temperature

°C per decade

(a) Under 1.8°C global warming (RCP2.6 in 2070–2099)

(b) Under 4.2°C global warming (RCP8.5 in 2070–2099)

0.5

0.25

0.1

No data

Not significant

Average intensity

of future lake heatwaves

1.89–2.27°C

2.27–2.69°C

2.69–2.92°C

2.92–3.21°C

3.21–3.69°C

3.69–3.97°C

3.97–4.54°C

Figure9.21 | Climate change is projected to increase the intensity of lake heatwaves across Africa. Projected increases in average intensity of lake heatwaves (°C)

under

(a) 1.8°C global warming (RCP2.6 in 2070–2099) and

(b) 4.2°C global warming (RCP8.5 in 2070–2099). Each lake is represented by a point. Data were extracted from Woolway etal. (2021).

1346

Chapter 9 Africa

9.7.2.2 Vulnerability

Climate change is projected to reduce water availability and increase the

extent of water scarcity (Mekonnen and Hoekstra, 2016), particularly in

southern and north Africa, while other regions will be more affected by

increased hydrological variability over temporally short to interannual

time scales (see Section9.6.2). African countries are considered to be

particularly at risk due to their underlying vulnerabilities (IPCC, 2014b;

UNESCO and UN-Water, 2020), yet the continents’ water resources

are still inadequately quantiﬁed and modelled (Müller Schmied etal.,

2016; Reinecke etal., 2019), constraining sustainable management

practices (Cuthbert etal., 2019; Hughes, 2019).

Hydrological ﬂuctuations are associated with drought, ﬂood and

cyclone events which have had multi-sector impacts across Africa

(Siderius et al., 2021; see Chapter 4 Sections 4.3; 4.5), including:

reduced crop production (D’Odorico et al., 2018), migration and

displacement (Siam and Eltahir, 2017; IDMC, 2018), food insecurity

and extensive livestock deaths (Nhamo etal., 2018), electricity outages

(Gannon et al., 2018), increased incidence of cholera (Olago etal.,

2007; Sorensen etal., 2015; Houéménou etal., 2020) and increased

groundwater abstraction amplifying the risk of saline intrusion from

sea level rise (Hamed etal., 2018; Ouhamdouch etal., 2019).

The literature shows signiﬁcant gender-differentiated vulnerability and

intersectional vulnerability to climate change impacts on water in Africa

(Fleifel etal., 2019; Grasham etal., 2019; Mackinnon etal., 2019; Dickin

etal., 2020; Lund Schlamovitz and Becker, 2020), although studies are

generally lacking in northern Africa (Daoud, 2021). Women and girls

are, in most cases, more impacted than men and boys by customary

water practices, as adult females are the primary water collectors

(46% in Liberia to 90% in Cote d’Ivoire), while more female than male

children are associated with water collection (62% compared with

38%, respectively) (Graham etal., 2016). Women and girls face barriers

toward accessing basic sanitation and hygiene resources, and 71% of

studies reported a negative health outcome, reﬂecting a water–gender–

health nexus (Pouramin etal., 2020). These differential vulnerabilities are

crucial for informing adaptation, but are still relatively under-researched,

more so for the urban poor than rural communities (Grasham et al.,

2019; Mackinnon etal., 2019; Lund Schlamovitz and Becker, 2020).

9.7.3 Water Adaptation Options and Their Feasibility

9.7.3.1 Reducing Risk Through a Systems Approach to Water

Resources Planning and Management

An integrated systems and risk-based approach to the design and

management of water resources at scale is generally accepted as a

practical and viable way of underpinning the resilience of water systems

to climate change and human pressures (Duffy, 2012; García etal., 2014).

Such approaches confer multiple beneﬁts to nature and society at scale

and enhance efﬁciency gains through technology and management

improvements, but their full implementation has not yet been realised

(Weinzierl and Schilling, 2013; McDonald etal., 2014; UN Environment,

2019). Drylands are particularly singled out as ignored areas that require

integrated water resource management approaches (Section 9.3.1;

Stringer etal., 2021). Appropriate ecosystem-based adaptations that are

applicable at scale should be identiﬁed and strongly embedded in these

approaches to deliver multiple beneﬁts while maintaining the integrity of

ecosystems and biodiversity (UN Environment, 2019; see Sections9.6.4;

9.8.5; Box4.6). Furthermore, adaptation options are often inﬂuenced or

constrained by institutions, regulation, availability, distribution, price and

technologies (McCarl etal., 2016). Thus, institutional capacity to manage

complex water supply systems under rapidly increasing demand and

climate change stress is critical in achieving water security for African

cities, particularly as cities become more dependent on alternative and

distant water sources (Padowski etal., 2016).

9.7.3.2 Adopting Nexus Lenses

The water–energy–food (WEF) nexus explicitly recognises the strong

interdependencies of these three sectors and their high levels of

exposure to climate change (Zografos etal., 2014; Dottori etal., 2018;

see Box9.5). With increasing societal demands on more variable water

resources under climate change, an intensiﬁcation of WEF competition

and trade-offs are projected (D’Odorico et al., 2018; Dottori et al.,

2018). Other interacting factors, for example, the increasing number

of transnational investments in land resources can lead to localised

increased competition for water resources (Messerli et al., 2014;

Breu et al., 2016; Chiarelli etal., 2016). Understanding such nexus

interlinkages can help characterise risks to water resource security,

identify co-beneﬁts and clarify the range of multi-sectoral actors

involved in and affected by development decisions (Kyriakarakos etal.,

2020). Major barriers and entry points for greater integration include

coordination of horizontal policy and integration of climate change

adaptation actions (England etal., 2018), capturing the scarcity values

of water and energy embedded in food/energy products (Allan etal.,

2015), and inclusion of community-based organisations such as

water resource user associations (Villamayor-Tomas etal., 2015) and

agricultural cooperatives (Kyriakarakos etal., 2020).

9.7.3.3 Climate-prooﬁng Water Infrastructure

While natural variability in the hydrological cycle has always been

considered by water resources planners and engineers (Müller

Schmied etal., 2016; Muller, 2018), many countries will have to take

into consideration the range of historically unprecedented extremes

expected in the future. Increasingly, the provision of urban water

security is dependent on the functioning of complex bulk water

infrastructure systems consisting of dams, inter-basin transfers,

pipelines, pump stations, water treatment plants and distribution

networks (McDonald etal., 2014). Risk-based studies on the potential

climate change risks for water security show that there are beneﬁts

when risks are reduced at the tails of the distribution—ﬂoods and

droughts—even if there is little beneﬁt in terms of changes in the

mean (Arndt et al., 2019). When risk is taken into account in an

integrated (national) bulk water infrastructure supply system, the

overall impact of climate change on the average availability of water to

meet current and future demands is signiﬁcantly reduced (Cullis etal.,

2015). Further, stemming leakages and enhancing efﬁciency through

technology and management improvements is important in building

climate-resilient water conveyance systems (UN Environment, 2019).

African cities could leap-frog through the development phases to

1347

Africa Chapter 9

Box9.5 | Water–energy–food nexus

The interdependencies in the water-energy-food (WEF) nexus, coupled with its high exposure to climate change, amplify WEF risks. Risks

can be transmitted from one WEF sector to the other two with cascading risks to human health, cities and infrastructure (Conway etal.,

2015; Mpandeli etal., 2018; Nhamo etal., 2018; Yang and Wi, 2018; Ding etal., 2019; Simpson etal., 2021b). For example, increasing

demand for water for agricultural and energy production is driving an increasing competition over water resources between food and

energy industries which, among other effects, compromises the nutritional needs of local populations (Zografos etal., 2014; Dottori etal.,

2018). Drought events, such as in southern Africa during the 2015/16 El Niño, have been associated with major multi-sector impacts on

food security (over 40million food-insecure people and extensive livestock deaths) and reduced energy security through disruption to

hydropower generation (associated in Zambia with the lowest rate of real economic growth in over 15years) (Nhamo etal., 2018). The

WEF nexus of the Nile and Zambezi river basins, which include many of Africa’s largest existing hydropower dams, have received the

most attention. In these two regions, where socioeconomic development is already driving up demand, projections indicate that water

scarcity may be exacerbated by drying (Munday and Washington, 2019) and increased ﬂow variability (Siam and Eltahir, 2017). However,

for Africa more widely, very few studies fully integrate all three WEF nexus sectors and rarely include an explicit focus on climate change.

In Africa, the climate risks that the water, energy and food sectors will face in the future are heavily inﬂuenced by the infrastructure

decisions that governments make in the near term. The AU’s Programme for Infrastructure Development (PIDA), along with other national

energy plans (jointly referred to as PIDA+), aim to increase hydropower capacity nearly six-fold, irrigation capacity by over 60% and

hydropower storage capacity by over 80% in major African river basins (Cervigni etal., 2015). The vast majority of hydropower additions

would occur in the Congo, Niger, Nile and Zambezi river basins, and the majority of the irrigation capacity additions would occur in the

Niger, Nile and Zambezi River basins (Figure Box9.5.1; Huber-Lee etal., 2015).

Climate change risk to the productivity of this rapidly expanding hydropower and irrigation infrastructure compound the overall WEF

nexus risk. Future levels of rainfall, evaporation and runoff will have a substantial impact on hydropower and irrigation production.

Climate models disagree on whether climates will become wetter or dryer in each river basin. Cervigni etal. (2015) modelled revenues

from the sale of hydroelectricity and irrigated crops in major African river basins under different climate scenarios between 2015 and

2050 (Figure Box9.5.1). The study found that hydropower revenues in the driest climate scenarios could be 58% lower in the Zambezi

River basin, 30% lower in the Orange basin and 7% lower in the Congo basin relative to a scenario with current climate conditions.

Hydropower revenues in the wettest climate scenario could be more than 20% higher in the Zambezi river basin and 50% higher in the

Orange basin. The biggest risk to the production of irrigated crops is in the eastern Nile where irrigation revenue could be 34% lower in

the driest scenario and 11% higher in the wettest than in a scenario without climate change (Cervigni etal., 2015).

Studies have used the river basin as a unit of analysis and adopted sophisticated techniques to assess and present trade-offs between

competing uses. For example, Yang and Wi (2018) consider the WEF nexus in the Great Ruaha tributary of the Ruﬁji River in Tanzania

motivated by an observed decrease in streamﬂow during the dry season in the 1990s, but without an explicit focus on climate. Yang and

Wi (2018) show sensitivity of water availability for irrigated crop production to warming, and sensitivity of hydropower generation and

ecosystem health to changes in precipitation and dam development. Understanding of WEF nexus interlinkages can help characterise

risks and identify entry points and the relevant institutional levels for cross-sectoral climate change adaptation actions (England etal.,

2018). An integrated response can be enhanced through the inclusion of community-based organisations, such as water resource user

associations and the wide range of other multi-sectoral actors involved in and affected by development decisions. Capturing the scarcity

values of water and energy embedded in food and other products can help identify the co-beneﬁts and costs of integrated adaptation

(Allan etal., 2015).

achieve a water sensitive city ideal, reaping beneﬁts such as improved

liveability, reduced ﬂooding impacts, safe water and overall lower

net energy requirements and avoid making the mistakes developed

countries’ cities have made (Fisher-Jeffes etal., 2017) (Brodnik etal.,

2018). However, the challenge of large proportions of the population

lacking access to even basic water supply and sanitation infrastructure

(Armitage et al., 2014) must be simultaneously and effectively

addressed, particularly in light of other major exacerbating factors, like

the COVID-19 pandemic (Section9.11.5).

9.7.3.4 Decision Support Tools for Managing Complex Water

Systems

Many studies in Africa use the river basin as a unit of analysis at scale

and adopt sophisticated model-based techniques to assess climate

change impacts on hydrology under different climate and development

scenarios, thereby presenting trade-offs between competing uses such

as hydropower generation, irrigation and ecosystem requirements

(Section 9.12.1; Yang and Wi, 2018; Ahmed, 2020). However, longer

1348

Chapter 9 Africa

Existing +

planned

hydropower

93,848

Megawatts

Existing +

planned

irrigation

12,620,558

Hectars

Nile (Equatorial)

Nile (Eastern)

Zambezi

Congo

Niger

Nile

(Equatorial) Zambezi Congo Niger Senegal

0.29

0.03

0.25

0.43

0.34

-0.18

0.52

-0.25

0.46 0.52 0.38

0.43 0.31

0.74

-0.28

weak strongnegative

63 existing

79 planned (2015–2050)

Hydropower

3,052–39,000

5–255

Capacity (Megawatts)

256–750

751–1,600

1,601–3,050

150

200

100

150

200

100

Existing hydropower

13,774 MW

Planned hydropower

80,074 MW

Existing irrigation

7,765,688 Ha

Planned irrigation

4,854,870 Ha

Congo

44,402

Nile

21,392

Niger

4,667

Zambezi

8,204

Zambezi

4,827

Nile

6,220,270

Senegal

754,460

Niger

1,791,457

Nile

772,350

Zambezi

668,542

Volta

177,389

Senegal

255,327

Niger

738,011

Billions US$Billions US$

Hydropower plants clustered within the same areas, are likely to

experience similar rainfall and run-off patterns, increasing the risk

that neighbouring states will experience concurrent drought-induced

hydropower shortages.

When historical annual river flows are weakly or negatively

correlated, power trade between basins will be more effective in

managing the risk of shortages than power trade between those

experiencing similar patterns.

Approximate areas

of shared rainfall

variability &

concentrated

hydropower

capacity

Zambezi

Niger

Congo

Nile

(Eastern)

Volta

Senegal

Orange

Nile

(Equatorial)

Zambezi NigerCongo Nile

(Eastern)

Volta SenegalNile

(Equatorial)

Zambezi NigerCongo Nile

(Eastern)

Volta SenegalNile

(Equatorial)

Min. revenue

Max. revenue

Net present value in 2012

(without climate change)

Forecast revenues from planned hydropower

under different climate scenarios (2015–2050)

Forecast revenues from planned irrigation

under different climate scenarios (2015–2050)

Highest risk to

hydropower output is

in the Zambezi, where

the driest scenarios

would see a 58%

reduction in revenues

relative to a scenario

without climate change

Highest risk to

production of irrigated

crops is in the

Eastern Nile, where

irrigation revenue

could be 34% lower in

the driest scenario

than the baseline

scenario

Correlation of historical

annual river flows

(d)(c)

(f)(e)

Climate risks to hydropower and irrigation in Africa

(b)(a) Distribution of hydropower plants within 7 major river basins

Box9.5 (continued)

1349

Africa Chapter 9

FigureBox9.5.1 | Climate risks to hydropower and irrigation in Africa.

(a) The map shows the location and size of existing (blue) and planned (orange) hydropower plants in African governments’ infrastructure expansion plans, 2015–2050.

(b) Matrix shows historical correlations in annual river ﬂows between some of the major river basins indicating risk of hydropower shortages where correlations are higher.

(c, e) Existing and planned hydropower and irrigation are indicated in charts. Dark blue shows forecasted revenues from 2015–2050 of existing hydropower and irrigation in

major African river basins in a scenario without further climate change (i.e., based on historical data). Orange in charts (c, e) shows the expected increase in hydropower and

irrigation revenues as new hydropower and irrigation infrastructure is added based on planned infrastructure development (PIDA+) in a scenario without climate change.

(d, f) The bar graphs show the forecast revenues for hydropower and irrigation infrastructure in each river basin under 121 different climate scenarios from 2015–2050,

highlighting risk to revenues from high variability in river discharge due to climate change. In river basins with a wide range of potential river ﬂow outcomes due to climate

change, such as the eastern Nile and Zambezi, there is substantial uncertainty around revenue forecasts and potential for large reductions in future revenue. Hydropower

revenues refer to net present value of hydroelectricity produced in each river basin over the period 2015–2050, and irrigation revenues refer to the crop revenues per

hectare for each crop multiplied by the number of hectares of each crop across the basin. All ﬁgures are estimates of the net present value of revenues, using a discount

rate of 3%, and are in 2012 USD billions. The 121 potential climate futures were derived using different General Circulation Models (GCMs), Representative Concentration

Pathways (RCPs), and downscaling methods. IPCC AR4 and AR5 provided data from 22 and 23 GCMs, respectively. These were evaluated across two or three emissions

pathways, including RCP4.5 and RCP8.5. The Bias Corrected Spatial Disaggregation method of downscaling was then used to derive 99 potential climate futures. An

additional 22 climate futures (11 GCMs driven by the RCP4.5 and RCP8.5 emissions pathways) were produced using the Empirical Statistical Downscaling Methods

developed at the Climate Systems Analysis Group at the University of Cape Town. Data sourced from Cervigni etal. (2015).

Box9.5 (continued)

(multi-decadal) hydrological datasets and model improvements

are required (Taye etal., 2015), and models should incorporate the

quantiﬁcation of the wider beneﬁts, risks and political opportunities

arising from reservoir development to better inform decision makers

to achieve a higher level of (transboundary) cooperation (Digna etal.,

2016; Nijsten et al., 2018). Collaboration between scientists and

policymakers to address the complexity of decision making under

uncertainty (Steynor etal., 2016) (Pienaar and Hughes, 2017), coupled

with community involvement in participatory scenario development and

participatory GIS to aid in collaborative planning that is context speciﬁc

(Muhati etal., 2018; Álvarez Larrain and McCall, 2019) are powerful

tools for more beneﬁcial adaptive and resilience-building actions.

9.7.3.5 Other Adaptation Options

Climate change is projected to increase dependence upon groundwater

withdrawals in most parts of Africa as an adaptive strategy to ampliﬁed

variability in precipitation and surface water resources, highlighting

the need for conjunctive surface-groundwater management and

rainwater harvesting (Cobbing and Hiller, 2019; Taylor etal., 2019).

Alternative water supply options such as desalination, managed

aquifer recharge, stormwater harvesting and re-use (direct and

indirect, potable and non-potable), all require signiﬁcant amounts of

energy and are complex to operate and maintain. A failure to provide a

source of reliable energy and the capacity to implement, maintain and

operate these systems is a signiﬁcant contributor to water scarcity risks

in Africa (Muller and Wright, 2016). Soft adaptation options include

increasing water use efﬁciency, changing agricultural practices, more

appropriate water pricing (Olmstead, 2014) and enhancing capacity

to tackle groundwater overexploitation (Kuper etal., 2016), among

others (see Section9.10.2.4 and Chapter4 Sections4.6 and 4.7).

9.7.3.6 Mainstreaming Gender Across all Adaptation Options

Gender is important in building resilience and adaptation pathways to

global environmental change (Ravera etal., 2016). It is well-established

that women, in most societies, have accumulated considerable knowledge

about water resources, including location, quality and storage methods

because they are primarily responsible for the management of water for

household water supply, sanitation and health, and for productive uses

in subsistence agriculture (UN-Water, 2006). As gender-differentiated

relationships are complex, adaptation should take into account

intersectional differences such as homeownership, employment and

age (Harris etal., 2016), educational, infrastructural and programmatic

interventions (Pouramin etal., 2020), aspects of protection and safety

(Mackinnon etal., 2019), barriers to adaptation and gendered differences

in the choice of adaptation measures (Mersha and Van Laerhoven, 2016),

the complex power dynamics of existing social and political relations

(Djoudi etal., 2016; Rao etal., 2017), and inclusion and empowerment

of women in the management of environmental resources (Makina and

Moyo, 2016). Incorporation of gender and water inequities into climate

change adaptation would have a signiﬁcant impact on achieving the

SDGs (particularly 1, 3, 4, 5 and 6), while failure to incorporate gender

will undermine adaptation efforts (Bunce and Ford, 2015; Fleifel etal.,

2019; Pouramin etal., 2020).

9.8 Food Systems

Ideally, a systems approach (Ericksen, 2008; Rosenzweig etal., 2020)

could be used to assess how global environmental changes affect

the food sector in Africa, emphasising the complex interactions that

exist within the components of the food supply system, including its

enabling socioeconomic and biophysical environment (Ingram, 2011;

Foran etal., 2014; Tendall etal., 2015), and how food is connected

to other critical systems such as energy, water and transportation

(Albrecht etal., 2018; see Box 9.5). Production will not be the only

aspect of food security that is impacted by climate change. Processing,

storage, distribution and consumption will also be affected. Access

to healthy and adequate food in the face of climate change requires

resilience across these components of the food system (Adenle etal.,

2017). However, most studies on climate change impacts on food in

Africa are heavily focused on production only. A signiﬁcant knowledge

gap, therefore, exists around the complex ways in which climate

1350

Chapter 9 Africa

change will interact with broader components of African food systems,

and strategies for making these systems more resilient, particularly

in a context of rapid population growth and urbanisation across the

continent (Adenle etal., 2017; Schmitt Olabisi etal., 2018).

9.8.1 Vulnerability to Observed and Projected Impacts

from Climate Change

Agricultural activities are mainly rainfed and subsistence across Africa.

The dominant farming system is mixed cereal–livestock (Thornton and

Herrero, 2015; Nematchoua etal., 2019), with pastoral systems in east

Africa, and commercial livestock and crop systems also representing a

signiﬁcant proportion of the food system in southern Africa (Thornton

and Herrero, 2015). Many African regions are vulnerable to food

insecurity, facing dwindling food production, food access, stocks and

income due to low adaptive capacity (Evariste etal., 2018; Fuller etal.,

2018; Bang etal., 2019; Gebre and Rahut, 2021).

Across regions with food systems highly vulnerable to climate change,

female farmers, cocoa farmers, pastoralists, plantain farmers, coastal

zone communities, rural households and forest communities in central

Africa indicate higher vulnerability (Chia etal., 2016; Schut etal., 2016;

Nematchoua et al., 2019). Their vulnerability is multi-dimensional

and affected by low adaptive capacity, location, livelihood system,

socioeconomic status, gender, age and ethnicity (Perez et al., 2015;

Weston etal., 2015; Gebre and Rahut, 2021; see also Box9.1).

Across Africa, including west Africa, adverse climate conditions for

agricultural and pastoral livelihoods have contributed to rural to urban

migration patterns and migration among African regions (see Box9.8;

Baudoin et al., 2014; Abbas, 2017; Gemenne and Blocher, 2017b).

Rural to urban migration may increase vulnerability of migrants

through exposure to additional risks, including food insecurity (Amadi

and Ogonor, 2015; Abbas, 2017). In general, west African countries

are characterised by the poor adaptive capacity of rural households

(Douxchamps etal., 2015; Dumenu and Obeng, 2016).

In north Africa, livelihoods and economies are strongly dependent

on agriculture. Pressure on water demand due to climate change

and variability is threatening income, development processes and

food security in the region (high conﬁdence) (Mohmmed etal., 2018;

Khedr, 2019). Increased temperatures and droughts have enhanced the

vulnerability of the irrigation sector (Verner etal., 2018; İlseven etal.,

2019), and the combined effect of these hazards negatively affects

crop and animal production (Mohmmed et al., 2018; Verner et al.,

2018). For example, dairy farms in Tunisia are experiencing warmer

temperatures above the thermoneutral zone of cows for more than

5months each year, reducing production efﬁciency and resulting in

signiﬁcant economic losses (Amamou etal., 2018).

Non-climatic stressors aggravate food insecurity in many parts of

the continent, including lack of access to production inputs and land,

lack of education and limited income sources, with adverse climate

impacts on agriculture reducing education attainment for children

(Section9.11.1.2; Evariste etal., 2018; Fuller etal., 2018). Geographic

and social isolation is another type of social vulnerability, especially

for pastoralist communities in east and southern Africa (Sonwa etal.,

2017; Basupi etal., 2019). Rural communities often have poor transport

networks, limited access to markets or information and fewer livelihood

alternatives, and are less able to be informed of risks or be assisted in the

event of extreme climate events (Sonwa etal., 2017; Basupi etal., 2019).

Extreme climate events have been key drivers in rising acute food

insecurity and malnutrition of millions of people requiring humanitarian

assistance in Africa (high conﬁdence). Between 2015 and 2019, an

estimated 45.1 million people in the Horn of Africa and 62 million

people in eastern and southern Africa required humanitarian assistance

due to climate-related food emergencies. Children and pregnant women

experience disproportionately greater adverse health and nutrition

impacts (very high conﬁdence) (Gebremeskel Haile et al., 2019; see

Chapter7 Section7.2.4).

Future climate warming is projected to have a substantial adverse

impact on food security in Africa and is anticipated to coincide with low

adaptive capacity as climate change intensiﬁes other anthropogenic

stressors, as 85% of Africa’s poor live in rural areas and mostly depend

on agriculture for their livelihoods (Adams, 2018; Mahmood et al.,

2019). This highlights the need to prioritise innovative measures for

reducing vulnerabilities in African food systems (Fuller etal., 2018;

Mahmood etal., 2019).

Climate change impacts could increase the global number of people

at risk of hunger in 2050 by 8million under a scenario of sustainable

development (SSP1) and 80 million under a scenario of reduced

international cooperation and low environmental protection (SSP3),

with populations concentrated in sub-Saharan Africa, south Asia and

central America (see Chapter5 Sections 5.2.2; 5.4.2; 5.4.3). Global

climate impacts on food availability are expected to lead to higher food

prices, increasing the risk of hunger for people in African countries,

and slowing progress towards eradicating child undernutrition and

malnutrition in all its forms (see Chapter7 Section7.4).

9.8.2 Observed Impacts and Projected Risks to Crops

and Livestock

9.8.2.1 Observed Impacts and Projected Risks for Staple Crops

Climate change is already negatively impacting crop production and

slowing productivity growth in Africa (high conﬁdence) (Iizumi etal.,

2018; Ray etal., 2019; Sultan etal., 2019; Ortiz-Bobea etal., 2021).

Climate change has reduced total agricultural productivity growth in

Africa by 34% since 1961, more than in any other region (Ortiz-Bobea

etal., 2021). Maize yields have decreased 5.8% and wheat yields 2.3%,

on average, in sub-Saharan Africa due to climate change in the period

1974–2008 (Ray etal., 2019). Overall, climate change has decreased

total food calories across all crops in sub-Saharan Africa by 1.4% on

average compared to a no climate change counterfactual since 1970,

with up to 10% reductions in Ghana and Zimbabwe (Ray etal., 2019).

Farmers perceive a wide variety of climate threats to crop production

including droughts, precipitation variability, a delayed onset and overall

reductions in early growing season rainfall and excess heat (Rankoana,

1351

Africa Chapter 9

2016a; Elum etal., 2017; Kichamu et al., 2017; Alvar-Beltrán etal.,

2020). Farmers attribute these perceived changes as a major driver

of yield losses (Ayanlade and Jegede, 2016; see Section9.4.5). Over

half of surveyed farmers in west Africa perceive increases in crop pests

and diseases as due to climate change as the range and seasonality of

many pests and diseases change under warming (Callo-Concha, 2018).

Pests and diseases contribute between 10–35% yield losses for wheat,

rice, maize, potato and soybean in sub-Saharan Africa (Savary etal.,

2019). Recent locust outbreaks in 2019 in east Africa have been linked

to climate conditions caused in part by ocean warming (Wang etal.,

2020b; see Box5.8).

Future climate change may increase insect pest-driven losses in Africa

for maize, rice and wheat. Compared to 1950–2000, losses may

increase by up to 50% at 2°C of global warming (Deutsch etal., 2018).

However, many challenges remain in modelling pest and disease under

climate change with additional research needed expanding the range

of crops and diseases studied (Newbery etal., 2016).

Agriculture in Africa is especially vulnerable to future climate change

in part because 90–95% of African food production is rainfed (Adams,

2018). Maize, rice, wheat and soybean yields in tropical regions

(20°S–20°N) are projected to decrease approximately 5% per degree

Celsius of global warming in a multi-model ensemble (Rosenzweig

et al., 2014; Franke et al., 2020). Dryland agricultural areas are

especially sensitive to changes in rainfall. For example, without

adaptation, substantial yield declines are projected for staple crops

in north Africa. A recent meta-analysis of 56studies indicates that,

compared to 1995–2005, economic welfare in the agriculture sector

in north Africa is projected to decline 5% for 2°C global warming and

20% for 3°C global warming, and in sub-Saharan Africa by 5% (2°C)

and 10% (3°C) (Moore et al., 2017a), both more pessimistic than

previous economic estimates.

A synthesis of projected staple crop impacts across 35 studies for

nearly 1040 locations and cases shows, on average, decreases in

crop yields with increasing global warming across staple crops in

Africa, including when accounting for CO2 increases and adaptation

measures. For example, for maize in west Africa, compared to 2005

yield levels, median projected yields decrease 9% at 1.5°C global

warming and 41% at 4°C, without adaptation (Figure9.22). However,

uncertainties in projected impacts across crops and regions are driven

by uncertainties in crop responses to increasing CO2 and adaptation

response, especially for maize in east Africa and wheat in north Africa

and east Africa (Figure9.22; Hasegawa etal., 2021).

There is also growing evidence that climate change is likely beginning

to outpace adaptation in agricultural systems in parts of Africa (Rippke

etal., 2016). For example, despite the use of adjusted sowing dates and

existing heat-tolerant varieties, Sudan’s domestic production share of

wheat may decrease from 16.0% to 4.5–12.2% by 2050 under RCP8.5

(2.4°C global warming) (Iizumi etal., 2021).

Elevated CO2 concentrations in the atmosphere might mitigate some or

all climate-driven losses (Swann etal., 2016; Durand etal., 2018), but

there is considerable uncertainty around the CO2 response (Deryng etal.,

2016; Toreti etal., 2020), especially when nutrients such as nitrogen and

phosphorus are limiting crop growth. Additional Free-Air Carbon dioxide

Enrichment (FACE) experiments are needed in the tropics, particularly

on the African continent, to better understand the impacts of increased

CO2 concentrations on the productivity of crops and cultivars grown in

Africa under additional temperature impacts and water and nutrient

limitations (Ainsworth and Long, 2021). Warming and elevated CO2

may also change the nutritional content of some crops. By 2050 under

RCP8.5 (2.4°C global warming), overall wheat yields and grain protein

content may decrease by 10% and 15%, respectively, in north and east

Africa, and by over 15% in southern Africa (Asseng etal., 2019). See

Chapter 5 for more details on CO2 impacts and uncertainties.

9.8.2.2 Observed Impacts and Projected Risks on Regional Cash

Crops and Food Crops

Few studies have attributed changes in yields of cash crops and other

regionally important food crops in Africa to human-caused climate

change, but recent research suggests yields of cash crops in Africa

have already been impacted by climate change, in both a negative

and positive manner (Falco etal., 2012; Traore etal., 2013; Ray etal.,

2019). For example, between the period 1974–2008, sugarcane yields

decreased on average by 3.9% and 5.1% in sub-Saharan Africa and

north Africa, respectively, due to climate change, while sorghum yields

increased 0.7%, and cassava yield increased 1.7% in sub-Saharan

Africa and 18% in north Africa (Ray etal., 2019).

There are also limited studies assessing projected climate change impacts

on important cash crops and food crops other than maize, rice and wheat

(Jarvis etal., 2012; Schroth etal., 2016; Awoye etal., 2017). These studies

often represent changes at speciﬁc sites in a country or assess changes

in the yield and/or suitability for cultivating a speciﬁc crop across a larger

geographic area. Climate change is projected to have overall positive

impacts on sugarcane and Bambara nuts in southern Africa, oil palm in

Nigeria and chickpea in Ethiopia (low conﬁdence) (Figure9.23).

Climate change is projected to reduce sorghum yields in west Africa

(Figure 9.23). For example, across the west African Sahel savanna

sorghum yields are projected to decline on average 2% at 1.5°C and 5%

at 2°C global warming (Faye etal., 2018). For coffee and tea in eastern

Africa, olives in Algeria and sunﬂower in Botswana and Morocco,

studies indicate mostly negative impacts on production systems.

For example, in Kenya, compared to 2000, optimal habitat for tea

production is projected to decrease in area by 27% with yields declining

10% for global warming of 1.8–1.9°C, although yield declines may be

reduced at higher levels of warming (Beringer etal., 2020; Jayasinghe

and Kumar, 2020; Rigden etal., 2020). Suitable area for tea production

may reduce by half in Uganda (Eitzinger etal., 2011; Läderach etal.,

2013). In east Africa, the coffee-growing area is projected to shift up

in elevation with suitability decreasing 10–30% between 1.5–2°C of

global warming (Bunn etal., 2015; Ovalle-Rivera etal., 2015).

For all other crops, there is at least one study that ﬁnds low to highly

negative impacts for one or several warming levels (Figure 9.23).

Mixed results on the direction of change often occur when several

contrasting sites with varying baseline climates are studied, and when

a study considers the full range of climate scenarios. For example,

there are mixed results on the direction of change for impacts of 1.5°C

1352

Chapter 9 Africa

global warming on cassava, cotton, cocoa and millet in west Africa

(low conﬁdence) (Figure9.23). In general, there is limited evidence in

the direction of change, due to single studies being available for most

crop-country combinations (Knox etal., 2010; Chemura etal., 2013;

Asaminew et al., 2017; Bouregaa, 2019). Occasionally, two studies

agree on the direction and magnitude of change, for example, for

potatoes in east Africa, yields are projected to decrease by 11–17%

with 3°C of warming (Fleisher etal., 2010; Tatsumi etal., 2011).

Projected yield changes for major crops in Africa due to climate change

Compared to 2005 yield levels

Maize WheatRice

-100

-50

Yield impact (%)

Western Africa

Southern Africa

Northern Africa

Eastern Africa

-100

-50

Yield impact (%)

-100

-50

Yield impact (%)

-100

-50

Yield impact (%)

Without

adaptation

With

adaptation

Global warming level

>1.5 >2.0 >3.0 >4.0

Global warming level

>1.5 >2.0 >3.0 >4.0

Global warming level

>1.5 >2.0 >3.0 >4.0

Figure9.22 | Projected yield changes for major staple crops in Africa due to climate change (compared to 2005 yield levels). Projected impacts are grouped

by projected global warming levels. Boxplots show a synthesis of projected staple crop impacts, with and without adaptation measures (e.g., planting date, cultivar, tillage or

irrigation). On average crop yields are projected to decrease with increasing global warming across staple crops in Africa. The overall adaptation potential to offset yield losses

across Africa for rice, maize and wheat reduces with increasing global warming. On average, in projections including adaptation options, yield losses in the median case are reduced

from −33% to −10% of 2005 levels at 2°C of global warming and from −46% to −23% at 4°C. Global warming levels were calculated using a baseline for pre-industrial global

mean temperature of 1850–1900 . Data are a synthesis across 35studies for nearly 1040 locations and cases of projected impacts for regions of Africa for maize, rice and wheat

(Hasegawa etal., 2021; TableSM9.5).

1353

Africa Chapter 9

9.8.2.3 Observed Impacts and Projected Risks for Wild-

Harvested Food

Wild-harvested foods (e.g., fruits, vegetables and insects) provide

dietary diversiﬁcation and for many people in Africa, wild-harvested

food plants may provide a livelihood and/or nutritional safety net

when other sources of food fail, such as during drought (Sunderland

etal., 2013; Shumsky etal., 2014; Wunder etal., 2014; Baudron etal.,

2019b). In Zimbabwe, during lean times, consumption of wild fruits

increases, as does their sale to generate income for additional food

expenses in poor, rural households (Mithöfer and Waibel, 2004). In Mali,

Tanzania and Zambia, household surveys indicate that forest products

including wild foods can play an important role in reducing household

vulnerability to climate shocks by providing alternative sources of food

Projected risks at increasing global warming levels for regionally important cash and food crops in Africa

Cassava

Sugarcane

Cotton

Oil Palm

Tobacco

Cocoa

Coffee

Tea

Groundnut

Bambara nut

Chickpea

Olive

Millet

Sorguhm

Potato

Sunflower

Cowpea

East Africa

West Africa

Central Africa

Southern Africa

North Africa

Sub-Saharan Africa

Sahel

Southern Africa*

West Africa (Benin and Cameroon)

East Africa (Ethiopia)

North AFrica (Sudan)

Sub-Saharan Africa

West Africa (Nigeria)

Southern Africa (Zimbabwe)

East Africa

East Africa (Kenya and Uganda)

Sub-Saharan Africa

West Africa (Benin)

North Africa (Sudan)

Southern Africa

East Africa (Ethiopia)

North Africa (Algeria)

West Africa

Southern Africa

North Africa (Sudan)

Africa

East Africa

Southern Africa

West Africa

Sahel

Central Africa

Southern Africa (Botswana)

North Africa (Morocco)

West Africa (Benin)

>3.0°C

Crop Region (country) >2.0°C>1.5°C >4.0°C

= insufficient data(empty)

*Southern Africa (South Africa and Swaziland)

**West Africa (Ghana and Côte d’Ivoire)

A = Late planting can reduce the impact of climate change.

B= Crop modelling suggests that shifts in sowing date and

fertilizer rate can be effective in reducing negative

impacts on soghum yield in Southern Africa.

Adaptation

options

= negligible/

West Africa**

Benificial

outcome

Detrimental

outcome

Magnitude of

projected outcome

% yield

change

(biomass,

sucrose)

% change

in current

real GDP

(due cost of

inaction on

adaptation)

% change

in climate

suitability

(area)

Very positive >40% >4%>40%

Highly positive >20% >2%>20%

Moderately positive >10% >1%>10%

Low positive >5%

+>0.5%>5%

>20% >2%>20%Highly negative

>40% >4%>40%Very negative

>10% >1%>10%Moderately negative

>5% >0.5%>5%Low negative

Projected changes

per global warming level

Level of confidence

High

Low

Medium

Figure9.23 | Projected risks at increasing global warming levels for regionally important cash and food crops in Africa. Insufﬁcient data indicates there were

limited to no published studies that have quantiﬁed projected climate change impacts or adaptation options for speciﬁc crops under different warming levels (see TableSM9.6).

Global warming levels were calculated using a baseline for pre-industrial global mean temperature of 1850–1900 .

1354

Chapter 9 Africa

and income during droughts and ﬂoods (Robledo etal., 2012). In the

parklands of west Africa, wild trees are a signiﬁcant source of wild

foods and are thus a place where one might expect wild plant foods

to make an important contribution to diets and nutrition (Boedecker

etal., 2014; Leßmeister et al., 2015). Non-timber forest products are

consumed by an estimated 43% of all households in Burkina Faso (FAO,

2019), and wild vegetables accounted for about 50% of total vegetable

consumption in southeastern Burkina Faso (Mertz etal., 2001).

The focus of projected climate change impacts has been almost

exclusively on agricultural production, yet climate change could

have substantial impacts on the distribution and availability of wild-

harvested food plants in Africa (Wessels etal., 2021). Non-cultivated

species in Africa are vulnerable to current and future climate changes,

with widespread changes in woody plant cover already observed

(see Section9.6.1.1). Evidence about the impacts of climate change

on individual wild food species is less consistent. Communities in the

Kalahari (Crate and Nuttall, 2016) and Zimbabwe (Sango and Godwell,

2015) report growing scarcity of wild foods (such as wild meat and fruit)

perceived to be, at least in part, due to drought and climate change.

Shea tree (Vitellaria paradoxa) nuts provide fats and oils for the diets of

many rural populations in west Africa. In Burkina Faso, global warming

of 3°C is projected to reduce area of suitable habitat for the shea tree

by 14% (Dimobe etal., 2020). In southern Africa, 40% of native, wild-

harvested food plant species are projected to decrease in geographic

range extent at 1.7°C global warming with range reductions for 66% of

species projected for 3.5°C (Wessels etal., 2021).

9.8.2.4 Observed Impacts and Projected Risks on Livestock

Livestock systems in Africa are already being affected by changes in climate

through increased precipitation variability leading to decreasing fodder

availability (Sloat etal., 2018; Stanimirova etal., 2019). More than twice

as many countries in Africa have experienced increases in precipitation

variability in the last century than decreases (Sloat etal., 2018). Fodder

availability is also being impacted by woody plant encroachment—

the increase in shrub and tree cover—which has increased by 10%

on subsistence grazing lands and 20% on economically important

grazing lands in south Africa in the last 60years (Stevens etal., 2016),

and is driven in part by climatic factors (see Section9.6.1.1). Increased

temperature and precipitation have contributed to the expanding range,

especially in east and southern Africa, of several ixodid tick species which

carry economically important livestock diseases (Nyangiwe etal., 2018).

Pastoralists in Africa perceive the climate as already changing and

report more erratic and reduced rainfall, prolonged and more frequent

droughts and a rise in temperature (Sanogo etal., 2017; Kimaro etal.,

2018). They also report reduced milk production, increased deaths and

disease outbreaks in their herds due to malnutrition and starvation

resulting from the shortages in forage and water (Kimaro etal., 2018).

Additional research is required to attribute precipitation variability to

human-induced climate change (see Section9.5), and to evaluate the

relative contributions of climate change and management to disease

vector extent.

Future climate change will have compounding impacts on livestock,

including negative impacts on fodder availability and quality, availability

of drinking water, direct heat stress and the prevalence of livestock

diseases (Nardone etal., 2010; Rojas-Downing etal., 2017; Godde etal.,

2021). Climate change is projected to negatively affect fodder availability

(Briske, 2017) because overall rangeland net primary productivity (NPP)

by 2050 is projected to decrease 42% under RCP4.5 (2°C global warming)

and 46% under RCP8.5 (2.4°C global warming) for western sub-Saharan

Africa, compared to a 2000 baseline (Boone etal., 2018). NPP is also

projected to decline by 37% in southern Africa, 32% in north Africa

and 5% in both east Africa and central Africa by 2050 under RCP8.5

(2.4°C global warming) (Boone etal., 2018). For example, in Zimbabwe

by 2040–2070, net revenues from livestock production, compared to a

2011 survey, are projected to decline by 8–32% under RCP4.5 for 2°C

and 11–43% under RCP8.5 for 2.7°C global warming due to a decline in

fodder availability (Descheemaeker etal., 2018). The available literature

does not comprehensively capture the economic implications of climate-

related impacts on livestock production across Africa.

Fodder quality, critical for animal health and weight gain, is at risk

from climate change as increases in temperature, elevated CO2 and

water stress have been shown to reduce dry matter digestibility and

nitrogen content for C3 grasses (Augustine etal., 2018), tropical C4

grasses (Habermann etal., 2019) and fodder crops such as Lucerne/

Alfalfa (Polley etal., 2013; Thivierge etal., 2016).

Climate change is projected to threaten water availability for

livestock. Droughts in Africa have become more intense, frequent and

widespread in the last 50years (Masih etal., 2014), and progressive

increase in droughts between 3- and 20-fold under climate change

up to 3°C of warming are projected for most of Africa (Section9.5).

In the Klela basin in Mali by 2050, groundwater recharge is projected

to decline by 49% and groundwater storage by 24% under RCP8.5

(2.4°C global warming) compared to the 2006 baseline (Toure etal.,

2017). Water availability for livestock during drought is a major

concern for many African pastoralists including but not limited to those

in Zimbabwe (Dzavo etal., 2019) and Nigeria (Ayanlade and Ojebisi,

2019). Increased livestock mortality and livestock price shocks have

been associated with droughts in Africa, as well as being a potential

pathway for climate-related conﬂict (Catley etal., 2014; see Box9.9;

Maystadt and Ecker, 2014).

Heat stress may already be the largest factor impacting livestock

production in many regions in Africa (El-Tarabany etal., 2017; Pragna

etal., 2018), as the combination of high temperatures and high relative

humidity can be dangerous for livestock and has already decreased

dairy production in Tunisia (Amamou etal., 2018). Climate change is

projected to increase heat stress for all types of livestock, especially in

the tropics (Figure9.24; Lallo etal., 2018). More studies quantifying

the impact of heat stress on other types of livestock production loss

are needed in Africa (Rahimi etal., 2021).

Climate change will impact livestock disease prevalence primarily

through changes in vector dynamics or range (Abdela and Jilo,

2016; Semenza and Suk, 2018). African Rift Valley Fever (RVF) and

trypanosomiasis are positively associated with extreme climate events

(droughts and ENSO) (Bett etal., 2017) and are projected to expand in

range under climate change (Kimaro etal., 2017; Mweya etal., 2017).

More quantitative estimates of projected risk from diseases are needed.

1355

Africa Chapter 9

Severe heat stress duration for cattle in Africa is projected to increase with increased global warming

(a) Historical risk (1985–2014)

(b) Historical exposure (1985–2014)

(d) Global warming 3.75°C

Annual number

of days over

threshold

300

240

180

120

Increase in

annual number

of days over

threshold

300

240

180

120

cattle

More severe heat

Figure9.24 | Severe heat stress duration for cattle in Africa is projected to increase with increasing global warming.

(a) Number of days per year with severe heat stress in the historical climate (1985–2014).

(b) Historical cattle exposure to severe heat. Cattle density data from Gilbert etal. (2018).

(c, d) Projected increase in the number of days per year with severe heat stress for a global warming level of 1.5°C and 3.75°C. Severe heat stress for cattle is projected to become

much more extensive in the future in Africa at increased global warming levels. Strong mitigation would substantially limit the spatial extent and the duration of cattle heat stress

across Africa. Heat stress is estimated using the Temperature Humidity Index with a value greater than 79 considered the onset of severe heat stress (Livestock Weather Safety Index)

(Lallo etal., 2018). Global warming of 1.5°C used scenario SSP1–2.6 and global warming of 3.75°C used SSP5-8.5, both for 2070–2099 (12 climate models from O’Neill etal.,

2016; Tebaldi etal., 2021). Global warming levels were calculated using a baseline for pre-industrial global mean temperature of 1850–1900 .

1356

Chapter 9 Africa

9.8.3 Adapting to Climate Variability and Change in

Agriculture

Agricultural and livelihood diversiﬁcation are strategies used by

African households to cope with climate change, enabling them to

spread risks and adjust to shifting climate conditions (Thierfelder etal.,

2017; Thornton etal., 2018). This includes adjusting cropping choices,

planting times, or size, type and location of planted areas (Altieri etal.,

2015; Nyagumbo et al., 2017; Dayamba et al., 2018). In southern

Africa, changes in planting dates provide farmers with greater yield

stability in uncertain climate conditions (Nyagumbo et al., 2017).

In Ghana, farmers are changing planting schedules and using early

maturing varieties to cope with late-onset and early cessation of the

rainy season (Antwi-Agyei etal., 2014; Bawakyillenuo etal., 2016).

The use of drought-tolerant crop varieties is another adaptation

available to African farmers (Hove and Gweme, 2018; Choko et al.,

2019). Adoption, however, is hindered by lack of information and

training, availability or affordability of seed, inadequate labelling and

packaging size for seed supplies and ﬁnancial constraints (Fisher etal.,

2015). Moreover, drought-tolerant varieties do not address changing

temperature regimes (Guan etal., 2017).

Crop diversiﬁcation enhances crop productivity and resilience and

reduces vulnerability in smallholder farming systems (McCord etal.,

2015; Mulwa and Visser, 2020). In Tanzania, diversiﬁed crop portfolios

are associated with greater food security and dietary quality (Brüssow

etal., 2017). In Kenya, levels of crop diversity are higher in villages

affected by frequent droughts, which are the main cause of crop failure

(Bozzola and Smale, 2020). Crop diversiﬁcation also helps control

pest outbreaks, which may become more frequent and severe under

increased climate variability and extreme events (Schroth and Ruf,

2014). High farming diversity enables households to better meet food

needs, but only up to a certain level of diversity (Waha etal., 2018),

and the viability of and beneﬁts from mixed farming are highly context

dependent (Thornton and Herrero, 2015; Weindl etal., 2015).

Agroecological and conservation agriculture practices, such as

intercropping, integration of legumes, mulching and incorporation of

crop residues, are associated with household food security and improved

health status (Nyantakyi-Frimpong etal., 2017; Shikuku etal., 2017).

These practices can enhance the beneﬁts of other adaptations, such as

planting drought- and heat-tolerant or improved varieties, although

effects vary across soil types, geographical zones and social groups

(Makate etal., 2019; Mutenje etal., 2019). Non-climatic variables, such

as ﬁnancial resources, access to information and technology, level of

education, land security and gender dynamics affect feasibility and

adoption (Makate etal., 2019; Mutenje etal., 2019).

To mitigate growing water stress, countries like Ethiopia, Rwanda,

Tanzania and Uganda are striving to improve irrigation efﬁciency

(McCarl etal., 2015; Connolly-Boutin and Smit, 2016; Herrero etal.,

2016). The feasibility and effectiveness of this adaptation depend

on biophysical and socioeconomic conditions (Amamou et al.,

2018; Harmanny and Malek, 2019; Schilling et al., 2020). Irrigation

is unaffordable for many smallholder farmers and only covers a

negligible proportion of the total cultivated area. Nonetheless, in some

regions of west Africa, small-scale irrigation, including the digging

of ditches, holes and depressions to collect rainwater (Makondo and

Thomas, 2018), is widely adopted and promoted to support national

food security (Dowd-Uribe etal., 2018).

African farmers are also diversifying their income sources to offset

reduced yields or crop losses by shifting labour resources to off-farm work,

or by migrating seasonally or longer term (Kangalawe etal., 2017; Hove

and Gweme, 2018). Off-farm activities provide ﬁnancial resources that

rural households need to cope with extreme climate variability (Hamed

etal., 2018; Rouabhi etal., 2019). However, in some cases, these off-farm

activities can be maladaptive at larger scales, such as when households

turn to charcoal production, which contributes to deforestation (Egeru,

2016). Whether off-farm activities constitute maladaptation depends on

whether resources are available to upgrade skills or support investments

that make a new business more lucrative. Without such resources, this

option may lead to impoverishment (see Box5.8).

Smallholder farmers’ responses tend to address short-term shocks

or stresses by deploying coping responses (e.g., selling labour,

reducing consumption and temporary migration), rather than longer-

term sustainable adaptations (Ziervogel and Parnell, 2014; Jiri etal.,

2017). This is partly due to institutional barriers (e.g., markets, credit,

infrastructure and information) and resource requirements that are

unaffordable to smallholder farmers (Pauline etal., 2017). There is a

need for policies that strengthen natural, ﬁnancial, human and social

capitals, the latter being key to household and community resilience,

especially where government services may be limited (Mutabazi etal.,

2015; Alemayehu and Bewket, 2017). There is evidence that collective

action, local organisations and climate information are associated with

higher food security, and that institutional interventions are needed to

ensure scaling up of adaptations (Thornton etal., 2018).

A range of options is considered potentially effective in reducing future

climate change risk, including plant breeding, crop diversiﬁcation

alongside livestock, mixed planting, intercrops, crop rotation and

integrated crop–livestock systems (see Chapter5 Sections5.4.4; 5.14.1;

Thornton and Herrero, 2014; Cunningham etal., 2015; Himanen etal.,

2016; Farrell etal., 2018; Snowdon etal., 2021). However, adaptation

limits for crops in Africa are increasingly reached for global warming

above 2°C (high conﬁdence), and in tropical Africa may already be

reached at current levels of global warming (low conﬁdence).

Global warming beyond 2°C will place nearly all of sub-Saharan

Africa cropland substantially outside of its historical safe climate

zone (Kummu etal., 2021) and may exponentially increase the cost of

adaptation and residual damage for major crops (Iizumi etal., 2020).

Without accounting for CO2 increases, global-scale studies employing

ensembles of gridded crop models for 2°C of global warming ﬁnd

that for adaptation using genetic cultivar change in most of Africa net

losses are projected, even with adaptation up to 2°C of global warming

for rice, maize, soybean and wheat (Minoli etal., 2019; Zabel et al.,

2021), although model uncertainty is still high (Müller etal., 2021). In

contrast, when accounting for CO2 increases, applying new genetics for

rice under warming is projected to fully counteract all climate change-

induced losses in Africa up to 3.5°C of global warming, except in west

Africa (van Oort and Zwart, 2018).

1357

Africa Chapter 9

However, compared to temperate regions, risks of adaptation shortfalls—

that is climate change impacts even after adaptation—are generally

greater for current agricultural conditions across much of Africa (tropical,

arid and semi-arid) (Sun etal., 2019). The overall adaptation potential

to offset yield losses across Africa for rice, maize and wheat reduces

with increasing global warming. On average, in projections including

adaptation options, yield losses, in the median case, are reduced from

−33% to −10% of 2005 levels at 2°C of global warming and from −46%

to −23% at 4°C, but estimates vary widely (Figure9.22; Hasegawa etal.,

2021).Across Africa, the risks of no available genetic varieties of maize

for growing season adaptation are higher for east Africa and southern

Africa than for central or west Africa (Zabel etal., 2021). To keep pace

with expected rates of climate change, crop breeding, development

and adoption must accelerate to meet the challenge (Challinor et al.,

2016). Regional modelling has shown very little efﬁcacy for late sowing,

intensiﬁcation of seeding density and fertilizers, water harvesting and

other measures for cereals in west Africa at 2°C of global warming

(Sultan and Gaetani, 2016; Guan etal., 2017). Historical climate change

adaptation by crop migration has been shown in some cases (Sloat etal.,

2020) but poses risks to biodiversity and water resources, and this option

may be limited for maize in Africa by suitable climate shifting completely

across national borders and available land at the edges of the continent

(Franke etal., 2021). More research is required to evaluate the potential

effectiveness and limits of adaptation options in African agriculture under

future climate change (see Chapter5 Section5.4.4 for more details).

9.8.4 Climate Information Services and Insurance for

Agriculture Adaptation

In addition to adaptation in crop, soil and water management, the

combination of (a) Climate Information Services, (b) institutional

capacity building and (c) strategic ﬁnancial investment can help

African food producers adapt to projected climate risks (Carter etal.,

2015; Surminski etal., 2016; Scott et al., 2017; Cinner etal., 2018;

Diouf etal., 2019; Hansen et al., 2019a). There is growing evidence

of farmers’ use of weather and climate information, especially at the

short- and medium-time horizon (Carr etal., 2016; Singh etal., 2018).

Digital services can contribute to the sustainable intensiﬁcation of food

production globally (Duncombe, 2018; Klerkx etal., 2019). This points

to the need for the scientiﬁc and development communities to better

understand the conditions that enable widespread adoption in Africa.

Although climate information services have the potential to strengthen

farmers’ resilience, barriers to accessibility, affordability and utilisation

remain (Krell et al., 2021). Often the information offered is not

consistent with what farmers need to know and how they access

and process information (Meadow et al., 2015; Singh etal., 2018).

Production of salient and credible climate information is hindered

by the limited availability of and access to weather and climate data

(Coulibaly et al., 2017; Hansen etal., 2019a). The existing weather

infrastructure remains suboptimal to enable the development of

reliable early warning systems (Africa Adaptation Initiative, 2018; Krell

etal., 2021). Of the 1017 land-based observational networks in the

world, only 10% are in Africa, and 54% of Africa’s surface weather

stations cannot capture data accurately (Africa Adaptation Initiative,

2018; World Bank, 2020d).

Advances in remote sensing and climate analysis tools have allowed

the development of weather index insurance products as a potential

adaptation option, with Malawi and Ethiopia being early testbeds

(Tadesse etal., 2015, Section 9.11.4). These pilot projects were initially

sponsored by NGOs, but in the last decade, the private sector has

become more active in this sector. The Ghana Agricultural Insurance

Pool and Agriculture and Climate Risk Enterprise (ACRE) in Kenya,

Tanzania and Rwanda are examples. Despite the potential for weather

index insurance, uptake by smallholder farmers in Africa remains

constrained by several factors. These include the failure to capture

actual crop loss as in traditional crop insurance products, as well

as the inability of poor farmers to pay premiums (Elum etal., 2017;

Weber, 2019). Weather index insurance could be part of a wider

portfolio of risk mitigation services offered to farmers (Tadesse etal.,

2015; Weber, 2019). Strategic partnerships between key players (e.g.,

credit institutions, policymakers, meteorologists, farmer associations,

extension services, NGOs) are needed to develop better products and

build capacity among smallholder farmers to engage more beneﬁcially

with weather index insurance (Singh etal., 2018; Tesfaye etal., 2019).

9.8.5 Marine and Inland Fisheries

9.8.5.1 Observed Impacts of Climate Variability and Change on

Marine and Inland Fisheries

Marine and freshwater ﬁsheries provide 19.3% of animal protein intake

(Chan etal., 2019) and support the livelihoods of 12.3million people

(de Graaf and Garibaldi, 2015) across Africa. Estimates suggest that ﬁsh

provides approximately 200 million people in Africa with their main

source of animal protein and key micronutrients (Obiero etal., 2019).

Although marine ﬁsheries account for >50% of total capture ﬁshery

production (Obiero etal., 2019), 2.9million tonnes of ﬁsh are harvested

annually from inland water bodies constituting the highest per capita

inland ﬁshery production of any continent (2.56 kg per person per year)

(Harrod etal., 2018a; Funge-Smith and Bennett, 2019).

Climate change already poses a signiﬁcant threat to marine and

freshwater ﬁsheries and aquaculture in Africa (Blasiak etal., 2017;

Harrod et al., 2018a). Severe (>30%) coral bleaching has impacted

~80% of major reef areas in the western Indian Ocean and Red Sea

along Africa’s eastern coast (Hughes et al., 2018). Biological effects

(e.g., changes in primary production, ﬁsh distribution) have also

occurred (Hidalgo et al., 2018). Range shifts in marine ﬁsh species

can exacerbate boundary conﬂicts among ﬁsher communities (Penney

etal., 2017; Belhabib et al., 2019). Changes in ﬁsh distribution and

reductions in catch across inland ﬁsheries are associated with climatic

variability by ﬁshing communities (Okpara etal., 2017b; Lowe etal.,

2019; Muringai etal., 2019b). Floods and reduced river ﬂow reduces

ﬁsh catches (Kolding etal., 2019), which scale positively with discharge

rates in rivers across Africa (McIntyre etal., 2016). Warming air and

water temperatures have altered water stratiﬁcation patterns in African

lakes causing reductions in or redistributions of primary productivity

and leading to reduced ﬁsh biomass (Section9.6.1.3). Such changes,

partially explain reduced ﬁsh catches in Lake Tanganyika (Cohen etal.,

2016). In some regions, water scarcity has resulted in conﬂict within

and among food production sectors (pastoralists, ﬁshers and farmers)

1358

Chapter 9 Africa

in this region (Okpara etal., 2017b). Small-scale and artisanal ﬁsher

communities are ill-equipped to adapt to climate impacts because

there are few ﬁnancially accessible alternative livelihoods (Belhabib

etal., 2016; Ndhlovu and Saito, 2017).

9.8.5.2 Projected Risks of Climate Change to Fisheries

At 4.3°C global warming, maximum catch potential (MCP) from marine

ﬁsheries in African Exclusive Economic Zones (EEZs) would decrease by

12–69% by the end of the 21st century relative to recent decades (1986–

2005), whereas global warming of 1.6°C would limit the MCP decrease to

3–41% (Cheung William etal., 2016; IPCC, 2019c). By mid-century under

2°C global warming, MCP would decrease by 10 to >30% on the western

coast of South Africa, the Horn of Africa and west Africa, indicating these

regions could be at risk to declines in MCP earlier in the century than

other parts of Africa (Cheung etal., 2016). Declining ﬁsh harvests due to

sea temperature rise could leave 1.2–70 (median 11.1) million people in

Africa vulnerable to deﬁciencies in iron, and up to 188million to vitamin

A and 285million to vitamin B

and omega-3 fatty acids by mid-century

under 1.7°C global warming (Golden etal., 2016). Maire etal. (2021)

assessed the nutritional vulnerabilities of African countries to climate

change and overﬁshing, and found that the four most vulnerable countries

ranked on a scale from 0 (low vulnerability) to 100 (high vulnerability)

were Mozambique (87), Madagascar (76), Tanzania (61) and Sierra Leone

(58). Coral reef habitat in east Africa is projected to decrease, resulting

in negative impacts on demersal ﬁsh stocks and invertebrates (Hoegh-

Guldberg etal., 2018). Central, west and east Africa are projected to be at

the greatest nutritional risk from sea temperature rise, leading to reduced

catch in coastal waters (Figure9.25; Golden etal., 2016). In north Africa,

a rise in water temperatures is expected to impact the phenology and

migratory patterns of large pelagic species (e.g., blueﬁn tuna, Thunnus

thynnus) (Hidalgo et al., 2018). Increased sea surface temperatures

have been associated with increases in spring and summer upwelling

intensity reducing the abundance and larval survival of small pelagic

ﬁshes and shellﬁsh in west Africa (Bakun etal., 2015; Tiedemann etal.,

2017; Atindana etal., 2020). Ocean warming, acidiﬁcation and hypoxia

(a)

Climate change risk to marine fisheries in Africa

Countries with

high overlap of

dependence and future threat

to fisheries from climate change

Global

warming

1.6°C

Present

Global

warming

>4°C

Dependence on

marine foods

for nutrition

>23%

18–23%

7–17%

3–7%

<3%

No data

> 13%

Projected decrease in

maximum catch potential (MCP)

of marine fisheries

No data

13–27%

51–60%

41–50%

28–40%

(b)

(c)

(d)

(e)

60–70%

Figure9.25 | Climate change increases risks to the catch potential and nutrition from marine ﬁsheries.

(a) The percentage of animal source foods consumed that originate from a marine environment. Countries with higher dependence are indicated by darker shades of green (Golden

etal., 2016).

(b–c) Projected percentage change in maximum catch potential of marine ﬁsheries compared to the recent past (1986–2005) under 1.6°C global warming and >4°C global

warming by end of 21st century (2081–2100) in countries’ Exclusive Economic Zones (EEZs) (Cheung William etal., 2016). Darker red indicates greater percentage reduction

(negative values).

(d–e) Countries (in purple) that have overlap between high nutritional dependence on marine ﬁsheries and high risk of reduction in maximum catch potential under the two global

warming scenarios. Global warming levels were calculated using a baseline for pre-industrial global mean temperature of 1850–1900 .

1359

Africa Chapter 9

are predicted to affect the early life history stages of several marine

food species, including ﬁsh and crustaceans (Kifani etal., 2018). Climate

warming is projected to impact water temperature and horizontal and

vertical mixing on the southern Benguela ecosystem, with marked

negative effects on the biomass of several important ﬁshery resources by

2050 ampliﬁed under 2.5°C compared to 1.7°C global warming (Ortega-

Cisneros etal., 2018).

For inland ﬁsheries, 55–68% of commercially harvested ﬁsh species will

be vulnerable to extinction under 2.5°C global warming by the end of

the 21st century (2071–2100) compared to 77–97% under 4.4°C global

warming (Figure9.26). This will increase the number of countries that

are at food security risk due to ﬁshery species declines from 10 to 13

(Figure9.26). Other recent analyses suggest that African countries with

the highest inland ﬁsheries production have low- to mid-range projected

climate risk (2.4°C–2.6°C local temperature increase compared to

other regions with 2.7°C–3.3°C increase by end of century) based on a

3.9°C global warming scenario (Harrod etal., 2018b). In regions where

inland ﬁshery production is derived primarily from lakes, there is a lower

likelihood of reduced catch, especially where precipitation is projected

to increase (e.g., African Great Lakes region) (Harrod et al., 2018b).

Regions reliant on rivers and ﬂoodplains (e.g., Zambezi and Niger

basins) are more likely to experience downturns in catch, as hydrological

dynamics may be altered (Harrod etal., 2018b). Projections suggest that

opportunistic species that do well in modiﬁed systems (Escalera-vázquez

etal., 2017) and small pelagic ﬁshes will remain important components

of inland ﬁshery food systems (Kolding etal., 2016; Gownaris etal., 2018;

2019). Climate adaptation responses that rely on freshwater resources

(e.g., hydroelectric power generation, agricultural irrigation) represent

threats to inland ﬁsheries (Cowx etal., 2018; Harrod etal., 2018c), by

changing ﬂow regimes, reducing water levels, and increasing runoff of

pesticides and nutrients (Harrod etal., 2018c).

Climate change risk to freshwater fisheries in Africa

Countries with

high overlap of

dependence and future threat

to fisheries from climate change

Global

warming

2.4°C

<0.3

No data

Average number of

climate-change vulnerable,

commercially harvested, freshwater fishes species

>11.2

7.8–11.2

3.3–7.8

0.3–3.2

Index of current

dependence on

inland fisheries

<0.04 (Low)

0.05–0.21

0.26–0.55

0.57–1.05

>1.05 (High)

No data

Global

warming

>4°C

Present

(a)

(b)

(c)

(d)

(e)

Figure9.26 | Climate change risk to freshwater ﬁsheries.

(a) Countries’ dependence on inland ﬁsheries for nutrition; darker green shows higher dependence on inland ﬁsheries.

(b–c) Projected numbers of freshwater ﬁshery species vulnerable to climate change within freshwater ecoregions under >2°C global warming and >4°C global warming estimated

by the end of the 21st century (2071 to 2100). Numbers of vulnerable ﬁsh species translate to an average of 55–68% vulnerable at >2°C and 77–97% vulnerable at >4°C global

warming. Darker reds indicate higher concentrations of vulnerable ﬁsh species.

(d–e) Countries (in purple) that have an overlap between high dependence on freshwater ﬁsh and high concentrations of ﬁshery species that are vulnerable to climate change

under two warming scenarios. Countries’ dependence on inland ﬁsheries for nutrition was estimated by catch (total, tonnes)(FAO, 2018b; Fluet-Chouinard etal., 2018), per capita

catch (kg per person per year) (FAO, 2018b), percentage reliance on ﬁsh for micronutrients, and percentage consumption per household (Golden etal., 2016). Z-scores of each

metric were averaged for each country to create a composite index describing ‘current dependence on freshwater ﬁsh’ for each country with darker blue colours indicating higher

dependence. Data on vulnerable ﬁsh species was from (Nyboer etal., 2019).

1360

Chapter 9 Africa

For both marine and freshwater ﬁsheries, climate-related extreme

weather events and ﬂooding may drive the loss of ﬁshing days, cause

damage and loss to ﬁshing gear, endanger the lives of ﬁshers and

block transportation from damaged roads (Muringai etal., 2021). Fish

processing via weather-dependent techniques such as sun drying may

be hampered, causing post-harvest losses (Akintola and Fakoya, 2017;

Chan etal., 2019).

9.8.5.3 Current and Future Adaptation Responses for Fisheries

Patterns of vulnerability and adaptive capacity are highly context

dependent and vary within and among ﬁshing communities in

coastal and riparian areas (Ndhlovu and Saito, 2017; Lowe et al.,

2019; D’agata etal., 2020). Interventions that integrate scientiﬁc

knowledge and ﬁshers’ local knowledge while focusing on vulnerable

groups are expected to be more successful (Musinguzi etal., 2018;

Muringai etal., 2019b). Infrastructure improvements (e.g., storage

facilities, processing technologies, transport systems) could reduce

post-harvest losses and improve food safety (Chan etal., 2019). Fisher

safety can be aided by early warning of severe weather conditions

(Thiery et al., 2017), enhanced through communication via mass

media and mobile phones (Thiery etal., 2017; Kiwanuka-Tondo etal.,

2019). Although changing ﬁshing gears and shifting target species

are important adaptation options for artisanal ﬁshers, many have

instead expanded their ﬁshing range or increased effort (Musinguzi

etal., 2015; Belhabib etal., 2016). Adapting to the impacts of climate

change on marine ﬁsheries productivity requires management

reforms accounting for shifting productivity and species distributions,

such as increasing marine protected areas, strengthening regional

trade networks, and increasing the investment and innovation in

climate-resilient aquaculture production (Golden etal., 2021). This

could yield higher catch and proﬁts in the future relative to today

in 50% of African countries with marine territories under 2°C global

warming and in 35% under 4.3°C global warming (Free etal., 2020).

For inland ﬁsheries, opportunities for adaptation include better

integration of inland ﬁsheries into management plans from other

sectors (e.g., hydropower and irrigation) (Harrod etal., 2018c; Cowx

and Ogutu-Ohwayo, 2019; McCartney etal., 2019). There is growing

interest in enhancing the supply of freshwater ﬁshery production

from small water bodies and reservoirs in dryland regions of sub-

Saharan Africa (Kolding etal., 2016).

9.9 Human Settlements and Infrastructure

This section assesses climate impacts, risks and adaptation options for

human settlements comprising human populations and infrastructure

such as buildings, roads and energy across Africa.

9.9.1 Urbanisation, Population and Development Trends

Africa is the most rapidly urbanising region in the world, with an

annual urban population growth rate of 3.6% for 2005–2015 (UN-

Habitat, 2016). About 57% of the population currently lives in rural

areas, but the proportion of the population living in urban areas is

projected to exceed 60% by 2050 (UNDESA, 2019b) (UN-Habitat,

2016). Much of the rapid rate of urbanisation has resulted from the

growth of small towns and intermediary cities (African Development

Bank etal., 2016).

Approximately 59% of sub-Saharan Africa’s urban population resides

in informal settlements (in some cities up to 80%), and the population

in informal settlements is expected to increase (very high conﬁdence)

(Taylor and Peter, 2014; UN-Habitat, 2014; 2016; UNDP, 2019). These

urbanisation trends are compounding increasing exposure to climate

hazards, particularly ﬂoods and heatwaves (high conﬁdence) (Dodman

etal., 2015).

Globally, the highest rates of population growth and urbanisation are

taking place in Africa’s coastal zones (high conﬁdence) (Merkens etal.,

2016). Coastal urban populations account for 25–29% of the total

population in west, north and southern Africa (OECD/SWAC, 2020).

Accounting for a continuing young population, stagnant economies

and migration to regional growth centres, projections indicate that the

low-lying coastal zone population of Africa could increase to over 100

million people by 2030 and over 200 million people by 2060 relative to

54 million in 2000 (Neumann etal., 2015; see Figure 9.28).

Climate-related displacement is widespread in Africa, with increased

migration to urban areas in sub-Saharan Africa linked to decreased

rainfall in rural areas, increasing urbanisation and affecting household

vulnerability (see Box9.9). Much of this growth can occur in informal

settlements which are growing due to both climatic and non-climatic

drivers, and which often house temporary migrants, including internally

displaced people. Such informal settlements are located in areas

exposed to climate change and variability and are exposed to ﬂoods,

landslides, sea level rise and storm surges in low-lying coastal areas,

or alongside rivers that frequently overﬂow, thereby exacerbating

existing vulnerabilities (Satterthwaite etal., 2020).

Sub-Saharan Africa’s large infrastructure deﬁcit (quantity, quality and

access) with respect to road transport, electricity, water supply and

sanitation places the region at the lowest of all developing regions

(AfDB, 2018a; Calderon et al., 2018). Adequate infrastructure to

support Africa’s rapidly growing population is important to raise living

standards and productivity in informal settlements (AfDB, 2018b;

UN Environment, 2019). Yet planned infrastructure developments,

including those related to the AU’s PIDA, along with other energy

plans, and China’s Belt and Road Initiative, may increase or decrease

both climate change mitigation and adaptation depending on whether

infrastructure planning integrates current and future climate change

risks (Cervigni etal., 2015; Addaney, 2020; see Box9.5).

9.9.2 Observed Impacts on Human Settlements and

Infrastructure

African human settlements are particularly exposed to ﬂoods (pluvial

and ﬂuvial), droughts and heat waves. Other climate hazards are

sea level rise and storm surges in coastal areas, tropical cyclones

and convective storms. This sub-section provides an assessment of

observed impacts and risks from climate hazards in different sub-

regions to underscore the relevance of climate-sensitive planning and

1361

Africa Chapter 9

actions to advance social and economic development, and reduce the

loss and damage of property, assets and critical infrastructure.

9.9.2.1 Observed Impacts on Human Settlements

The spatial distribution of climate hazards and observed impacts in

terms of total people affected (displaced persons and deaths) during

2010–2020 is shown in Figure 9.27. From 2000–2019, ﬂoods and

droughts accounted for 80% and 16%, respectively, of the 337million

affected persons, and a further 32% and 46%, respectively, of 46,078

deaths from natural disasters in Africa (CRED, 2019). Flooding is a

major hazard across Africa (Kundzewicz et al., 2014; Douglas, 2017)

and is increasing (Zevenbergen etal., 2016; Elboshy etal., 2019). An

increase in extreme poverty and up to a 35% decrease in consumption

has been associated with exposure to ﬂood shocks (Azzarri and

Signorelli, 2020). Sub-Saharan Africa is the only region globally that did

not show decreasing rates of ﬂood mortality since the 1990s (Tanoue

et al., 2016). Economic opportunities, transportation of goods and

services, and mobility and access to essential services, including health

and education, are greatly hindered by ﬂooding (Gannon etal., 2018).

Severe impacts from tropical cyclone landfalls have been recorded in

east and southeastern Africa (Rapolaki and Reason, 2018; Cambaza

Total people affected by climate hazards across Africa, 2010–2020

(a) Climate hazards between 2010–2020

(b) Total people affected by droughts

by convective storms

(d) Total people affected

by floods

(e) Total deaths from

tropical cyclones

(f) Total deaths

from heat waves

Floods

Tropical cyclones

Heat wave

Convective storm

Droughts

Climate hazards

12,000–1,000,000

1,000,001–2,000,000

2,000,001–3,500,000

3,500,001–5,000,000

5,000,001–10,200,000

Total people

affected

12–1,500

1,501–5,000

5,001–15,000

15,001–35,000

35,001–120,000

Total

people

affected

14–50,000

50,001–150,000

150,001–450,000

450,001–1,000,000

1,000,001–7,100,000

Total

people

affected

2–20

21–50

51–100

101–250

251–700

Total

deaths

11–15

16–50

51–150

Total

deaths

Figure9.27 | From 2010–2020, over 166million people were reported to be affected by climate hazards across Africa. Maps show

(a) location of all reported climate hazards;

(b) people affected by droughts;

(d) people affected by ﬂoods,

(e) total deaths from tropical cyclones, and

(f) total deaths from heat waves. Source: EMDAT and CRED (2020). Note: Although extreme weather damage databases under-report heatwaves (which is indicated in panel (f) by

very few deaths), the region has experienced a number of heatwaves and will be affected disproportionately by them in the future under climate change (Harrington and Otto, 2020).

1362

Chapter 9 Africa

Table9.7 | Case studies of climate hazard impacts and risks to selected human settlements in Africa

Hazard Country/City Impact on Human Settlement and Infrastructure Source

Sea level rise and

storm surge

Egypt

(North Africa)

December 2010, January 2011 and October 2015: Storm surge of 1.2 m.a.s. l. (metres above sea

level) (typical of the Nile Delta coast: 0.4–0.5 m). Coastal ﬂooding and damage to some coastal structures.

Moderate ﬂooding of the Nile Delta lowlands.

Alexandria city: Flooding generated by heavy rainfall (2015). Increased turbidity of water sources affected

efﬁciency of water treatment plants leading to reduction of water supplies affecting public health systems.

Potable water supply affected by saltwater intrusion. Coastal erosion and property damage.

Kloos and Baumert (2015);

Abutaleb etal. (2018)

Eldeberky Y (2015); Yehia etal.

(2017)

Drought

Southern Africa

El Niño drought, 2015–2016: Western Cape Region affected 8.6million people. Losses:

>USD2.2billion. Power generation reduced by 75% at Kariba dam (Zambia) in 2016, and the Cahora

Bassa dam (Mozambique) reduced to 34% of its capacity with widespread impact on electricity supplies

across southern Africa.

Davis-Reddy etal. (2017);

Spalding-Fecher etal. (2017)

Brooks (2019)

Somalia

(East Africa)

Somalia drought, 2016–2017: 926,000 newly displaced people reported (November 2016–October

2017). Around 40% of total drought-related displacements accommodated in Mogadishu, Baidoa,

Kismayo; 60% hosted in other secondary cities. Increased population density and overcrowding in

Somalia’s urban areas. Explosion of new shelters and tents for displaced persons within and in outskirts of

cities. In Mogadishu, 34% of new settlements developed within 6months.

Government of Somalia (2018)

Flooding

Malawi

(East Africa)

Floods, 2019: Approximately 975,600 people affected, 672 injured, 60 persons killed and 86,976 people

displaced. 288,371 houses damaged. 129 bridges and 68 culverts destroyed. Around 1841 km of road

network estimated at USD36.1million destroyed. Total cost of damage and losses: housing sector, USD

106.9million; energy, USD3.1million; water and sanitation, USD6.4million; transport, USD37.0million.

Total cost of destroyed physical assets, USD 157.7million. Damage and losses in Blantyre city: housing

sector, USD29.87million; energy sector, USD0.38million; transport sector, USD1.72million.

Government of Malawi (2019)

Tropical cyclone

Mozambique,

Zimbabwe and

Malawi (southern

Africa)

Cyclones Idai and Kenneth, 2019: Severe ﬂooding of districts in Mozambique, Zimbabwe, and Malawi;

233,900 houses completely destroyed or damaged in Mozambique.

Cyclone Kenneth: about 40,000 houses and 19 health facilities destroyed.

Cyclone Idai: destroyed or damaged 1345 km of transmission lines, 10,216 km of distribution lines, two

90 MW generation plants, 30 sub-stations and 4000 transformers, resulting in estimated damage of

USD133.5million and loss of USD47.9million in the energy sector in Mozambique. 602 and 299 people

killed in Mozambique and Zimbabwe, respectively; about 1.5million people affected in Mozambique and

270,000 in Zimbabwe.

In Beira (Mozambique), 60% of city was inundated, 70% of houses damaged or totally destroyed, mostly

in the poorest neighbourhood, and 90% of the city’s power grid affected. Huge losses and damages

to infrastructures in the energy, transport, water supply, communication services, housing, health and

education sectors were also recorded.

(Cambaza etal., 2019;

Chatiza, 2019; Government of

Mozambique, 2019; Hope, 2019;

Lequechane etal., 2020; Phiri

etal., 2021)

(Enenkel etal., 2020)

Landslide

Freetown

(West Africa)

August, 2017: At least 500 people killed and over 600 people declared missing, >3000 residents

rendered homeless; 349 houses destroyed. Damage to health facilities and educational buildings.

Economic cost of landslide and ﬂood, USD31.6million.

(Cui etal., 2019)

(World Bank, 2017b)

Uganda

(East Africa) Slopes of Mt Elgon, 2010: More than 350 deaths and 500,000 people needed to be relocated. (Croitoru etal., 2019)

etal., 2019; Chatiza, 2019; Hope, 2019). Cyclones Idai and Kenneth

in early 2019 caused ﬂooding of districts in Malawi, Mozambique and

Zimbabwe, with substantial loss and damage to infrastructure in the

energy, transport, water supply, communication services, housing,

health and education sectors, particularly in Mozambique (Figure9.27;

see also Cross-Chapter Box DISASTER in Chapter 4; Warren, 2019;

Dube etal., 2021; Phiri etal., 2021).

From 2005–2020, ﬂood-induced damage over Africa was estimated at

over USD4.4billion, with eastern and western Africa being the most

affected regions (EMDAT and CRED, 2020). Total damages in four west

African countries (Benin, Cote d’Ivoire, Senegal and Togo) in 2017 were

estimated at USD850 million for pluvial ﬂoods and USD555million

for ﬂuvial ﬂoods (Croitoru etal., 2019). Unprecedented economic loss,

in terms of goods and properties, estimated by the Nigerian insurance

industry at USD 200 million resulted from ﬂoods in Lagos in 2011

(Adelekan, 2016). In southern Africa, the highest costs were incurred

from ﬂood losses during the period 2000–2015 (UNEP-FI, 2019b;

Simpson, 2020).

Business disruptions from climate impacts have implications for

deepening poverty (Adelekan and Fregene, 2015). Small and medium

enterprises (SMEs) employ 60–90% of workers in many African

countries and contribute 40% or more to the GDP in Ghana, Kenya,

Nigeria, South Africa, Tanzania and Zimbabwe (Muriithi, 2017). The

viability of businesses and economic well-being of large populations

employed in SMEs is severely affected by climate hazards as reported for

local wind storms in Ibadan (Adelekan, 2012), El Niño-related ﬂooding

(Nairobi), drought-induced water supply disruption (Gaborone) and

power outages (Lusaka) (Gannon et al., 2018). High water demand

due to high rates of urbanisation and population growth, coupled with

drought, reduce groundwater levels in cities (e.g., Bouake, Harare,

Tripoli, Niamey) and increase saltwater intrusion into groundwater

in coastal areas, reducing water availability and water security,

1363

Africa Chapter 9

particularly for poorer populations not connected to municipal water

networks (Aswad etal., 2019; Claon etal., 2020).

Evidence of the impact of heat waves in urban Africa in the current

climate is sparse, due in part to low reporting and monitoring

(Engelbrecht etal., 2015; Harrington and Otto, 2020). Knowledge is

also limited on the interaction of climate change, urban growth and

the urban heat island effect in Africa (Chapman etal., 2017). In north

Africa, the present-day number of high heat stress nights is around

10times larger in urban than rural areas (Fischer etal., 2012).

9.9.2.2 Observed Impacts to Road and Energy Infrastructure

The highest transport infrastructure exposures are from ﬂoods (Koks

etal., 2019), with potentially severe consequences for food security

(Fanzo et al., 2018), communication and the economy of affected

regions (high conﬁdence) (Koks etal., 2019). Eight of the 20countries

with the highest expected annual damages to road and rail assets,

relative to the country’s GDP, are located in east, west and central

Africa (Koks etal., 2019). Transport impacts compound climate impacts,

such as heat stress and air pollution linked to vehicle emissions in Dar

es Salaam (Ndetto and Matzarakis, 2014).

African economies that rely primarily on hydropower for electricity

generation are particularly sensitive to climate variability (Brooks,

2019). This sensitivity was already felt during the 2015/16 El Niño,

in which Malawi, Tanzania, Zambia and Zimbabwe all experienced

widespread and prolonged load shedding due to low rainfall. The

impact was felt throughout the economy and reﬂected in reduced GDP

growth in Zambia (Conway etal., 2017).

9.9.3 Observed Vulnerabilities of Human Settlements to

Climate Risks

Urban vulnerabilities and exposure to climate change are increasing

(medium to high conﬁdence) and are inﬂuenced by patterns of urban

settlement and housing characteristics (Satterthwaite, 2017; Godsmark

etal., 2019; Williams etal., 2019a). About 70% of African cities are

highly vulnerable to climate shocks of which small- and medium-sized

towns and cities are more at risk (Verisk Maplecroft, 2018). Flooding

was perceived as the most prominent water risk in 75% of 36 sampled

cities across African sub-regions, while drought-related water scarcity

was indicated as very important/important in 66.7% of cities (OECD,

2021). Almost one-third of African cities with populations of 300,000

or more are located in areas of high exposure to at least one natural

hazard, including ﬂoods (11%) and droughts (20–25%) using natural

hazard data for the period 1970s to early 2000s (Gu etal., 2015). The

coastal cities of east, west and north Africa are particularly vulnerable

to the effects of rising sea levels (Abutaleb etal., 2018; IPCC, 2019a).

From 2000–2015, the proportion of people exposed to ﬂoods increased

for most African countries, with Mozambique and multiple countries in

West Africa estimated to have had the proportion of their populations

exposed to ﬂooding increase more than 50% (Tellman etal., 2021).

Globally, sub-Saharan Africa has the largest population living in

extreme poverty that are exposed to high ﬂood risk (~71 million

people or 55% of global total) (Rentschler and Salhab, 2020). Poverty

is a signiﬁcant factor of ﬂood-induced displacement in Africa, where

even small ﬂood exposure can lead to high numbers being displaced

(Kakinuma etal., 2020). Africa’s large population of urban poor and

marginalised groups and informal sector workers, further contribute

to high vulnerability to extreme weather and climate change in many

settlements (high conﬁdence) (Adelekan and Fregene, 2015; IPCC,

2019a; UNDP, 2019).

Other non-climatic stressors which exacerbate vulnerabilities, especially

in urban areas, include poor socioeconomic development, weak

municipal governance, poor resource and institutional capacities,

together with multi-dimensional, location-speciﬁc inequalities (high

conﬁdence) (Dodman etal., 2017; Satterthwaite, 2017).

9.9.4 Projected Risks for Human Settlements and

Infrastructure

9.9.4.1 Projected Risks for Human Settlements

The extent of urban areas in Africa exposed to climate hazards will

increase considerably and cities will be hotspots of climate risks, which

could amplify pre-existing stresses related to poverty, exclusion and

governance (high conﬁdence) (IPCC, 2018b).

9.9.4.1.1 Flooding

Continuing current population and GDP growth trends, the extent of

urban land exposed to high-frequency ﬂooding is projected to increase

around 270% in north Africa, 800% in southern Africa, and 2600%

in mid-latitude Africa by 2030 when compared to 2000, without

considering climate change (Güneralp etal., 2015). In addition, global

warming is projected to increase frequency and magnitude of river

ﬂoods in east, central and west Africa (Alﬁeri etal., 2017; Gu etal.,

2020; Kam etal., 2021). On average, across large African river basins,

the frequency of ﬂood events with a current return period of 100years

is projected to increase to 1 in 40 years at 1.5°C and 2°C global

warming, and 1 in 21years at 4°C warming, with Egypt, Nigeria, Sudan

and the Democratic Republic of Congo in the top 20countries globally

for projected damages (Alﬁeri etal., 2017). Compared to population in

2000, human displacement due to river ﬂooding in sub-Saharan Africa

is projected to increase 600% by 2066–2096 with moderate-to-high

population growth and 2.6°C global warming, with risk reducing to a

200% increase for low population growth and 1.6°C global warming

(Kam etal., 2021).

Urban population exposure to tropical cyclone hazards in southeastern

Africa, in particular Mozambique, is projected to increase due to the

intensiﬁcation of cyclones and their extended duration associated

with warmer sea surface temperatures (Fitchett, 2018; Vidya etal.,

2020). Urban damage assessment based on a 10-year ﬂood protection

level for Accra, Ghana, shows that without ﬂood protection, there is

a 10% probability of a ﬂood occurring annually which could cause

USD98.5million urban damage, affect GDP by USD50.3million and

affect 34,000 people (Asumadu-Sarkodie etal., 2015). Many urban

1364

Chapter 9 Africa

Current and future population exposed to sea level rise in low elevation coastal zone in Africa

Africa

Western Africa

Northern Africa

Eastern Africa

Central Africa

Southern Africa

Year 2000 Year 2030 (+10 cm sea level rise) Year 2060 (+21 cm sea level rise)

117.6

47.1

52.3

15.1

2.2

0.9

229.3

111.7

72.4

39.9

3.8

1.5

108.9

43.6

48.6

13.8

2.0

0.9

190.0

95.0

56.3

34.8

3.0

0.9

185.6

88.9

61.4

31.1

3.0

1.1

116.8

47.2

52.3

14.1

2.2

1.0

245.2

122.3

74.8

42.5

4.1

1.7

108.5

45.3

46.6

13.8

2.0

0.8

Baseline

54.2

17.1

30.3

5.2

1.1

0.5

Population growth scenarios:

A = growth at high end of forecasts

B = growth at lowest end of forecasts

C = growth at highest end of forecasts

D = growth at low end of forecasts

Population exposed to sea level rise

in low-elevation coastal zones (LECZ)

1 million

people

>200 million

people

Egypt

Nigeria

Senegal

Benin

Tanzania

Somalia

Cote d'Ivoire

Mozambique

(a) Population exposed to sea level rise in low elevation coastal zone (LECZ)

(b) African countries in the global top 25 with highest populations within LECZ and in the 100-year floodplains, under growth

scenario C

Populations within LECZ

Growth

2000–2060

0.25

0.79

0.66

1.06

2.2

1.68

0.64

0.33

Year

2030

45.0

19.8

8.5

5.4

2.8

2.2

3.0

4.4

Year

2060

63.5

57.7

19.2

15.0

14.0

9.8

7.6

7.5

Baseline

2000

25.5

7.4

2.9

1.4

0.6

1.2

2.3

Populations within 100-year floodplains

Year

2030

13.8

0.3

1.1

0.6

0.9

0.6

0.3

1.4

Baseline

2000

7.4

0.1

0.4

0.1

0.2

0.1

0.7

Growth

2000–2060

0.28

0.84

0.76

1.12

2.3

1.7

0.65

0.36

Year

2060

20.7

0.9

2.7

1.6

4.3

2.7

0.7

2.5

Once in 100-years floodplain

Mean sea level

Figure9.28 | Tens to hundreds of millions of people in Africa are projected to be exposed to sea level rise, with a major risk driver being increased exposure

due to population increase in low-lying areas.

(a) Population in the low-elevation coastal zone (LECZ) projected to be exposed to mean sea level rise (SLR) for 2030 (+10 cm SLR) and 2060 (+21 cm SLR). Scenarios A, C have

exclusive social, political and economic governance whereas scenarios B and D have inclusive social, political and economic governance.

(b) African countries with the highest projected population numbers in the LECZ, and also the additional population projected to be exposed in these countries due to a 1-in-100year

storm surge event. For panel b projections of population exposure used the high population growth socio-economic scenario (scenario C). Data sourced from Neumann etal. (2015).

households and Africa’s growing assets could therefore be exposed to

increased ﬂooding (IPCC, 2018b).

9.9.4.1.2 Sea level rise and coastal ﬂooding

Africa’s low-lying coastal zone population is expected to grow more

than any other region from 2000 to 2060 (see Figure9.28; Neumann

etal., 2015). Future rapid coastal development is expected to increase

existing high vulnerabilities to sea level rise (SLR) and coastal hazards,

particularly in east Africa (high conﬁdence) (Figure9.29; Hinkel etal.,

2012; Kulp and Strauss, 2019). By 2100, sea levels are projected to

rise at least 40 cm above those in 2000 in a below 2°C scenario, and

possibly up to 1 m by the end of the century under a 4°C warming

scenario (Serdeczny et al., 2017; see also Cross-Chapter BoxSLR in

Chapter 3).

In the absence of any adaptation, Egypt, Mozambique, and Nigeria

are projected to be worst affected by SLR in terms of the number of

people at risk of ﬂooding annually in a 4°C warming scenario (Hinkel

etal., 2012). Recent estimates have explored the potential damages

due to SLR and coastal extreme events in 12 major African cities using

a stochastic approach to account for uncertainty (Abadie etal., 2020).

The aggreate of expected average damages to these cities in 2050

is USD 65 billion for RCP4.5 and USD 86.5 billion for RCP8.5, and

USD137.5billion under a high-end scenario that incorporates expert

opinion on additional ice sheet melting with damages up to (Table9.8).

When considering low-probability, high-damage events, aggregate

damage risks can be more than twice as high, reaching USD187billion

and USD206billion under RCP4.5 and RCP8.5 scenarios, respectively,

and USD397billion under the high-end scenario. City characteristics

and exposure play a larger role in expected damages and risk than

changes in sea level. The city of Alexandria in north Africa leads the

1365

Africa Chapter 9

Selected regions at risk

of projected sea level rise

(a) Dar es Salaam, Bagamoyo and Stonetown (Tanzania)

(b) Lagos (Nigeria) and Cotonou and Porto-Novo (Benin) (c) Cairo and Alexandria (Egypt)

Present

day

2050

2100

50 km

Present day 2050 2100

50 km

(c)

(b) (a)

RCP2.6

RCP4.5

RCP8.5

Permanent

flooding

due to

sea level

rise

Present

sea level

Area built-up by 2014

Figure9.29 | Multiple large African cities will be exposed to sea level rise (SLR), these include the selected examples: (a) Dar es Salaam, Bagamoyo, and Stone

Town in Tanzania (east Africa), (b) Lagos in Nigeria, and Cotonou and Porto-Novo in Benin (west Africa) and (c) Cairo and Alexandria in Egypt (north Africa). Orange shows built-up

area in 2014. Shades of blue show permanent ﬂooding due to SLR by 2050 and 2100 under low (RCP2.6), intermediate (RCP4.5) and high (RCP8.5) greenhouse gas emissions

scenarios. Darker colours for higher emissions scenarios show areas projected to be ﬂooded in addition to those for lower emissions scenarios. The ﬁgure assumes failure of coastal

defences in 2050 and 2100. Some areas are already below current SLR and coastal defences need to be upgraded as SLRs (e.g., in Egypt), others are just above mean sea levels

and they do not necessarily have high protection levels, so these defences need to be built (e.g., Dar es Salaam and Lagos). Blue shading shows permanent inundation surfaces

predicted by Coastal Digital Elevation Model (DEM) and Shuttle Radar Topography Mission (SRTM) given the 95th percentile K14/RCP2.6, RCP4.5 and RCP8.5, for present day,

2050, and 2100 sea level projection for permanent inundation (inundation without a storm surge event), and RL10 (10-year return level storm) (Kulp and Strauss, 2019). Low-lying

areas isolated from the ocean are removed from the inundation surface using connected components analysis. Current water bodies are derived from the SRTM Water Body Dataset.

Orange areas represent the extent of coastal human settlements in 2014 (Corbane etal., 2018). See FigureCCP4.7 for projections including subsidence and worst-case scenario

projections for 2100.

1366

Chapter 9 Africa

Table9.8 | Regional relative sea level rise (SLR) for 2050 and 2100, and associated aggregated expected damage risks over the period 2020 to 2050 in 12 major African

coastal cities under four SLR scenarios. (a) Regional relative SLR by 2050 and 2100. For SLR, median and 95th percentiles are presented, in centimetres. (b) Probabilistic damage

estimations by 2050 include expected average damages (EAD), damages at the 95th percentile (value at risk; VaR) and the expected shortfall (ES), which represents the average

damages of the 5% worst cases. Four relative sea level projections were considered under no adaptation: the RCP2.6, 4.5 and 8.5 scenarios from the (IPCC, 2014a), and a high-end

RCP8.5 scenario that incorporates expert opinion on additional ice sheet melting. Note that ﬁgures are provided in undiscounted millions of US dollars (2005) and have been

rounded off to avoid a false sense of precision (Abadie etal., 2020; Abadie etal., 2021).

(a) Regional relative sea level rise (cm)

City Year RCP2.6 RCP4.5 RCP8.5 High-end

Median P95 Median P95 Median P95 Median P95

Abidjan 2050 21 30 22 32 24 34 28 48

2100 44 69 53 86 75 114 86 206

Alexandria 2050 18 26 18 28 21 30 25 43

2100 36 58 46 73 67 102 78 186

Algiers 2050 19 27 19 29 22 31 25 45

2100 39 62 47 76 66 98 78 192

Cape Town 2050 20 30 21 31 23 33 27 48

2100 44 69 53 87 75 117 86 199

Casablanca 2050 19 27 20 29 22 31 26 46

2100 39 63 47 78 65 99 77 198

Dakar 2050 21 31 21 31 23 33 27 48

2100 43 69 53 86 73 111 85 209

Dar es

Salaam

2050 20 29 21 31 24 33 27 47

2100 45 70 54 86 76 117 87 206

Durban 2050 20 30 22 32 25 34 28 49

2100 46 72 55 90 78 119 89 207

Lagos 2050 21 30 22 32 24 34 28 48

2100 44 69 54 86 75 113 86 205

Lome 2050 21 30 22 32 24 34 28 48

2100 44 69 53 86 76 115 87 205

Luanda 2050 21 30 23 32 25 35 29 49

2100 45 70 55 88 78 119 90 205

Maputo 2050 21 31 22 32 24 34 28 49

2100 45 71 55 89 78 120 89 209

(b) Expected average damages and risk measures (USD millions)

City RCP2.6 RCP4.5 RCP8.5 High-end scenario

EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%)

Abidjan 14,290 33,910 41,690 16,730 38,230 46,390 20,910 42,140 49,550 32,670 77,750 96,570

Alexandria 32,840 74,100 92,470 36,220 83,700 104,270 49,990 99,500 117,580 79,360 180,090 221,390

Algiers 270 620 760 300 700 870 390 810 960 640 1,540 1,920

Cape Town 110 310 400 130 360 450 170 410 490 300 800 1,010

Casablanca 350 1,150 1,520 420 1,340 1,740 610 1,570 1,930 1,230 3,590 4,630

Dakar 590 1,310 1,590 620 1,390 1,690 760 1,530 1,800 1,180 2,880 3,610

Dar es

Salaam 880 2,100 2,600 1,050 2,440 2,970 1,360 2,760 3,250 2,140 5,120 6,360

Durban 110 370 470 150 420 530 210 490 590 370 970 1,230

Lagos 3,680 6,790 7,950 4,200 7,660 8,930 4,920 8,270 9,420 6,750 13,820 16,730

Lome 3,230 10,480 13,460 4,280 12,580 15,780 5,980 14,430 17,380 10,720 28,580 36,010

Luanda 160 380 470 200 440 530 260 510 600 400 910 1,130

Maputo 650 1,990 2,530 700 2,080 2,620 980 2,410 2,910 1,790 4,830 6,110

Aggregate

damage

and risk

57,160 133,510 165,910 65,000 151,340 186,770 86,540 174,830 206,460 137,550 320,880 396,700

1367

Africa Chapter 9

ranking, with aggregate expected damage of USD 36 billion and

USD50billion under RCP4.5 and RCP8.5 scenarios, respectively, and

USD79.4billion under a high-end scenario.

Sea level rise and associated episodic ﬂooding are identiﬁed as key

drivers of projected net migration of 750,000 people out of the east

African coastal zone between 2020 and 2050 (IPCC, 2019a). These

trends, alongside the emergence of ‘hotspots’ of climate in- and

out-migration (Box 9.8), will have major implications for climate-

sensitive sectors and the adequacy of human settlements, including

urban infrastructure and social support systems. Actions which could

help reduce the number of people being forced to move in distress,

include adoption of inclusive and CRD policies, together with

targeted investments to manage the reality of climate migration; and

mainstreaming climate migration in development planning (Box9.8).

9.9.4.1.3 Drought

Although an increase in drought hazard is projected for north and

southwest southern Africa with increased global warming (Figure9.15),

central African countries may have the highest drought risk because of

high vulnerability and high population growth (Ahmadalipour et al.,

2019). Among continents, Africa contains the second largest population

of people living in drylands, which is expected to double by 2050

(IPCC, 2019a). Continuing current population and GDP growth trends,

the extent of urban land in arid zones is projected to increase around

180% in southern Africa, 300% in north Africa and 700% in mid-latitude

Africa by 2030 when compared to 2000, without considering climate

change (Güneralp etal., 2015). At 1.5°C warming, urban populations

exposed to severe droughts in west Africa are projected to increase

(65±34 million) and increase further at 2°C (IPCC, 2018b; Liu et al.,

2018b). Risks associated with increases in drought frequency and

magnitudes are projected to be substantially larger at 2°C than at 1.5°C

for north Africa and southern Africa (IPCC, 2018b; Oppenheimer etal.,

2019). Dryland populations exposed (vulnerable) to water stress, heat

stress, and desertiﬁcation are projected to reach 951 (178) million at

1.5°C, 1152 (220) million at 2°C, and 1285 (277) million at 3°C of global

warming (IPCC, 2019a). At global warming of 2°C under a scenario

of low population growth and sustainable development (SSP1), the

exposed (vulnerable) dryland population is 974 (35) million and for

higher population growth and low environmental protections (SSP3) it

is 1.27billion (522million), a majority of which is in west Africa (IPCC,

2019a).

9.9.4.1.4 Extreme heat

Projections for 173 African cities show that around 25 cities will have

over 150days per year with an apparent temperature above 40.6°C for

1.7°C global warming, increasing to 35 cities for 2.1°C and 65 cities

for 4.4°C warming, with west African cities most affected (Rohat etal.,

2019). Across Africa, urban population exposure to extreme heat was

estimated to be 2billion person-days per year above 40°C for 1985–

2005 (that is the annual average number of days with a maximum

temperature above 40.6°C multiplied by the number of people exposed

to that temperature), but this is expected to increase to 45billion

person-days for 1.7°C global warming with low population growth

(SSP1), and to 95 billion person-days for 2.8°C and medium-high

population growth (SSP4) by the 2060s, with increases of 20–52times

1985–2005 levels by 2080–2100, depending on the scenario (Rohat

etal., 2019). West Africa (especially Nigeria) has the highest absolute

exposure and southern Africa the least. Considering the urban heat

island effect, the more vulnerable populations under 5 and over 64

exposed to heat waves of >15days over 42°C are projected to increase

from 27million in 2010 to 360 million by 2100 for low population

growth (SSP1) with 1.8°C global warming, increasing to 440million for

low population growth (SSP5) with >4°C global warming, with west

Africa most affected (Marcotullio etal., 2021). This portends increased

vulnerability to risk of heat stress in big cities of central, east and west

Africa (very high conﬁdence) (Gasparrini etal., 2015; Liu etal., 2017;

Rohat etal., 2019). Shifting to a low urban population growth pathway

is projected to achieve a greater reduction in aggregate exposure to

extreme heat for most cities in west Africa, whereas limiting warming

through lower emissions pathways achieves greater reductions in

exposure in central and east Africa (Rohat etal., 2019).

The African population exposed to compound climate extremes,

such as coincident heat waves and droughts or drought followed

immediately by extreme rainfall, is projected to increase 47-fold

by 2070–2099 compared to 1981–2010 for a scenario with high

population growth and 4°C global warming (SSP3/RCP8.5) and only

12-fold for low population growth and 1.6°C global warming (SSP1/

RCP2.6), with west, central-east, northeastern and southeastern Africa

especially exposed (Weber etal., 2020). Coincident heat waves and

drought is the compound event to which the most people are projected

to be exposed: ~1.9billion person-events (a 14-fold increase) for SSP1/

RCP2.6 and ~7.3 billion person-events (52-fold increase) for SSP3/

RCP8.5 (Weber etal., 2020).

9.9.4.2 Projected Risks to Electricity Generation and Transmission

Climate change poses an increased risk to energy security for human

settlements in Africa (high conﬁdence). With burgeoning urban

populations and growing economies, sub-Saharan Africa’s electricity

needs are growing. The International Energy Agency (IEA) projects

total generation capacity in Africa must grow 2.5times from 244 GW

in 2018 to 614 GW by 2040 (IEA, 2019). African nations plan to add

signiﬁcant generation capacity from natural gas, hydropower, wind

and solar power. Each of these technologies is associated to a varying

degree with climate risk.

The long lifespan of hydropower dams exposes them to decades of

climatic change risk. There is a wide range of uncertainty around the

future climate of Africa’s major river basins, but in several basins,

there is the likelihood of increased rainfall variability and a drier

climate (see Box9.5). In countries that rely primarily on hydropower,

climate change could have considerable impacts on electricity prices

and as a result, consumers’ expenditure (Sridharan etal., 2019). With

increasing societal demands on limited water resources and future

climate change, it is expected that there will be an intensiﬁcation

of WEF competition and trade-offs (high conﬁdence) (Section9.7;

Box9.5).

1368

Chapter 9 Africa

9.9.4.3 Projected Risks to Road Infrastructure

Climate change and SLR will result in high economic costs for road

infrastructure in sub-Saharan Africa (medium conﬁdence) (Chinowsky

etal., 2015). Across Africa as a whole, potential cumulative costs

estimates through 2100 range from USD 183.6 billion (with

adaptation) to USD 248.3 billion (no adaptation) to repair and

maintain existing roads damaged by temperature and precipitation

changes directly related to projected climate change (see Figure9.30)

(Chinowsky etal., 2013). Climate-related road damage and associated

repairs will be a signiﬁcant ﬁnancial burden to countries, but to

varying degrees according to ﬂood risk, existing road asset liability,

topography and rural connectivity, among other factors (Chinowsky

etal., 2015; Cervigni et al., 2017; Koks etal., 2019). For example,

Mozambique is projected to face estimated annual average costs

of USD 123 million for maintaining and repairing roads damaged

directly by precipitation and temperature changes from climate

change through 2050 in a median climate change scenario for a

policy that does not consider climate impacts during road design

and construction (Chinowsky etal., 2015). Risk of river ﬂooding to

bridges in Mozambique under current conditions is estimated to be

USD200million, equal to 1.5% of its GDP per year, and could rise to

USD400million per year in the worst-case climate change scenario

by 2050 (Schweikert etal., 2015).

9.9.5 Adaptation in Human Settlements and for

Infrastructure

9.9.5.1 Solutions and Residual Risk Observed in Human

Settlements

Autonomous responses to climate impacts in 40 African cities show

that excess rainfall is the primary climate driver of adaptation, followed

by multi-hazard impacts, with 72% of responses focused on excess

rainfall (Hunter etal., 2020). Innovation for adaptation in areas such

as home design, social networks, organisations and infrastructure, is

evident (Swanepoel and Sauka, 2019). Social learning platforms also

increase communities’ adaptive capacities and resilience to risk (Thorn

etal., 2015).

There is limited evidence of successful, proactively planned climate

change adaptation in African cities (Simon and Leck, 2015), particularly

for those countries highly vulnerable to climate change (Ford etal.,

2014). Planned adaptation initiatives in African cities since 2006 have

been predominantly determined at the national level with negligible

participation of lower levels of government (Ford et al., 2014).

Adaptation action directed at vulnerable populations is also rare (Ford

etal., 2014). There are emerging examples of cities planned climate

adaptation measures, such as those advanced by Durban (Roberts,

2010), Cape Town (Taylor etal., 2016) and Lagos (Adelekan, 2016). There

are also examples of community-led projects such as those in Maputo

(Broto etal., 2015), which have seen meaningful help from a range of

policy networks, dialogue forums and urban learning labs (Pasquini and

Cowling, 2014; Shackleton etal., 2015). These researched cities can be

lighthouses for wider exchange and the basis for a deeper synthesis of

evidence (Lindley etal., 2019). However, planned adaptation progress is

slow, especially in west and central Africa (Tiepolo, 2014).

Ecosystem-based approaches are also being deployed in mitigating

and adapting to climate change, with demonstrated long-term health,

ecological and social co-beneﬁts (Section9.6.4; Swanepoel and Sauka,

2019). The cost–beneﬁt analysis of nature-based solutions, compared

to purely grey infrastructure initiatives, is discussed in Chapter 6

(Section 6.3.3). Nature-based solutions can also lengthen the life of

existing built infrastructure (du Toit etal., 2018). Since 2014, an increasing

number of EbA projects involving the restoration of mangrove, wetland

and riparian ecosystems have been initiated across Africa, a majority of

which address water-related climate risks (Table9.9).

For green infrastructure to be successful, however, sustainable landscapes

and regions require both stewardship and management at multiple

levels of governance and social scales (Brink etal., 2016).

Currently, planned climate change adaptation to coastal hazards

in Africa’s large coastal cities has mainly been achieved through

expensive coastal engineering efforts such as sea walls, revetments,

breakwaters, spillways, dikes and groynes. Examples are found in

west Africa (Adelekan, 2016; Alves etal., 2020). Beach nourishment

efforts have also been undertaken in Egypt, Banjul and Lagos (Frihy

etal., 2016; Alves etal., 2020). However, the use of vegetated coastal

ecosystems presents greater opportunities for African cities because of

the lower costs (Duarte etal., 2013).

Projected costs for repair and maintenance of

pre-2011 road infrastructure as a result of projected

climate-change-related damages

05% 10% 15% 20% 25% 30%

Proportion of 2011 GDP

Max of

22 SRES

scenarios

Sub-Saharan Africa

Mozambique

Tanzania

Ethiopia

Côte d'Ivoire

Morocco

Democratic Republic

of Congo

Niger

Algeria

Mali

Namibia

87%

Median

Figure9.30 | Projected costs for repair and maintenance of pre-2011 road

infrastructure in selected African countries as a result of projected climate-

change-related damages due directly to precipitation and temperature

changes through to 2100. Data sources: Chinowsky etal. (2013). The analysis was

run for 22 SRES climate scenarios and the median, and maximum results of the analyses

are represented as proportions of the 2011 GDP of each country.

1369

Africa Chapter 9

Table9.9 | Examples of ecosystem-based adaptations to climate impacts in African cities.

Project City Ecosystem-based Adaptation Reference

Green Urban Infrastructure Beira (Mozambique)

Mitigating against increased ﬂood risks through restoration of mangrove and

other natural habitats along the Chiveve river and the development of urban

green spaces.

IPCC (2019a); CES Consulting

Engineers Salzgitter GmbH

and Inros Lackner SE (2020)

The Msimbazi Opportunity Plan (MOP)

2019–2024 Dar es Salaam, Tanzania Enhancing urban resilience to ﬂood risk by reducing ﬂood hazard, and

reducing people, properties and critical infrastructure exposed to ﬂood hazard. Croitoru etal. (2019)

Tanzania Ecosystem-based Adaptation Dar es Salaam and ﬁve

coastal districts, Tanzania Rehabilitation of over 3000 ha of climate-resilient mangrove species. UNEP (2019)

Building Resilience in the Coastal Zone

through Ecosystem-based Approaches

to Adaptation

Maputo, Mozambique Restoration of mangrove and riparian ecosystems for ﬂood control and

protection from coastal ﬂooding enhanced water supply. GEF (2019)

Addressing Urgent Coastal Adaptation

Needs and Capacity Gaps in Angola

Five coastal communities

in Angola

Restoration of 561 ha of wetland, mangroves and other ecological habitats to

promote ﬂood defence and mitigate the threat of drought. UNEP (2020)

Green City Kigali

2016 Kigali, Rwanda Planned neighbourhood of 600 ha, integrating green building and design,

efﬁcient and renewable energy, recycling and inclusive living. SWECO (2019)

Urban Natural Assets for Africa—Rivers

for Life Kampala, Uganda Preservation of natural buffers to enhance the protective functions offered by

natural ecosystems that support disaster resilience beneﬁt. World Bank (2015)

Most (>80%) of Africa’s large coastal cities have no adaptation

policies and, where available, these are mostly, except for South

Africa, dominated by national plans (Olazabal etal., 2019). Coastal

adaptation actions minimally consider socioeconomic projections and

are not at all aligned with future climate scenarios and risks, which is

highly limiting for adaptation planning (Olazabal etal., 2019).

9.9.5.2 Anticipated Adaptation and Residual Risk for Human

Settlements

Africa’s smaller towns and cities have received far less scholarly and

policy development attention for adaptation (Clapp and Pillay, 2017;

White and Wahba, 2019). Smaller towns also have less ability to partner

effectively with private entities for adaptation initiatives (Wisner etal.,

2015). Political will to address climate change and information ﬂows

between key stakeholders, professional and political decision makers

may be easier to establish in smaller cities than in the megacity context

(Wisner etal., 2015).

Exposure and vulnerability are particularly acute in informal areas,

making coordinated adaptation challenging. Yet, there is growing

recognition of the potential for bottom-up adaptation that embraces

informality in order to more effectively reduce risk (Figure9.31; Taylor

etal., 2021a). This can provide an opportunity for change towards more

risk-sensitive urban development and transformative climate adaptation

(Leck etal., 2018). Addressing social vulnerability is particularly important

for ensuring the resilience of populations at risk. Improved monitoring,

modelling and communication of climate risks is needed to reduce the

impacts of climate hazards (Tramblay etal., 2020; Cole etal., 2021a).

9.9.5.3 Anticipated Adaptation for Transport Systems in Africa

Higher costs will be incurred to maintain and repair damages caused

to existing roads as a result of climate change for countries with no

adaptation policy for transport infrastructure (very high conﬁdence)

(Chinowsky et al., 2013; Cervigni et al., 2017; Koks et al., 2019).

Countries with a greater percentage of unpaved roads will, however,

incur higher economic costs through adaptation policy when compared

to no adaptation policy (Cervigni etal., 2017).

Adaptation measures in the transport sector have focused on the climate

resilience of road infrastructure. Modelling suggests that proactive

adaptation of road designs to account for temperature increases is a

‘no regret’ option in all cases, but accounting for precipitation increases

should be assessed on a case-by-case basis (medium conﬁdence)

(Cervigni etal., 2017). African governments will need climate adaptation

ﬁnancing options to meet the higher capital requirements of resilient

road infrastructure interventions (Hearn, 2016).

Under the Nationally Appropriate Mitigation Action programme,

investments in public transport and transit-oriented development are

highlighted as desired mitigation–adaptation interventions within

cities of South Africa, Ethiopia and Burkina Faso (UNFCCC, 2020).

These interventions simultaneously reduce the vulnerability of low-

income residents to climate shocks, prevent lock-ins into carbon-

intensive development pathways and reduce poverty (high conﬁdence)

(Hallegatte et al., 2016; Rozenberg et al., 2019). The combined

mitigation–adaptation interventions in the land use transport systems

of African cities are also expected to have sufﬁcient short-term co-

beneﬁts (reducing air pollution, congestion and trafﬁc fatalities) to be

‘no regret’ investments (very high conﬁdence) (Hallegatte etal., 2016;

Rozenberg etal., 2019). Only eight African countries have transport-

speciﬁc adaptation measures in their NDCs (Nwamarah, 2018). Five

African countries have submitted NAPs (Table9.10).

9.9.5.4 Projected Adaptation for Electricity Generation and

Transmission in Africa

Most electricity infrastructure in Africa has been designed to account

for historical climatic patterns. Failure to consider future climate

scenarios in power system planning increases the climate risk facing

infrastructure and supplies. Yet, energy demand for cooling over Africa,

for example, is expected to increase, with a potential increase in heat

stress, population growth and rapid urbanisation to 1.2% of total ﬁnal

1370

Chapter 9 Africa

Table9.10 | Transport sector references in the National Adaptation Plans (NAPs) of ﬁve African countries. Source: Government of Burkina Faso (2015); Government of Cameroon

(2015); Government of Togo (2016); Government of Kenya (2017); Government of Ethiopia (2019).

Country Identify climate

change impacts

Promote transport

as a disaster risk

reduction measure

Transport-speciﬁc adaptation measures

Climate-resilient

design standards

Promote public

transport

Promote non-mo-

torised transport

Urban land use

planning

Burkina Faso X X X X

Cameroon X X

Ethiopia X X X X

Kenya X

Togo X X

Key elements of adaptation in informal settlements in Africa

Hazard

Climate hazard affecting the highest

number of people per country (2000–2019)

Vulnerability context of

informal settlements in Africa

Currently:

• 189 million people (59%) of urban population live in

informal settlements

• 72% of non-agricultural employment in the informal sector

• 78%

of residential areas developed between 1990 and 2014

Projected:

•Cost of water, electricity and transport delays USD300

million per year

• 3x urban population by 2050

• 4x physical footprint by 2050

•Africa needs to spend USD 130–170 million per year on

basic infrastructure delivery

• 1.2 billion people will live in informal settlements by 2050

Vulnerability

•Ecosystem-based

measures to reduce

riparian and coastal

flooding

•Mangroves alleviate

coastal storm energy

•Water reservoirs to

buffer low-flows and

water scarcity

•Comprehensive in situ

community upgrading

•Ameliorate flood desert

conditions

•Actions to reduce

discrimination

•High quality health care

•Insurance

•Clarification of land

tenure

•Risk sensitive land use

planning

•Early warning systems

•Evacuation routes

•Maintained storm

surface drains

•Hazard proof housing

infrastructure

•Transport

infrastructure

Adaptation

pathways

Such as,

•Pooling (e.g.

knowledge, care,

space, income and

labour

•Diversification of

livelihoods

•Mobility/migration

•Rationing over

time/community saving

schemes

•Intensification (e.g.

crop production)

•Material and symbolic

exchange

•Innovation and

reconfiguration of

ideologies

•Cooling spaces during

heatwaves

•Access to clean

drinking water and

sanitation

•Effective Disaster

Risk Reduction

•Access to clean,

reliable renewable

energy

•Watershed

management

•Physical

•Ecological

•Technological

•Economic

•Political

•Institutional

•Psychological and/or

socio-cultural

Drought

Extreme temperature

Flood

Storm

Vulnerability

Exposure

Response

Risk

Hazard

Actions to

reduce Hazards

Actions to

reduce Exposure

Actions to

reduce Vulnerability

Limits to

adaptation

Actions to

reduce Risks

Figure9.31 | Key elements of adaptation in informal settlements in Africa. Adapted from Thorn etal. (2015); Fedele etal. (2019); Satterthwaite etal. (2020).

energy demand by 2100 compared to 0.4% in 2005 (Parkes et al.,

2019). Integrated energy system costs from increased demand for

cooling to mitigate heat stress are projected to accumulate from 2005

to USD51.3billion by 2035 at 2°C and to USD486.5billion by 2076 at

4°C global warming (Parkes etal., 2019).

For hydropower, adaptations to different climate conditions can

be made at the level of the power plant, turbine size and reservoir

storage capacities, and can be adjusted to projected hydrological

patterns (Lempert et al., 2015). At the river basin level, integrated

water resource management practices can be implemented across

1371

Africa Chapter 9

sectors that compete for the same water resources (Howells etal.,

2013). At the power system level, the energy mix and the protocol

through which different power plants are dispatched can be adapted

to different climate scenarios (Spalding-Fecher etal., 2017; Sridharan

etal., 2019).

Given the uncertainty around future hydroclimate conditions,

hydropower development decisions carry risk of ‘regrets’ (that is,

damages or missed opportunities) when a different climate than was

expected materialises. ‘Robust adaptation’ refers to an adaptation

strategy that balances risks across different climate scenarios (Cross-

Chapter BoxDEEP in Chapter 17; Cervigni etal., 2015). Development

bank lending principles require consideration of the regional picture

and interactions with other developments along a river when they

determine the social and environmental impacts of the proposed

hydropower project. However, these principles often do not explicitly

consider climate change, so the risk of recurring drought-induced

hydropower shortages could be missed (Box9.5).

Lastly, given the degree to which hydropower competes with other

sectors and ecosystems for the same water resources, it is critical

that hydropower planning and adaptation does not occur in isolation.

As discussed in Section9.7, it must be part of an integrated water

management system that balances the needs of different water-reliant

sectors with other societal and ecological demands under increasingly

variable climate and hydrological conditions (Section9.7.3).

9.10 Health

The health section is organised by disease or health outcome, with

observed impacts and projected risks described for each condition. All

adaptation options are presented at the end of the section, highlighting

prevention and preparedness, community engagement and disease-

speciﬁc adaptation options.

9.10.1 The Inﬂuence of Social Determinants of Health on

the Impacts of Climate Change

The social determinants of health are ‘the conditions in which people

are born, grow, live, work and age’ as well as the drivers of these,

including the social circumstances which profoundly affect health

and drive health disparities (Commission of Social Determinants of

Health, 2008; Gurewich etal., 2020). Social features (e.g., health-

related behaviours), socioeconomic factors (e.g., income, wealth and

education) and environmental determinants (e.g., air or water quality)

are critical for shaping health outcomes. These factors are inextricably

Observed climate change impacts and projected risks across African regions for eight key health outcomes

Impact

or risk

People

exposed

Number

of cases

Number

of deaths

Increase in

incidence

(cases/

deaths)

Increase in

population

at risk

Very high >10 million >100,000 >3,000 >10% 31–50% >100

High >1 million >10,000 >1,000 >7% 21–30% >50

Moderate >100,000 >1,000 >500 >5% 11–20% >10

Cost

(million USD)

Health outcomes

per region

Northern

Central

Eastern

Western

Southern

Air

pollution-

Low >1,000 >100 >100 >2% 5–10% >1

Reduced >1,000 >100 >100 >2% 5–10% >1

Negligible –––– –––

Northern

Central

Eastern

Western

Southern

Malaria

Northern

Central

Eastern

Western

Southern

Dengue

and Zika

Northern

Central

Eastern

Western

Southern

Cholera

Northern

Central

Eastern

Western

Southern

Diarrhoeal

disease

Northern

Central

Eastern

Western

Southern

HIV

Northern

Central

Eastern

Western

Southern

All-cause mortality

attributed to non-

optimal temperatures

Northern

Central

Eastern

Western

Southern

Heat-related

illness and

mortality

Key for criteria used to define the severity of observed impact or projected risk for each health outcome

= Insufficient evidence availableEmpty

Confidence level

Very

high

Projected risk

per global warming level

Medium

= Conflicting result

Low High

>1°C

>1.5°C

>3°C

>4°C

>2°C

–

Observed

Observed impact

Figure9.32 | Risks to health in Africa increase with increasing global warming. Observed climate impacts and projected climate change risks across African regions

for eight key health outcomes. Global warming levels shown refer to increases relative to pre-industrial values (1850–1900). This list of health impacts and risks is not intended

to be exhaustive, but instead focuses on well-documented conditions. This assessment is a synthesis across 58studies on observed impacts and 29studies on projected risks for

health (see TableSM 9.7). The category of air pollution-related health outcomes includes health impacts from changing particulate matter concentrations due to climate change.

1372

Chapter 9 Africa

linked (Schulz and Northridge, 2004; Moore and Diaz, 2015) and are

largely outside the domain of the health sector. Climate change is

already challenging the health and well-being of African communities,

compounding the effects of underlying inequalities (high conﬁdence).

The interlinkage between climate change and social determinants of

health are largely discussed at a global level (Commission of Social

Determinants of Health, 2008), or for developed countries (Ahdoot

et al., 2015; Levy and Patz, 2015; Department of Economic and

Social Affairs, 2016), with scant evidence for Africa. Nevertheless,

there is robust evidence that the health impacts of climate change

disproportionately affect the poorest people and children and, in some

situations, can differ by gender and age (St Louis and Hess, 2008;

Nyahunda etal., 2020; Ragavan etal., 2020; see Box 9.1). Unequal

access to health care particularly affects rural communities (Falchetta

etal., 2020), vulnerable women and children (Wigley et al., 2020a)

and challenges the achievement of development priorities such as

universal health care access (SDG 3) (Weiss etal., 2020).

9.10.2 Observed Impacts and Projected Risks

Climate change is already impacting certain health outcomes in

Africa (e.g. temperature-related mortality) and risks for most (but

not all) health outcomes are projected to increase with increasing

global warming (Figure9.32), with young children (<5years old), the

elderly (>65years old), pregnant women, individuals with pre-existing

morbidities, physical labourers and people living in poverty or affected by

other socioeconomic determinants of health being the most vulnerable

(high conﬁdence). Women may be more vulnerable to climate change

impacts than men (Chersich etal., 2018; Jaka and Shava, 2018; Adzawla

etal., 2019a). Contextualising projected impacts of climate change on

health requires an understanding of observed impacts (Figure9.32).

Without management and mitigation, current and projected morbidities

and mortalities will put additional strain on health, social and economic

systems (Hendrix, 2017; Alonso etal., 2019).

9.10.2.1 Vector-borne Diseases

9.10.2.1.1 Malaria

Observed impacts

Higher temperatures and shifting patterns of rainfall inﬂuence the

distribution and incidence of malaria in sub-Saharan Africa (high

conﬁdence) (Agusto et al., 2015; Beck-Johnson et al., 2017). Up to

10.9million km2 of sub-Saharan Africa is optimally suitable for year-round

malaria transmission (Mordecai etal., 2013; Ryan etal., 2015). Current

climate suitability for endemic malaria transmission is concentrated in

the central African region, some areas along the southern coast of west

Africa and the east African coast (Ryan etal., 2020).

In east Africa, there has been an expansion of the Anopheles vector

into higher altitudes (Gone et al., 2014; Carlson et al., 2019) and

increasing incidence of infection with Plasmodium falciparum with

higher temperatures (high conﬁdence) (Alemu etal., 2014; Lyon etal.,

2017). Over southern Africa, changes in temperature and rainfall are

increasing malaria transmission (Abiodun etal., 2018). In west Africa,

studies show both positive (Adu-Prah and Koﬁ Tetteh, 2015; Darkoh

etal., 2017) and negative (M’Bra etal., 2018) correlations of malaria

incidence with increases in mean monthly temperatures, and an

abundance of Anopheles gambiae s.s. associated with mean diurnal

temperature (Akpan etal., 2018).

Malaria incidence and outbreaks in east Africa were linked with both

moderate monthly rainfall and extreme ﬂooding (Boyce etal., 2016;

Amadi et al., 2018; Simple et al., 2018), and increase 1–2months

after periods of rainfall in southern and west Africa (Diouf et al.,

2017; Ferrão etal., 2017; Adeola etal., 2019). The years following La

Niña events (southern Africa) (Adeola etal., 2017)) and high relative

humidity (west Africa) (Adu-Prah and Koﬁ Tetteh, 2015; Darkoh etal.,

2017) have been positively linked with malaria incidence.

Projected risks

Since AR5, signiﬁcant progress has been made in understanding how

changes in climate inﬂuence the seasonal and geographical range

of malaria vectors, transmission intensity and burden of disease of

malaria across Africa. Yet projecting changes remains challenging given

the range of factors that inﬂuence transmission and disease patterns,

and model outputs contain high degrees of uncertainty (Zermoglio

etal., 2019; Giesen etal., 2020). Models have limited ability to account

for population changes and development trends (Kibret etal., 2015;

2017), investments in health sectors and interventions (McCord, 2016;

Colborn etal., 2018; Caminade etal., 2019), and confounders such as

age, socioeconomic status, employment, labour migration and climate

variability (Bennett etal., 2016; Karuri and Snow, 2016; Byass etal.,

2017; Chuang etal., 2017; Colborn etal., 2018). Nevertheless, available

models do allow for projections of malaria transmission under different

climate change scenarios to be made with high levels of certainty.

In east and southern Africa and the Sahel, malaria vector hotspots

and prevalence are projected to increase under RCP4.5 and RCP8.5 by

2030 (1.5°C–1.7°C global warming) (high conﬁdence) (Leedale etal.,

2016; Semakula etal., 2017b; Zermoglio et al., 2019), becoming more

pronounced later in the century (2.4°C–3.9°C global warming) (Ryan

et al., 2020). Under RCP4.5, 50.6–62.1 million people in east and

southern Africa will be at risk of malaria by the 2030s (1.5°C global

warming), and 196–198million by the 2080s (2.4°C global warming)

(Ryan etal., 2020). Northern Angola, southern DRC, western Tanzania and

central Uganda are predicted to be worst impacted in 2030, extending

to western Angola, upper Zambezi River basin, northeastern Zambia

and the east African Highlands by 2080 (Ryan etal., 2020). Under rising

temperatures, by the 2050s, the greatest shifts in suitability for malaria

transmission will be seen in east, southern and central Africa (2°C global

warming) (Tonnang etal., 2014; Zermoglio etal., 2019; Ryan etal., 2020).

Conversely, in some regions, changing climatic conditions are projected

to reduce malaria hotspots and prevalence. With continued GHG

emissions, these include: west Africa by 2030 (1.7°C global warming)

(high conﬁdence) (Yamana etal., 2016; Semakula et al., 2017b; Ryan

etal., 2020), parts of southern central Africa and dryland regions in east

Africa by 2050 (2.5°C global warming) (high conﬁdence) (Semakula

etal., 2017b; Ryan et al., 2020) and large areas of southern central

Africa and the western Sahel by 2100 (>4°C global warming) (Yu etal.,

1373

Africa Chapter 9

2015; Tourre etal., 2019). These reductions in transmission correspond

with decreasing environmental suitability for the malaria vector and

parasite in these regions (Ryan etal., 2015; Mordecai etal., 2020). Most

areas in Burkina Faso, Cameroon, Ivory Coast, Ghana, Niger, Nigeria,

Sierra Leone, Zambia and Zimbabwe will have almost zero malaria

transmission under RCP8.5 (Semakula etal., 2017b; Tourre etal., 2019).

The ENSO cycle currently contributes to seasonal epidemic malaria in

epidemic-prone areas (high conﬁdence), and is projected to shift the

malaria epidemic fringe southward and into higher altitudes by mid-

to end-century (high conﬁdence) (Bouma etal., 2016; Semakula etal.,

2017b; Caminade etal., 2019). More evidence is needed, however, of

climate variability impacts through ENSO cycles in future risk projections,

as well as a deeper understanding of how climate change will impact

the length of transmission season for mosquitoes, particularly in areas

where increases in spring and autumn temperatures may increase

suitability for the reproduction of malaria vectors (Ryan etal., 2020).

Other gaps in knowledge include a better understanding of mosquito

thermal biology and thermal limits for a variety of species, potential

adaptations to extreme temperatures and how landscape changes

contribute to malaria transmission (Tompkins and Caporaso, 2016).

9.10.2.1.2 Mosquito-borne viruses

Observed impacts

Climate variability has driven a global intensiﬁcation of mosquito-

borne viruses (e.g., dengue, Zika and RVF), including expansion into

areas with higher altitudes (Leedale etal., 2016; Mweya etal., 2016;

Messina et al., 2019). Concerns centre on diseases vectored by the

yellow fever mosquito (Aedes aegypti), common throughout most

of sub-Saharan Africa, and the tiger mosquito (Aedes albopictus),

currently largely conﬁned to western central Africa (Kraemer etal.,

2019; Mordecai etal., 2020).

Although warming temperatures are largely responsible for increasing

environmental suitability for mosquito vectors (Mordecai et al.,

2019), droughts can augment transmission when open water storage

provides breeding sites near human settlements, and when ﬂooding

enables mosquitoes to proliferate and spread viruses further (Mweya

etal., 2017; Bashir and Hassan, 2019). Within Africa’s rapidly growing

cities, diseases vectored by urban-adapted Aedes mosquitoes pose a

major threat, especially in west Africa (Zahouli etal., 2017; Weetman

etal., 2018; Messina etal., 2019). Dengue virus expansion may cause

explosive outbreaks but the burden of dengue haemorrhagic fever and

associated mortality is higher in areas where transmission is already

endemic (Murray etal., 2013).

Projected risks

Populations of Aedes aegypti and Aedes albopictus mosquitoes and

epidemics of dengue and yellow fever and other Aedes-borne viruses

are expected to increase, including at high altitudes (Weetman etal.,

2018; Messina etal., 2019; Ryan etal., 2019; Gaythorpe etal., 2020;

Mordecai etal., 2020). Aedes albopictus may expand beyond western

central Africa into Chad, Mali and Burkina Faso by mid-century at

>2°C global warming (Kraemer etal., 2019). Shifts projected in Aedes

range due to changing environmental suitability, combined with rapid

urbanisation and population growth, suggest that by 2050 populations

exposed to these vectors in Africa may double, and by 2080 nearly

triple at >2°C global warming (Kraemer etal., 2019). Southern limits

of dengue transmission in Namibia and Botswana, and the western

Sahel, may show the greatest expansions in environmental suitability

under 1.8°C–2.6°C global warming (Messina et al., 2019). In the

warmest scenarios (RCP8.5), however, some parts of central Africa

may become too hot for mosquitoes to transmit dengue, and thus

at-risk populations may peak at intermediate warming levels (Ryan

etal., 2019). Climatic conditions favourable for mosquitoes, combined

with the increase of animal trade, may result in the expansion of the

geographic range of zoonotic diseases like RVF (Martin etal., 2008),

a threat for human and animal health with strong socioeconomic

impacts (Peyre etal., 2015).

9.10.2.2 Diarrhoeal Diseases, HIV and Other Infectious Diseases

9.10.2.2.1 Diarrhoeal diseases

Observed impacts

Africa has the highest rates of death due to diarrhoeal diseases in the

world (Havelaar etal., 2015; Troeger etal., 2018) and many children have

repeated diarrhoeal episodes with impaired growth, stunting, immune

dysfunction and reduced cognitive performance (Squire and Ryan,

2017). High land and sea temperatures (Paz, 2009; Musengimana etal.,

2016) and precipitation extremes increase transmission of bacterial and

protozoal diarrhoeal disease agents (Boeckmann etal., 2019) through

contamination of drinking water and food preparation and preservation

practices (Figure9.33; Levy etal., 2016; Soneja etal., 2016; Walker, 2018).

Cholera incidence has been shown to increase with temperature

(Trærup etal., 2011). Outbreaks, however, are most frequent in east

and southern Africa following tropical cyclones (Moore etal., 2017b;

Troeger etal., 2018; Ajayi and Smith, 2019; Cambaza etal., 2019).

Africa’s rapidly urbanising population increases the demand for

freshwater and is occurring in places that already have stretched water

and sanitation infrastructure (Howard etal., 2016). These conditions,

especially during periods of water scarcity, can reduce the frequency and

adequacy of hand washing and thereby increase disease transmission.

Projected risks

Disruptions in water availability, such as during droughts or infrastructure

breakdown, will jeopardise access to safe water and adequate sanitation,

undermine hygiene practices and increase environmental contamination

with toxins (Howard etal., 2016; WWF-SA, 2016; Miller and Hutchins,

2017).

Climate change is projected to cause 20,000–30,000 additional

diarrhoeal deaths in children (<15 years old) by mid-century under

1.5°C–2.1°C global warming (WHO, 2014), with west Africa most

affected, followed by east, central and southern Africa. Cholera

outbreaks are anticipated to impact east Africa most severely during

and particularly after ENSO events (Moore etal., 2017b).

1374

Chapter 9 Africa

Climate hazard Pathways to impact Vulnerable population groups Health outcomesPathogen exposure

Increased exposure, to bacterial

(e.g. E. coli, Campylobacter,

Salmonella & Shigella, Listeria,

V. Cholera), protozoal (e.g.

Cryptosporidium & Giardia) &

other pathogens (2.4.2.9; 5.11;

7.2.2.2; 7.2.2.3)



Increased reproduction & survival of

pathogens in water (Box 3.3) & food

sources (5.11; 5.12)



Contamination of food & drinking sources

(4.2.6; 4.3.3) with human & animal faeces

(7.2.2.3)



Increased phytoplankton, copepods & V.

Cholera (Box 3.3; 3.5.5)



Damage or disruption of water and

sanitation systems, reducing the quality and

quantity of water for drinking and hygiene

(4.3.3)



Use of unsafe sources of drinking water (4.2.6)



Reduced hygiene & food safety (cleaning

& processing food (5.11; 7.2.2.3)



Use of rainwater tanks for irrigation of vegetables

Decreased precipitation

(Box 7.2)

Increased sea temperature

(Box 7.2)

Increased precipitation & flooding

(Box 7.2)

Storms & extreme weather events

(Box 7.2)

Increased heat

Diarrhoeal disease

Disease, including dehydration

with hospital admission, loss of

weight, stunting & death (4.3.3;

7.2.2.2)

Asymptomatic infection

Shedding of

pathogens

General population

Infants & children (<5 years)

Elderly (>65 years)

Individuals with co-morbidities

Undernourished individuals (5.12; 9.6.1)

Urban residents in overcrowded informal

settlements (3.4.8; 4.4.1.3; 6)

Resource-poor segment of the population

with no or limited access to potable water

Displaced people settled in informal

settlements (Box 9.7)

Pathways to impact: diarrhoeal disease

Figure9.33 | Schematic showing the pathways to diarrhoeal disease impacts in Africa as a result of exposure to climate hazards. Numbers in the ﬁgure refer to chapter sections of this report.

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Africa Chapter 9

9.10.2.2.2 HIV

Observed impacts

Although levels of new HIV infections declined sharply during the

last decade, still more than a million adults and children become

infected each year (UNAIDS, 2020). Climate inﬂuences on HIV are

predominately indirect such as through heightened migration due to

climate variability, or extreme weather events leading to increased

transactional sex to replace lost sources of income. Changes in

climate affect each of the main drivers of HIV transmission in women,

including poverty, inequity and gender-based violence (Burke et al.,

2015a; Loevinsohn, 2015; Fiorella etal., 2019).

Projected risks

‘Oscillating’ or ‘circular’ migration for migrant workers in urban and

mining centres drove HIV transmission in the 1990s and 2000s (Lurie,

2006), and climate-related displacement may have similar effects (See

Box9.7; Gray and Mueller, 2012; Loevinsohn, 2015; Low etal., 2019).

Food insecurity and nutritional deﬁciencies, projected to increase with

increasingly variable climates, has been shown to increase sexual risk-

taking and migration, as well as increase susceptibility to other infections

(Lieber et al., 2021). Projected increases in exposure to infectious

diseases pose considerable threats to HIV-infected people who may

already have compromised immune function. Additionally, reduced lung

function in people with HIV from previous tuberculosis infection may put

them at high risk for morbidity and death during extreme heat (Abayomi

and Cowan, 2014). Moreover, extreme weather events accompanied by

damage to health system infrastructure could compromise the continuity

of antiretroviral treatment (Weiser etal., 2010; Pozniak etal., 2020).

9.10.2.2.3 Other infectious diseases

Poor populations in the western Sahel have the highest burden of

bacterial meningitis worldwide, with seasonal dynamics driven by the

dry Harmattan winds that transport dust long distances across the

continent (Agier etal., 2013; García-Pando etal., 2014). In Nigeria, rising

temperatures are projected to increase meningitis cases by about 50% for

1.8°C global warming (RCP2.6 in 2060–2075), and by almost double for

3.4°C global warming (RCP8.5 in 2060–2075) (Abdussalam etal., 2014).

Bilharzia is also highly climate sensitive, with its distribution inﬂuenced

by changes in temperature and precipitation, as well as development,

such as the introduction of freshwater projects (e.g., canals, hydroelectric

dams and irrigation schemes) (Adekiya etal., 2019).

9.10.2.3 Temperature-related Impacts

9.10.2.3.1 Mortality and morbidity

Observed impacts

Emergency department visits and hospital admissions have been

shown to increase at moderate-to-high temperatures (Bishop-Williams

Box9.6 | Pandemic risk in Africa: COVID-19 and future threats

Rapid advances in vaccination and other control measures in high-income countries means that the burden of COVID-19 is increasingly

concentrated in low- and middle-income countries, including those in Africa. The extent to which the COVID-19 pandemic is inﬂuenced

by weather or by future changes in climate remains contested (WMO, 2021). In time, COVID-19 may develop seasonal dynamics (Baker

etal., 2020; Kissler etal., 2020) similar to other respiratory infections (Carlson etal., 2020b).

Early work interpreted low-reported cases of COVID-19 in Africa as suggesting evidence of a protective climatic effect, but increasing

evidence indicates the role of climate is secondary to the timing of disease introduction, the pace of implementation of non-pharmaceutical

interventions and surveillance gaps (Evans etal., 2020; WMO, 2021). Going forward, testing coverage, reporting, governance, non-

pharmaceutical interventions and vaccine distribution and uptake are likely to be far more signiﬁcant for Africa’s COVID-19 trajectory than

climate change. Compounding risks, where climate hazards and natural disasters impair outbreak responses, may disrupt interventions

or cause additional deaths (Phillips etal., 2020; Salas etal., 2020).

Emerging and future pandemic threats

Future inﬂuenza pandemics are highly likely, as are regional epidemics and pandemics of novel zoonotic viruses (including coronaviruses

and ﬂaviviruses) (high conﬁdence). In the next decades, climate change will reshape the risk landscape for emerging zoonotic threats as

wildlife-livestock-human interfaces shift, facilitating the emergence of novel zoonotic threats and spillover of known zoonoses into novel

geographies (Carlson etal., 2020a; Mordecai etal., 2020). Characteristics of urban development and level of service provision, for example,

crowded living spaces and transport facilities, and access to water and sanitation will inﬂuence the transmission of COVID-19 and future

disease outbreaks (Wilkinson, 2020). Historically, west and central Africa were considered especially at risk of outbreaks given their high

biodiversity, high intensity of human–wildlife contact including wild meat trade, vulnerable health systems and history of Ebola virus

disease outbreaks (Paige etal., 2014; Allen etal., 2017; Pigott etal., 2017). However, as the Middle East respiratory syndrome coronavirus

(MERS-CoV) and COVID-19 pandemics have shown, there are multiple hotspots of viruses with pandemic potential globally, many of which

are not in Africa. Thus, labelling African rainforests as unique ‘hotspots’ undermines global health work and pandemic preparedness.

1376

Chapter 9 Africa

Climate hazard Pathways to impact Vulnerable population groups Health outcomes

General population

Infants & children (<5 years)

Elderly (>65 years)

Individuals with co-morbidities

Undernourished individuals (5.12; 9.12)

Outdoor workers

Resource-poor segment of the

population with no or limited cooling

systems

Urban residents in overcrowded

informal settlements (3.4.8; 4.4.1.3; 6)



Reduced crop yields, (5; 9.12)

including from increased

evaporation & soil drying (4.2; 9.7.2)



Increased energy use from sweating

& higher metabolic rate



Increased outdoor activities &

environmental exposures (7.2)

Increased heat

Heat-related mortality & morbidity

Heat stress

Heat exhaustion

Heat stroke

Dehydration

Cardio-respiratory compromise

Heat-related symptoms e.g. headache

Drowsiness, poor concentration, fatigue

Reduced work performance

Poor educational performance

Accidents

Mortality

Anxiety, anxiety disorders, depression

Increased aggression

Interpersonal violence including

homicide

Suicide

Collective violence

Dehydration

Maternal morbidity, prolonged labour

Preterm birth, stillbirth

Adverse long-term outcomes



Heat stress exacerbates heat production

by placenta, developing foetus & from

additional maternal weight, & uterine

contractions during labour

Pathways to impact: diarrhoeal disease

Mental health

(7.2.4; 9.6.1)

Poor pregnancy outcomes

(7.2.4; 9.6.1)

Direct heat-related

morbidity & mortality

(7.2.4; 9.6.1)

Figure9.34 | Schematic showing the pathways of impact for heat-related morbidities in Africa as a result of exposure to climate hazards. Numbers in the ﬁgure refer to chapter sections of this report. Indirect health

impacts of heat are not shown. For example, risk of malnutrition from reduced crop yields or reduced ﬁsheries catches (see Section9.8.5).

1377

Africa Chapter 9

et al., 2018; van der Linden et al., 2019), with increased levels of

mortality recorded on days with raised temperatures in Burkina Faso

(Kynast-Wolf etal., 2010; Diboulo etal., 2012; Bunker et al., 2017),

Ghana (Azongo et al., 2012), Kenya (Egondi et al., 2012; Egondi

etal., 2015), South Africa (Wichmann, 2017; Scovronick etal., 2018),

Tanzania (Mrema etal., 2012) and Tunisia (Bettaieb etal., 2010; Leone

etal., 2013). Cause of death most commonly involves cardiovascular

diseases (Kynast-Wolf et al., 2010; Scovronick et al., 2018), but

increased incidences of respiratory (Scovronick et al., 2018), stroke

(Longo-Mbenza etal., 1999) and non-communicable diseases (Bunker

etal., 2017) have also been linked with heat.

Excess death rates from non-optimal temperature in sub-Saharan

Africa are estimated to be nearly double the global average, with 24%

of the more than 5million annual deaths globally associated with non-

optimal temperature occurring in Africa (Zhao etal., 2021). The region

had the world’s highest cold-related excess death ratio and lowest

heat-related excess death ratio over the period 2000–2019. However,

during this time, cold-related excess deaths declined more rapidly than

the increase in heat-related excess deaths, resulting in a net decrease

in the excess death ratio from temperature.

Recent estimates of the burden of mortality associated with the

additional heat exposure from recent human-caused global warming

suggest approximately 43.8% of heat-related mortality in South Africa

was attributable to human-caused climate change from 1991–2018

(Vicedo-Cabrera etal., 2021). In many of South Africa’s 52 districts,

this equates to dozens of deaths per year. The elderly and children

under 5years are most vulnerable to heat exposure (Sewe etal., 2015;

Scovronick etal., 2018).

Projected risks

Globally, Africa is predicted to suffer disproportionately from higher

temperature-related all-cause mortality from global warming, compared

to temperate northern hemisphere countries (Carleton etal., 2018). The

number of days projected to exceed potentially lethal heat thresholds

per year reaches 50–150days in west Africa at 1.6°C global warming,

up to 200days in west Africa and 100–150days in central Africa and

parts of coastal east Africa at 2.5°C, and over 200days for parts of west,

central and east Africa for >4°C global warming (Mora etal., 2017; see

Sections9.5.3–7; Figure9.15). Projected rates of heat-related mortality

among people in the Middle East and north Africa who are older than

65years increase by 8–20 fold in 2070–2099, compared with 1951–

2005, based on RCP4.5 and RCP8.5 (both at >2°C global warming)

(Ahmadalipour and Moradkhani, 2018).

Temperature-related mortality across Africa is projected to escalate

with global warming. Above 1.5°C the risk of heat-related deaths

rises sharply, with at least 15 additional deaths per 100,000 annually

across large parts of Africa, reaching 50–180 additional deaths per

100,000 people annually in regions of north, west, and east Africa

for 2.5°C global warming, and increasing to 200–600 per 100,000

people annually for 4.4°C global warming (Figure9.35; Carleton etal.,

2018). However, some regions that currently experience cold-related

mortality (e.g., Lesotho and Ethiopian Highlands) are projected to

have reduced temperature-related mortality risk from warming.

GHG mitigation is projected to save tens of thousands of lives:

limiting warming to RCP4.5 (2.5°C) rather than RCP8.5 (4.4°C) at the

end of the century is projected to avoid on average 71 deaths per

100,000 people annually across Africa with larger reductions in risk

in north, west, central and parts of east Africa (Figure9.35). The cost

of mitigating heat stress using energy-intensive cooling methods is

expected to be unachievable for many African countries (Parkes etal.,

2019; see Section9.9.4).

9.10.2.3.2 Heat stress in speciﬁc settings

Heat stress symptoms are prevalent among people in buildings that

are poorly ventilated or insulated, or constructed with unsuitable

materials (e.g., corrugated metal sheeting). These features are

common to many structures in Africa, including slums, informal and

low-income settlements, as well as schools and healthcare facilities

(Bidassey-Manilal etal., 2016; Naicker etal., 2017; Wright etal., 2019).

Temperatures inside these structures can exceed outdoor temperatures

by 4°C or more and have large diurnal ﬂuctuations (Mabuya and

Scholes, 2020). Daily wage labourers and residents of urban informal

settlements are among the most vulnerable to heat stress because

of the urban heat island effect, with congestion, and inadequate

ventilation, shade, open space and vegetation (Bartlett, 2008) being

associated with impacts of both hot and cold conditions on public

health (Ramin, 2009). Temperature extremes are expected to result in

relatively more deaths in informal settlements than in other settlement

types (Scovronick and Armstrong, 2012).

The urban heat island effect exacerbates current and projected heat

stress in Africa’s rapidly growing cities (Mitchell, 2016) and is discussed

in more detail in Section9.9.3.

Escalating temperatures and longer-duration heatwaves are expected

to heavily affect workers already exposed to extreme temperatures,

for example, outdoor workers (Kjellstrom et al., 2018) and miners

(El-Shafei etal., 2018; Nunfam etal., 2019a; Nunfam et al., 2019b).

Vulnerability may also be high for women who cook food for a living,

and children who accompany them, due to prolonged exposure to

high temperatures (Parmar et al., 2019). Prisons, commonly poorly

ventilated and overcrowded, are also high-risk settings (Van Hout and

Mhlanga-Gunda, 2019).

9.10.2.3.3 Maternal and child health

Exposure to high temperatures during pregnancy has been linked with

adverse birth outcomes, including stillbirths or miscarriages (Asamoah

etal., 2018) and long-term behavioural and developmental deﬁciencies

(Duchoslav, 2017; MacVicar etal., 2017).

9.10.2.4 Impacts of Extreme Weather

During extreme conditions, for example, Cyclone Kenneth (Codjoe

et al., 2020) and El Niño 2015–2016 (WHO, 2016; Pozniak et al.,

2020), direct physical injury, loss of life, destruction of property and

population displacement can occur. Flooding and landslides are

common after extreme rainfall and are the most frequently described

impact of climate variability in Africa’s cities currently, with residents

1378

Chapter 9 Africa

of poorly serviced or informal settlements most vulnerable (Hunter

et al., 2020). Post-traumatic stress disorders in affected individuals

are common, including in children (Rother, 2020). In rural areas, the

resulting damage to health facilities, access routes and transport

services can severely compromise health service delivery (WHO, 2016).

The effects of extreme weather on urban health infrastructure depends

on the characteristics, location and adaptive capacity of cities (see

Section9.9.4).

16–45

311–419

Additional

deaths

(increased risk)

Avoided

deaths

(reduced risk)

176–310

46–175

6–10

11–15

1–5

6–10

11–15

16–45

46–80

1.6°C 2.0°C 2.5°C

(b) High emissions (RCP8.5)

1.7°C 2.5°C 4.4°C

Temperature-related mortality risk in Africa with increased global warming

(a) Intermediate emissions (RCP4.5)

Period 2020–2039 Period 2040–2059 Period 2080–2099 Changes in temperature-related

annual mortality rates per 100,000

1–5

16–45

46–149

Additional

deaths

Avoided

deaths

11–15

6–10

46–175

176–310

6–10

11–15

16–45

1–5

311–450

451–609

Figure9.35 | Projected temperature-related mortality risk in Africa with increasing global warming. Maps show changes in mortality rates in deaths per 100,000

for global warming in the years 2020–2039, 2040–2059 and 2080–2099 for

(a) intermediate emissions scenario (RCP 4.5);

(b) a high emissions scenario (RCP 8.5); and

(c) showing avoidable deaths due to increased emissions mitigation efforts to achieve a lower global warming level (RCP4.5 rather than RCP8.5). These estimates of climate

change impacts on mortality rates include temperature-related impacts only. They account for the beneﬁts of income growth and incremental adaptation to climate change, both

of which reduce mortality sensitivity to extreme temperatures. Projections were based on income and demographics from Shared Socioeconomic Pathway 3 (SSP3), with future

adaptation based on adaptation actions observed in the global historical record. The estimates do not include the costs of the behaviours and investments required to achieve such

adaptation (Carleton etal., 2018). Areas shown in burgundy in (c) have fewer deaths due to temperature under RCP8.5 than RCP4.5. This is because cold is currently the greatest

driver of temperature-related deaths in these areas, which is projected to be alleviated with increasing levels of global warming (Zhao etal., 2021).

1379

Africa Chapter 9

9.10.2.5 Malnutrition

9.10.2.5.1 Observed impacts

Africa has experienced the greatest impacts of climate change on acute

food insecurity and malnutrition (FAO and ECA, 2018). Adverse climatic

conditions exacerbate the impacts of an unstable global economy,

conﬂict and pandemics on food insecurity (AfDB, 2018b; Food Security

Information Network (FSIN), 2019; Fore et al., 2020; see Chapter 5

Section5.12.4).

More than 250million Africans are undernourished, mostly in central

and east Africa (FAO etal., 2020), which increases childhood stunting,

affects cognition and has trans-generational sequelae (IFPRI, 2016;

UNICEF etal., 2019). Undernutrition is strongly linked with hot climates

(Hagos etal., 2014; Tusting et al., 2020). In Burkina Faso, low crop

yields resulted in around 110 deaths per 10,000children under 5years,

with 72% of this impact attributable to adverse climate conditions in

the growing season (Belesova etal., 2019).

Increasing incidence and expanded distributions of vector-borne livestock

diseases (e.g., bluetongue, trypanosomiasis and RVF) in response to

changes in rainfall and increasing temperatures, undermine food security,

especially among subsistence farmers (Samy and Peterson, 2016;

Caminade etal., 2019). Locust infestations linked with changes in climate

(Salih etal., 2020) are a major risk for food security in Africa.

9.10.2.5.2 Projected risks

Projected risks for malnutrition in Africa are high (FAO, 2016; see

Section 9.8.1): 433 million people in Africa are anticipated to be

undernourished by 2030 (FAO etal., 2020) and, compared to 1961–

1990, 1.4million additional African children will suffer from severe

stunting by 2050 under 2.1°C global warming (WHO, 2014). In Burkina

Faso, the mortality burden due to low crop yields could double by 2100

with 1.5°C of global warming (Belesova etal., 2019). Drought risks

will include crop and livestock failures (Ahmadalipour etal., 2019).

Additionally, increasing concentrations of atmospheric CO2 will affect

the nutritional quality of C3 plant staples, lowering levels of protein

and minerals like zinc and iron (Myers etal., 2014; Weyant etal., 2018).

Declining ﬁsh catches due to ocean warming, illegal ﬁshing and poor

stock management are projected to increase deﬁciencies of zinc, iron

and vitamin A for millions of people across Mozambique, Angola and

multiple west African countries (see Section9.8.5; Golden etal., 2016).

9.10.2.6 Non-communicable Diseases and Mental Health

Links between climate change and the environmental risk factors for

non-communicable diseases (NCDs) may be direct (e.g., extreme heat

exposure in people with cardiovascular disease) or indirect, such as

via the global agriculture and food industry (Landrigan etal., 2018).

These effects are largely unreported for Africa (Amegah etal., 2016),

where the burden of many NCDs is growing rapidly with increasing

urbanisation and pollution (Rother, 2020).

Many urban poor populations have unhealthy dietary practices, which

present major risks for obesity, type II diabetes and hypertension.

Paradoxically, despite growing levels of undernutrition, the incidence

of overweight and obesity continues to rise in Africa, particularly in

children under 5years from the northern and southern parts of the

continent (FAO and ECA, 2018). Diabetes is increasingly prevalent

and outcomes may worsen if climate change undermines health

infrastructure and the range of available foods (Keeling etal., 2012;

Kula etal., 2013; Chersich and Wright, 2019).

The relationship between cancer and climate change is complex

and indirect. Changing temperature and humidity may alter the

distribution of aﬂatoxin-producing fungi, contaminating food (grains,

maize) and causing cancer (see Box5.9 in Chapter 5; Sserumaga etal.,

2020; Valencia-Quintana etal., 2020). Severe storms and ﬂooding may

disrupt wastewater treatment or disposal, potentially contaminating

drinking water with carcinogenic substances.

Areas with low service provision (e.g., informal settlements in Africa)

suffer from increased infestations of pests such as ﬂies, cockroaches,

rats, bedbugs and lice, which may be controlled by chemical pesticides

(Rother etal., 2020) and may become more prevalent with a changing

climate (Mafongoya et al., 2019). Inappropriate pesticide use and

disposal cause endocrine disruption and increased incidences of some

cancers (Rother etal., 2020).

9.10.2.6.1 Mental health and well-being

Mental health and well-being are affected by local climate conditions

and are therefore sensitive to climate change (Burke et al., 2018b;

Obradovich et al., 2018). High temperatures are strongly associated

with poor mental health and suicide in South Africa (Kim etal., 2019).

Exposure to extreme heat directly inﬂuences emotional control,

aggression and violent behaviour, escalating rates of interpersonal

violence, with homicides rising by as much as 18% in South Africa when

temperatures are above 30°C compared with temperatures below 20°C

(Burke etal., 2015a; Chersich etal., 2019b; Gates etal., 2019).

Extreme weather events are often severely detrimental to mental health

(Scheerens etal., 2020), with elevated rates of anxiety, post-traumatic

stress disorder and depression in impacted individuals (Schlenker and

Lobell, 2010; Nuvey etal., 2020). Youths may be at especially high risk

(Barkin etal., 2021).

Loss of livestock from disease or lack of pastures is strongly linked

with poor mental health among farmers (Nuvey etal., 2020). Climate

change impacts on mental health among refugees is concerning but

remains under-researched (Matlin etal., 2018).

9.10.2.7 Air Quality-related Health Impacts

Links between air quality and climate change are complex (Smith

et al., 2014; Szopa et al., 2021). Increases in particulate matter

concentrations are driven more by vehicle emissions, solid waste,

biomass burning and development (Abera et al., 2021) than by

climate change, and these factors vary widely across regions of the

continent (West etal., 2013). Women and children who are exposed

to high particulate matter concentrations when cooking indoors and

HIV-infected people are more vulnerable to the health impacts of air

1380

Chapter 9 Africa

Box9.7 | The health–climate change nexus in Africa

The intersections between climate change and human health involve interactions of numerous systems and sectors (Lindley etal., 2019;

Yokohata etal., 2019). This complexity means that holistic, transdisciplinary and cross-sectoral (systems) approaches like One Health,

EcoHealth and Planetary Health can improve the long-term effectiveness of responses to health risks (Zinsstag, 2012; Whitmee etal.,

2015; Nantima etal., 2019). More research is needed to identify sustainable solutions (Rother etal., 2020), as recently re-emphasised

by the Intergovernmental Panel on Biodiversity in its report on the COVID-19 pandemic (IPBES, 2020). The close dependency of many

Africans on their livestock and surrounding ecosystems forms a context where integrated health approaches are especially critical for

addressing climate change risks to health (Figure Box9.7.1; Watts etal., 2015; Cissé, 2019).

Integrated approaches to health in Africa can deliver multiple beneﬁts for humans and ecosystems For example, rather than addressing

micronutrient deﬁciencies with supplements, which may not be accepted culturally and can be disrupted by stockouts or similar, addressing

nutrient deﬁciencies in staple crops by selecting or breeding more nutritious varieties (e.g., orange-ﬂeshed sweet potatoes or ‘golden rice’

for vitamin A deﬁciency) may prove to be more sustainable options (Datta etal., 2003; Nair etal., 2016; Laurie etal., 2018; Oduor etal.,

2019; Stokstad, 2019). Additionally, some micro- or macronutrient deﬁciencies and food insecurities may be improved by addressing the

depletion of soils through better management, including the incorporation of holistic, sustainable principles, such as those promoted by

agroforestry or regenerative agriculture (Rhodes, 2017; Elevitch etal., 2018; LaCanne and Lundgren, 2018; Chapter5 Section5.12.4).

pollution (Abera etal., 2021). Information on the direction of change of

air quality in different African regions attributable to climate change are

contradictory (Westervelt etal., 2016; Silva etal., 2017). Additionally,

much uncertainty remains about interactions between air quality and

climate change and relative impacts of different modes of development

and climate change on pollutants. However, increasing temperatures

combined with a reduction in rainfall are likely to increase particulate

matter concentrations (Abera etal., 2021), particularly in north Africa

(Westervelt etal., 2016; Silva etal., 2017).

Nevertheless, continued dependence on fossil-fuelled power plants will

result in tens of thousands of avoidable deaths due to air pollution by

2030 (Marais and Wiedinmyer, 2016), and accelerate climate change.

Actions to reduce air pollution can both mitigate climate change and

have major co-beneﬁts for health (West etal., 2013; Rao etal., 2016;

Markandya etal., 2018; Rauner etal., 2020a; Rauner etal., 2020b) see

also AR6 WGIII, Chapters 3, 4, 8 and 10). Investing in renewable energy

resources rather than reliance on the combustion of fossil fuels would

mark an important step forward for African population health (Marais

etal., 2019). This is especially important in South Africa which emits

approximately half the total carbon emissions for Africa, ranking 12th

in the world for carbon emissions (Mohsin etal., 2019).

Dust events in west Africa have severe health impacts (cardiorespiratory

and infectious diseases, including meningitis) (Ayanlade etal., 2020)

given the proximity of the Sahara, which produces about half of the

yearly global mineral dust (de Longueville etal., 2013). Wildﬁres are

projected to become the main source of particulate matter in west,

central and southern Africa under both the lowest and highest future

emissions scenarios, whereas, under intermediate scenarios (i.e., SSP3/

RCP4.5), anthropogenic sources of particulate matter are projected to

exceed that produced by wildﬁres (Knorr etal., 2017).

9.10.3 Adaptation for Health and Well-being in Africa

In this section, we focus on adaptation actions that are well-documented

or shown to have the potential for substantially improving health or

well-being. These adaptation options are assessed in Figure9.36 and

Table9.11.

In Africa, adaptive responses have begun to be implemented by

local, national and international entities (Ebi and Otmani Del Barrio,

2017). With strong leadership, these initiatives can be used as an

opportunity for comprehensive, transformative change rather than

incremental improvements to existing systems. Adaptation responses

are necessarily context speciﬁc and can focus on providing services

for vulnerable and high-risk populations (Dumenu and Obeng, 2016;

Herslund etal., 2016).

Adaptation actions in the health sector range from building resilient

health systems to preparing responses to health impacts of extreme

weather events to reducing effects of increasing temperatures in

residential and occupational settings (Kjellstrom etal., 2016; Chersich

and Wright, 2019). A climate-resilient health system involves functional

and effective health systems (WHO, 2015), national and local policy

plans with resources for implementation, and long- and short-term

communication strategies to raise awareness around climate change

(Nhamo and Muchuru, 2019).

1381

Africa Chapter 9

Human Health

Ecosystem Health

Animal Health

Deforestation5, 6

Loss of ecosystem

services1, 2, 3

Changing disease

distributions

(incl. emerging

& zoonotic

diseases)3

Reduction in quantity

and quality of feed

and forage4, 7

Animal starvation

Food insecurity, malnutrition

Reduced provisioning,

pollination,

seed dispersal

Sections 9.6

and Chapters 2, 3, 5

Section 9.10 and Chapter 7 Section 9.8 and Chapter 5

Reduced access to phytomedicines /

traditional remedies

Reduced regulation

of air and

water quality

Cardio-respiratory and

diarrhoeal diseases

Increased

human-wildlife-livestock

interaction

Pandemics

Worsening livestock health4, 7

Increased

antimicrobial use

Antimicrobial resistance

Reduced livestock products & services7

Food insecurity,

malnutrition

Reduced income

Impaired mental health

& wellbeing

Synergy ecosystem

and human heath

Synergy ecosystem

and animal heath

Synergy human

and animal heath

Synergy ecosystem,

human, animal heath

Increased

chance of spillover

diseases in people and

livestock

Interlinkage between human, ecosystem and animal health

FigureBox9.7.1 | Human, ecosystem and animal health are intimately interlinked, and require transdisciplinary approaches such as One Health,

EcoHealth and Planetary Health for effective, sustainable, long-term management. This schematic shows some examples of these interlinkages, and how

they impact human health, highlighting the complex interactions and the importance of holistic, systems approaches to health interventions, including for climate change

adaptation. Supporting literature: (1) (Egoh etal., 2012); (2) (Wangai etal., 2016); (3) (Failler etal., 2018); (4) (Ifejika Speranza, 2010); (5) (Brancalion etal., 2020); (6)

(Bloomﬁeld etal., 2020); (7) (Rojas-Downing etal., 2017).

Box9.7 (continued)

1382

Chapter 9 Africa

Many health conditions associated with climate change are not new,

and existing evidence-based interventions can be modiﬁed to address

shifting disease patterns (Ebi and Otmani Del Barrio, 2017). Adaptation

options can build on a long tradition of community-based services in

Africa (Ebi and Otmani Del Barrio, 2017). Indeed, strengthening many

of the services already provided (e.g., childhood vaccinations and

vector control) will help curtail emerging burdens of climate-sensitive

conditions. However, a disproportionate focus on emerging zoonotic

and vector-borne viruses could undermine climate change adaptation

efforts in Africa if it shifts the focus away from health system

strengthening and leaves few resources for addressing other health

impacts of climate change.

Core components of an adaptation response include rapid impact

packages (e.g., mass drug administration for schistosomiasis), education

of women and direct poverty alleviation (Bailey et al., 2019). Where

droughts are more frequent and rainfall patterns have shifted, adaptation

support can be provided for strategies developed by communities,

including the adaptation of livelihoods and diversiﬁcation of crops and

livestock (Mbereko etal., 2018; Bailey etal., 2019). Continued efforts

through partnerships, blending adaptation and disaster risk reduction,

and long-term international ﬁnancing are needed to bridge humanitarian

and sustainable development priorities (Lindley et al., 2019; Cross-

Chapter BoxHEALTH in Chapter 7).

9.10.3.1 Risk Assessment and Warning Systems

Improved institutional capacity for risk monitoring and early warning

systems is key to support emergency preparedness and responsiveness

in Africa, as well as shock-responsive and long-term social protection

(FAO and ECA, 2018). Climate risk assessments grounded in evidence

and locally appropriate technologies are important for identifying

priority actions, the scale of intervention needed and high-risk

geographical areas and populations. Potential tools include those

developed by WHO (Ceccato etal., 2018) and the Strategic Tool for

Analysis of Risk (Ario etal., 2019).

Warning systems that predict seasonal to intra-seasonal climate risks

could assist in improving response times to extreme weather events

(such as droughts, ﬂooding or heat waves) and shifts in infectious

diseases. Weather and other types of forecasting provide an advanced

warning—a central tenet of disaster risk reduction (Funk etal., 2017;

Okpara et al., 2017a; Lumbroso, 2018). Models encompassing each

component of the human–animal–environmental interface, including

disease surveillance in humans and animals and remote sensing of

vegetation indexes, water and soil can be used to project patterns of

zoonose outbreaks (UNDP, 2016; Bashir and Hassan, 2019; Durand

etal., 2019). Early warning systems may help better prepare for these

and other forms of infectious disease outbreaks (Thomson etal., 2006)

but adaptation is possible in the absence of statistical tools through

vaccination and surveillance, for example.

Surveillance systems for diseases and vectors are well-established in

many parts of Africa (Ogden, 2017). However, many data gaps remain,

especially in monitoring climate-sensitive conditions such as diarrheal-

and arbovirus-related diseases, and morbidity and mortality stemming

from heat exposure (Ogden, 2017; Buchwald etal., 2020).

Climate and health adaptation indicators are required for Africa

to strengthen institutional capacity for risk monitoring and early

warning systems, emergency preparedness and response, vulnerability

reduction measures, shock-responsive and long-term social protection,

and planning and implementing resilience-building measures (FAO

and ECA, 2018). National-level progress is assessed through the

Lancet Countdown indicators (Watts etal., 2018), however, district-

and local-level indicators are needed to measure levels of vulnerability

and response effectiveness at a local level, and for informing planning

local service delivery. Potential indicators include monitoring the

number of excess health conditions during extreme heat events.

Indoor temperature monitoring in sentinel houses and health facilities

is a related indicator (Ebi and Otmani Del Barrio, 2017), linked with

threshold temperature levels at which health impacts occur, and the

ability of the built environment to protect against these impacts (e.g.,

for heatwaves).

Measuring climate-health linkages is challenging due to the considerable

diversity of the exposures, impacts and outcomes, as well as constraints

in key technical areas. Increasing our understanding of this diversity

and how this is inﬂuenced by adaptative changes is a major knowledge

gap. This could be facilitated through a pan-African database of climate

and other environmental exposures, together with real-time statistical

support for analyses of climate and health associations.

9.10.3.2 Community Engagement

Increased awareness can facilitate community engagement and

action (see Section9.4.3). In Ghana, for example, local communities

understand the climate hazards that drive outbreaks of meningitis

and adapt accordingly by improving housing to limit heat and

exposure, changing funeral practices during outbreaks, increased

vaccination uptake and afforestation (Codjoe and Nabie, 2014).

Similarly, participation in community organisations improved child

nutrition in vulnerable rural households in Eswatini (Anchang etal.,

2019). Interventions speciﬁcally targeting women are beneﬁcial for

food security, although they may be undermined by harmful gender

norms in communities that are patriarchal, led by chiefs or have high

rates of gender-based violence (Jaka and Shava, 2018; Kita, 2019;

Masson etal., 2019). The BRACED project in Burkina Faso and Ethiopia

speciﬁcally adopted a gender-transformative approach as an integral

part of resilience building (McOmber etal., 2019). Improving ‘climate

literacy’ could empower youth, women and men to be active citizens in

promoting adherence of governments to international agreements in

climate change (Mudombi etal., 2017; Chersich etal., 2019a).

9.10.3.3 Health Financing

Poor and low-income households often are not able to afford high

out-of-pocket costs for medical care, or it consumes a large portion of

their income. As a result, without ﬁnancial aid, peoples’ health needs

may not be met after a climate shock (Hallegatte and Rozenberg,

2017). Microﬁnance (the provision of small-scale ﬁnancial products

to low income and otherwise disadvantaged groups by ﬁnancial

institutions) and disaster contingency funds can serve to reduce health

risks of climate change for low-income communities (Agrawala and

Carraro, 2010; Ozaki, 2016), as can different forms of insurance and

1383

Africa Chapter 9

disaster relief (Fenton etal., 2015; Dowla, 2018). Unconditional cash

transfers in Kenya, Uganda and Zambia assisted vulnerable groups to

absorb the negative impacts of climate-related shocks or stress and to

prepare for these (Lawlor etal., 2019; Ulrichs etal., 2019). Based on

several case studies in Africa, the Food and Agriculture Organization

recommends a ‘Cash+’ approach which combines cash transfers with

productive assets, inputs or technical training to address the needs

of vulnerable households in emergency situations, and enhance

livelihoods potential, income generation and food security (FAO,

2017). New economic models have been implemented in north Africa,

focused on poor households, youth and women that enable access to

credit and support the implementation of policies that balance cash

and food crops, social safety nets and social protection (Mumtaz and

Whiteford, 2017; Narayanan and Gerber, 2017; see also Sections9.4;

9.8; 9.11).

9.10.3.4 Disease-speciﬁc Adaptations

9.10.3.4.1 Adaptation to prevent malaria

Increasing distribution and coverage of long-lasting insecticide-treated

bed nets, improved diagnostic tests and increasing health service

access could mitigate the impacts of climate change on malaria if

aligned with the predicted or actual burden of malaria (medium

conﬁdence) (Kienberger and Hagenlocher, 2014; Thwing etal., 2017).

Understanding seasonal shifts in malaria transmission suitability as a

result of climate change can guide more targeted seasonal public health

responses and better planning for different types of management and

control interventions based on the impact. For example, an increase

in the number of months where climate conditions are suitable for

mosquito survival will require public health responses for an extended

period of time (Ryan etal., 2020).

In malaria-endemic areas, repeated malaria infections can provide

temporary immunity, which reduces new clinical cases (Laneri etal.,

2015; Yamana etal., 2016). Conversely, where people have little or

no immunity, exposure to malaria can lead to epidemics (Semakula

etal., 2017a; Ryan etal., 2020). Pregnant women and infants remain

at risk of severe malaria, regardless of immunity status. Vector control

and case management capacity should be rapidly scaled up in newly

affected areas where risks for epidemics are high and populations are

especially vulnerable. Poverty-alleviation initiatives underpin malaria

control as the malaria burden is strongly tied to socioeconomic status

(Huldén etal., 2014; Degarege etal., 2019).

Contextualised risk studies on local drivers of transmission are still

lacking and present a major gap in developing appropriate adaptation

strategies (high conﬁdence). Progress has been made identifying and

ranking vulnerability and exposure indicators (Protopopoff et al.,

2009; Onyango etal., 2016a), however, better linking of biophysical

and socioeconomic determinants of risk in integrated assessment

models is needed (Caminade et al., 2019; Zermoglio etal., 2019),

as are applied approaches to develop adaptation strategies for risk

management (Leedale etal., 2016; Onyango et al., 2016b; Sadoine

etal., 2018).

9.10.3.4.2 Adaptation to reduce diarrhoeal disease

Reducing pathogen concentrations in water and across food chains is

fundamental for controlling diarrhoeal diseases (van den Berg etal.,

2019). Diarrhoea prevention and treatment post-disaster, encompass

social mobilisation campaigns, water treatment, enhanced surveillance,

and vaccination and treatment centres for cholera (Cambaza etal.,

2019) and typhoid (Neuzil etal., 2019).

Improved WASH requires robust water and sanitation infrastructure

(Duncker, 2017; Kohlitz et al., 2017; Venema and Temmer, 2017) and

technological adaptations (Gabert, 2016; van Wyk etal., 2017), such as

waterless on-site sanitation (Sutherland etal., 2021), diversiﬁcation of

water sources (e.g., rainwater harvesting (Lasage and Verburg, 2015)

and groundwater abstraction (MacDonald etal., 2012)), and sharing of

best practices across the continent (WASH Alliance International, 2015;

Jack etal., 2016; see also Section9.7.3; Chapter4 Section4.6.4). Hand

hygiene can be improved through the creation of handwashing stations,

increased access to soap and simple technologies such as the foot-

operated Tippy taps (Coultas and Iyer, 2020; Mbakaya etal., 2020).

9.10.3.4.3 Adaptation to reduce conditions related to heat exposure

Reducing morbidity and mortality during extreme heat events

requires changes in behaviour and health promotion initiatives,

health system interventions and modiﬁcations to the built and

natural environment. Health promotion initiatives include promoting

adequate hydration and simple cooling measures, such as drinking

cold liquids, water sprays and raising awareness of the symptoms

and importance of heat stress, including heatstroke (Aljawabra and

Nikolopoulou, 2018). Adaptive measures are especially important

for high-risk groups such as outdoor workers, the elderly, pregnant

women and infants. Health systems interventions may include

early warning systems, heat health regulation and health workers

providing cooling interventions, such as supplying cool water or

fans, during heat waves. Changes to the built environment include

painting the roofs of houses white and improving ventilation during

extreme heat (Codjoe etal., 2020), the use of insulation materials or

altering the building materials used for the construction of housing

to improve their ability to moderate indoor temperatures (Mathews

etal., 1995; Makaka and Meyer, 2006).

9.10.3.4.4 Adaptation to prevent malnutrition

Transformative adaptation requires integration of resilience and

mitigation across all parts of the food system including production, supply

chains, social aspects and dietary choices (IPCC, 2019a). Adaptation to

prevent malnutrition goes hand-in-hand with adaptation to prevent

food insecurity, as is discussed in Section9.8.3; Chapter5 Section5.12.5.

Urban agriculture and forestry can improve nutrition and food

security, household income and mental health of urban farmers

while mitigating against some of the impacts of climate change, like

ﬂooding and landslides (by stabilising the soil and reducing runoff, for

example), heat (by providing shade and through evapotranspiration)

and diversifying food sources in case of drought (Zezza and Tasciotti,

2010; Lwasa etal., 2014; Battersby and Hunter-Adams, 2020).

1384

Chapter 9 Africa

Adaptation options across multiple sectors have potential for reducing risk across multiple health outcomes,

considering their potential to reduce vulnerability, and potential barriers to implementation

Health outcome/benefit

Non-

communicable

diseases

(NCDs)

Heat-

illnesses

Infectious

diseases

Vector-

borne

diseases

Food- and

water-

borne

diseases Nutrition

Adaptation options

Potential for

risk reduction

Positive

outcomes

vulnerable

populations

Requires

sensitivity and

consideration

of cultural and

traditional

practices

Mainstreaming climate change into all health

policies xx xxx

Occupational setting interventions (labour laws;

avoiding heat during the day; education re

adaptations)

Local knowledge strengthening and education xxxx

Community, community health workers, and

leadership resilience xx

Teaching of climate change risks and

behavioural changes in schools and universities xx

Access to healthcare xxxxxx

Universal Health Coverage, including of

services for climate-related diseases xxxxxx

Infectious disease surveillance, early warning,

outbreak response and control xx

Heat health plans xx

Vulnerability assessments xxxx x

Intervention studies xx x

Risk assessments xxxxxx

Early warning systems forecasting/disaster

management for smallholder farmers xx xx

Disaster Preparedness xxxxxx

Health information systems for climate-related

diseases xxxxxx

Surveillance of health and environmental

factors xxxxxx

Improved management of environmental

determinants of health (water quality; waste

and sanitation; air quality)

xxxxx

Strengthening of health systems and

infrastructure against threat of extreme weather

events, and for post-disaster recovery

xxxxxx

Transport (sustainable; public) (infrastructure) xx

Sustainable land use, forestry, water

management xx xxx

Sustainable farming xx xxx

Solar power/biogas for electricity x

Tree and seed planting xx xx

Improved housing, including painting roofs

white xx xx

Insecticide-treated bed nets x

Indoor residual spraying x

Genetic modification x

Response

category

Policy

development

Education and

awareness

Health systems

and primary

healthcare

services

Surveillance,

risk

assessments,

monitoring,

and research

Resource

management

Vector control

and disease

prevention

Key for sectors involved in each response category, and level of confidence

(based on the literature)

Policy, governments, environmental health practitioners, community

Forestry

Agriculture, terrestrial

Indigenous and local knowledge

Water and sanitation

Weather and climate services

Research, innovation and development

Confidence

High

Medium

Low

Figure9.36 | Adaptation options across multiple non-health sectors have potential for reducing risk for multiple health outcomes, considering their

potential to reduce vulnerability. Reduced risk for health may result from targeted actions or as a result of co-beneﬁts (see TableSM9.8 for a full list of references).

1385

Africa Chapter 9

The health sector needs to collaborate and coordinate adaptation

activities with other sectors, as well as civil society and international

agencies, to engage communities in health promotion (Irwin etal.,

2006; Commission of Social Determinants of Health, 2008; Braveman

and Gottlieb, 2014). The importance of social determinants of

health, such as socioeconomic status, education and the physical

environment in which people live and work and their consideration

during development are highlighted in Chapter 7 (see Sections7.1.6;

7.4.2)

9.11 Economy, Poverty and Livelihoods

9.11.1 Observed Impacts of Climate Change on African

Economies and Livelihoods

9.11.1.1 Economic Output and Growth

Increased average temperatures and lower rainfall have reduced

economic output and growth in Africa, with larger negative impacts

than other regions of the world (Abidoye and Odusola, 2015; Burke

etal., 2015a; Acevedo etal., 2017; Kalkuhl and Wenz, 2020). In one

estimate, GDP per capita is on average 13.6% lower for African

countries than it would be if human-caused global warming since 1991

had not occurred (Diffenbaugh and Burke, 2019), although impacts

vary substantially across countries (see Figure9.37). As such, global

warming has increased economic inequality between temperate,

northern Hemisphere countries and those in Africa (Diffenbaugh and

Burke, 2019). Warming also leads to differential economic damages

within Africa (Baarsch etal., 2020). One estimate found a 1°C increase in

20-year average temperature reduced GDP growth by 0.67percentage

points, with the greatest impacts in Central African Republic, DRC and

Zimbabwe (Abidoye and Odusola, 2015). Changes in rainfall patterns

also inﬂuence individual and national incomes. Had total rainfall not

declined between 1960 and 2000, the gap between African GDP and

that of the rest of the developing world would be 15–40% smaller

than today, with the largest impacts in countries heavily dependent on

agriculture and hydropower (Barrios etal., 2010).

Aggregate macroeconomic impacts manifest through many channels

(Carleton etal., 2016). Macroeconomic evidence suggests aggregate

impacts occurred largely through losses in agriculture with a smaller role

for manufacturing (Barrios etal., 2010; Burke etal., 2015b; Acevedo etal.,

2017). Sector-speciﬁc analyses conﬁrm that declines in productivity of

food crops, commodity crops and overall land productivity contribute to

lower macroeconomic performance under rising temperatures (Schlenker

and Lobell, 2010; Bezabih etal., 2011; Jaramillo etal., 2011; Lobell etal.,

2011; Adhikari et al., 2015). Labour supply and productivity declines

Table9.11 | Co-beneﬁts, barriers and enablers of adaptation responses to climate change impacts on human health in Africa (see TableSM9.9 for a full list of references).

Response category Co-beneﬁts Inter-sectoral trade-offs and/

or drawbacks Enablers Barriers

Policy development

Policies and plans that facilitate service delivery

and guide national and international funding;

decreased number of work hours lost; improved

work performance, increased productivity

Willingness of policymakers;

political support; politically

willing environment; inter-sectoral

collaboration

Lack of implementation;

poor governance

Education and

awareness

Promotion of sustainable living and circular

economy

Guarantee of sustained funding;

political support; politically

willing environment; increased

accessibility of learning

institutions

Lack of implementation;

historical and

colonisation-related

insensitivities

Health systems and

primary healthcare

services

Capacity building in communities; buffered

economic impact of outbreaks/disasters; job

creation

Increased greenhouse gas emissions

from building health infrastructure;

increased energy demand; decreased

productivity and increased work

hours lost due to waiting times

Guarantee of sustained funding;

political support; politically willing

environment

Corruption and fraudulent

activities around resource

allocation

Surveillance, risk

assessments,

monitoring and

research

Evidence to improve adaptation response; fast

post-disaster recovery; increased awareness

and disease prevention; improved health system

functioning post-disasters

Requires effective institutional

arrangements and inter-sectoral

collaboration; guarantee to

sustained funding; requires skills

development

May be limited by

uncertainty in modelled

predictions and thresholds

Resource management

Improved health system functioning

post-disasters; capacity building in communities;

promotes economic growth/stability; increases

the tourism potential of the area; increased

accessibility/mobility of the community;

reduced land degradation, desertiﬁcation and

bush encroachment; food security; decreased

emissions

Potential to increase energy demand;

increased crowding/ population

density; land use; microclimate and

ecosystem disruption

Guarantee of sustained funding;

political support; politically willing

environment; requires effective

institutional arrangements and

inter-sectoral collaboration;

requires skills development

Corruption and fraudulent

activities around resource

allocation

Vector control and

disease prevention

Decreased mortality; improved work

performance; increased productivity; improved

mental health

Increased GHG; decreased

biodiversity; environmental impacts

of production, packaging, and

delivery; potentially detrimental to

health

Guarantee to sustained funding;

funding and resources; future

planning or retroﬁt required

Last-mile access; cost per

capita and capacity for

service delivery

1386

Chapter 9 Africa

in manufacturing, industry, services and daily wage labour have been

observed in other regions (Graff Zivin and Neidell, 2014; Somanathan

etal., 2015; Day etal., 2019; Nath, 2020) and contribute to aggregate

economic declines, countering aggregate poverty reduction strategies

and other SDGs (Satterthwaite and Bartlett, 2017; Day etal., 2019). In a

case study of a rural town in South Africa, over 80% of businesses (both

formal and informal) lost over 50% of employees and revenue due to

Observed aggregate economic impacts and projected risks from climate change in Africa

(a) Percentage change in GDP per capita

due to observed climate change (1991–2010)

-30% -20% -10% 0 10%

Mauritania

Mali

Niger

Sudan

Chad

Burkina Faso

Djibouti

DRC

Côte d'Ivoire

Guinea

Nigeria

Republic of Congo

Sierra Leone

Senegal

Gambia

Ghana

Cameroon

Benin

Guinea-Bissau

Mozambique

Togo

Liberia

Comoros

Malawi

Central African Republic

Namibia

Angola

Botswana

Uganda

Zambia

Gabon

Tanzania

Rwanda

Burundi

Ethiopia

Cape Verde

South Africa

Egypt

Kenya

Equatorial Guinea

Zimbabwe

Algeria

Morocco

Mauritius

Madagascar

Swaziland

Tunisia

Lesotho

(b) Projected percentage

decrease in GDP per capita

for 4°C global warming

compared to a scenario

with no global warming

after 2010

GDP per capita from limiting

global warming to 1.5°C

rather than 2°C

(d) Probability of economic

benefits from limiting global

warming to 1.5°C

rather than 2°C

80–89%

70–79%

60–69%

>5%

90–92%

No data

Percentage

decrease

in GDP

per capita

No data

Probability

100

No data

Percentage

20%

10%

-15%

-30%

Figure9.37 | Observed aggregate economic impacts and projected risks from climate change in Africa.

(a) Estimated effect of human-caused climate change on GDP per capita for 48 African countries between 1991 and 2010.

(b) Projected effect on GDP per capita of global warming of ~4°C by 2100 compared to economic growth with no further global warming after 2010.

(c) Projected percentage increase in GDP per capita of holding global warming to 1.5°C rather than 2°C above pre-industrial level.

(d) Probability of realising any economic beneﬁts by holding warming to 1.5°C versus 2°C. Data sources: Burke etal. (2015b); (2018a); Diffenbaugh and Burke (2019).

agricultural drought (Hlalele etal., 2016). Drought and extreme heat

events have also reduced tourism revenues in Africa (Section9.6.3).

Infrastructure damage and transport disruptions from adverse climate

events reduce access to services and growth opportunities (Chinowsky

etal., 2014). In global data sets including Africa, tropical cyclones have

been shown to have large and long-lasting negative impacts on GDP

growth (Hsiang and Jina, 2014).

1387

Africa Chapter 9

9.11.1.2 Human Capital Development and Education

Investments in human capital, particularly education, are critical for

socioeconomic development and poverty reduction providing valuable

skills and expanding labour market opportunities. Much progress has

been made in improving education access, however, in sub-Saharan

Africa, 32% of children, adolescents and youth (~97million people)

remain out of school (UNESCO Institute of Statistics, 2018). Climate

variability and change can undermine educational attainment with

negative impacts on later life earning potential and adaptive capacity

to future climate change (Figure9.11; Lutz etal., 2014).

Several studies indicate that experiencing low rainfall, warming

temperatures or extreme weather events reduce education attainment

and that future climate change may reduce children’s school participation,

particularly for agriculturally dependent and poor urban households. In

west and central Africa, experiencing lower-than-average rainfall during

early life is associated with up to 1.8 fewer years of completed schooling

in adolescence, while more rainfall and milder temperatures during the

main agricultural season are positively associated with educational

attainment for boys and girls in rural Ethiopia (Randell and Gray, 2016;

Randell and Gray, 2019). In Uganda, low rainfall reduced primary

school enrolment by 5% for girls (Björkman-Nyqvist, 2013), and in

Malawi, in utero drought exposure was associated with delayed school

entry among boys (Abiona, 2017). In rural Zimbabwe, experiencing

drought conditions during the ﬁrst few years of life was associated with

fewer grades of completed schooling in adolescence, which translates

into a 14% reduction in lifetime earnings (Alderman etal., 2006). In

Cameroon, warming temperatures have negatively affected plantain

yields, which in turn is linked to lower educational attainment (Fuller

et al., 2018). One suggested mechanism underlying the relationship

between climate and schooling is that adverse climatic conditions

can reduce income among farming households, leading them to pull

children out of school (Randell and Gray, 2016; Marchetta etal., 2019).

Other potential mechanisms are poor harvests from droughts or supply

interruptions from extreme weather events leading to undernutrition

among young children, negatively affecting cognitive development and

schooling potential (Alderman etal., 2006; Bartlett, 2008).

More research is needed on climate change impacts on education

in Africa. This information can help ensure families keep children in

school amid climate-related income shocks. For example, in Mexico, a

conditional cash transfer programme mitigated the negative effect of

natural disasters on school attendance (de Janvry etal., 2006).

9.11.2 Projected Risks of Climate Change for African

Economies and Livelihoods

Future warming will have negative consequences for economic

growth in Africa, relative to a future without additional climate

change and assuming current levels of adaptation (high conﬁdence)

(Dell etal., 2012; 2015a; Burke etal., 2015b; Acevedo etal., 2017;

Baarsch et al., 2020). Statistically based empirical analyses project

that global warming of 2.3°C by 2050 could lower GDP per capita

across sub-Saharan Africa by 12% (SSP2) (Baarsch etal., 2020) and

80% for warming >4°C by 2100 (SSP5, 75% for MENA) (Burke etal.,

2015b). Depending on the future socioeconomic scenario, this could

increase global inequality and leave some African countries poorer

than at present (Burke etal., 2015b). Inequalities between African

countries are projected to widen under climate change, with negative

impacts estimated to be largest in west and east Africa (Baarsch etal.,

2020). While negative impacts across African economies are highly

likely under climate change, precise magnitudes are debated in the

literature. Alternative statistical analyses suggest a 12% reduction

of GDP per capita by 2100 under RCP8.5 across African countries

relative to a future without climate change (Kahn etal., 2021), while

computable general equilibrium models generate smaller damages as

well, ranging from 3.8% reduction across sub-Saharan Africa in 2060

under warming of 2.5°C (Dellink etal., 2019) to 12% across all of

Africa in 2100 under warming of 5°C (SSP4) (Takakura etal., 2019).

Substantial avoided economic damages to African countries are

projected from ambitious, near-term global mitigation limiting global

warming well below 2°C above pre-industrial levels (high conﬁdence).

Increased economic damage forecasts for Africa under high emissions

scenarios start diverging rapidly from low emissions scenarios by the

2030s (Baarsch etal., 2020). Across nearly all African countries, GDP

per capita is projected to be at least 5% higher by 2050 and 10–20%

higher by 2100 if global warming is held to 1.5°C versus 2°C (Burke

etal., 2018a; Baarsch etal., 2020) (Figure9.37). The probability of this

positive gain to GDP per capita from achieving 1.5°C versus 2°C is

reported as close to 100% (Burke etal., 2018a). While these estimates

rely on temperature and rainfall-driven damages, SLR also poses a risk

for Africa. By 2050, damages from SLR across sub-Saharan Africa could

reach 2–4% of GDP, depending on the socioeconomic, adaptation and

emissions scenario (Parrado etal., 2020).

Heat stress is projected to reduce working hours and work capacity

under climate change, with among the largest declines in sub-Saharan

Africa and for workers in vulnerable occupation groups, such as those

working outdoors (Kjellstrom etal., 2014; 2016; de Lima etal., 2021;

Chapter 5). Global warming of 3°C is projected to reduce labour

capacity in agriculture by 30–50% in sub-Saharan Africa (relative to

the baseline in 1986–2005) (de Lima etal., 2021). These effects lead

to substantial aggregate losses, for example, in west Africa, labour

productivity impacts under a 3°C temperature increase are estimated

to cost up to 8% of GDP (Roson and Sartori, 2016). Manufacturing

productivity across Africa is projected to decline under RCP8.5 by

0–15% by 2080–2099, with the largest effects in the DRC, Ethiopia,

Somalia, Mozambique and Malawi (Nath, 2020).

Large risks to road, rail and water infrastructure are projected from

climate change with substantial economic cost implications (see

Section9.9.3; Box9.5).

9.11.3 Informality

Aggregate GDP data capture formal economic activity but informal

employment is the main source of employment in Africa, accounting

for 85.8% of all employment (71.9%, excluding agriculture), which

is 21.4% higher than the global average (ILO, 2018b). Estimates of

national levels of informal employment range from 30% in South

1388

Chapter 9 Africa

Africa, to 94.6% in Burkina Faso (ILO, 2018b), with high variability

within countries such as South Africa and Nigeria (Etim and Daramola,

2020). Informal employment is a greater source of employment for

women than for men in sub-Saharan Africa and young and old have

especially high rates of informal employment: 94.9% of persons

between ages 15 and 24 in employment and 96% of persons aged 65

and older (ILO, 2018b).

Informal sector impacts are omitted from GDP-based impacts

projections. Yet, informal sector activity and small to medium-sized

enterprises can be highly exposed to climate extremes, as they are often

located in low-lying areas, coastal areas, sloped or other hazardous

zones (Thorn etal., 2015; Satterthwaite etal., 2020). Businesses and

individuals in the informal sector, including construction workers,

domestic workers, street vendors and transport workers, often cannot

operate during climate shocks due to interruptions in transportation

and commodity ﬂows and, without the ability to insure against risk,

struggle to recover assets from extreme events such as ﬂooding,

landslides and waterlogging (Chen, 2014; Thorn etal., 2015; Roy etal.,

2018a). Women are overrepresented in the more poorly remunerated

sections of the informal economy (Satterthwaite etal., 2020).

There is scope for governments to better harness the role of the

informal sector in mitigation and adaptation (Douxchamps etal., 2015;

Satterthwaite etal., 2020). Multi-level governance that includes informal

service providers, such as informal water and sanitation networks, into

planned adaptation programmes can increase climate resilience, in part

because these networks can respond with more ﬂexibility than hard

infrastructure projects (Satterthwaite etal., 2020; Peirson and Ziervogel,

2021). Climate risk is often concentrated in urban informal settlements

(Section 9.9.4). Here, informal land markets inﬂuence development

patterns and can help ensure adherence to building codes to ensure

safety of informally built structures at high risks of landslides and ﬂoods

and enforce compliance with regulations relating to planning and land

use (Thorn et al., 2015; Satterthwaite et al., 2020). Improving land

management practices of charcoal producers and artisanal gold miners,

combined with appropriate alternative livelihood and energy sources,

can reduce emissions and increase resilience (e.g., reduce erosion and

sedimentation, increase water inﬁltration) and beneﬁt health (Atteridge,

2013; Paz etal., 2015; Macháček, 2019; Barenblitt etal., 2021; Eniola,

2021). Providing concessional loans, commercial ﬁnancing or equity

investment to informal brick makers can boost delivery of low emission

social housing while the use of crop residues or renewable energy for

brick making can replace wood biomass and reduce pressure on forests

(Alam, 2006; Paz etal., 2015).

9.11.4 Climate Change Adaptation to Reduce

Vulnerability, Poverty and Inequality

High temperature-related income losses have been observed in both

low- and high-income countries, suggesting optimistic economic

development trajectories may not substantially reduce climate change

impacts on aggregate economic performance in Africa (low conﬁdence)

(Burke et al., 2015b; Deryugina and Hsiang, 2017; Henseler and

3 Extreme poverty is deﬁned using a consumption poverty line at USD1.25 per day, using 2005 purchasing power parity exchange rates.

Schumacher, 2019). Nevertheless, climate change impacts on poverty

in Africa will depend on how socioeconomic development unfolds over

the coming decades (medium conﬁdence) (Rozenberg and Hallegatte,

2015; Hallegatte and Rozenberg, 2017; Henseler and Schumacher,

2019). Climate change by 2030 is projected to push 39.7 million

Africans into extreme poverty3 under a baseline scenario of delayed

and non-inclusive growth, with food prices acting as the dominant

channel of impact, but this number is cut roughly in half under an

inclusive economic growth scenario (Rozenberg and Hallegatte, 2015;

Hallegatte and Rozenberg, 2017; Jaﬁno etal., 2020).

People in Africa are disproportionately employed in highly climate-

sensitive sectors: 55–62% of the sub-Saharan African workforce is

employed in agriculture and, although between 90–95% of cropland

is rainfed (Woodhouse etal., 2017; ILO, 2018a; International Institute

of Water Management, 2019; World Bank, 2020c), there has been an

expansion of small-scale ‘farmer-led irrigation’ (Woodhouse et al.,

2017). Agricultural GDP also appears more strongly affected by

increasing temperatures than non-agricultural GDP, implying livelihood

diversiﬁcation out of agriculture may help minimise future economic

damage (Bezabih etal., 2011; Burke etal., 2015b; Acevedo etal., 2017;

Deryugina and Hsiang, 2017), although such workforce reallocation

requires careful management and planning depending on the overall

livelihood portfolios, type of farmer and proﬁtability (Stringer etal.,

2020). De-agrarianisation can feed urbanisation, which may exacerbate

inequality within and between countries (Stringer etal., 2020).

Changes in trade patterns may help mitigate projected aggregate

economic losses by reallocating agricultural production abroad and

encouraging economic diversiﬁcation toward less affected sectors.

Temperature increases have been shown to lower agriculture and

manufacturing exports with especially large declines in poor countries

(Jones and Olken, 2010; Roberts and Schlenker, 2013). Further, imports

of agricultural products are projected to rise across most of Africa by

2080–2099 under a high emissions scenario (RCP8.5), with increases

ranging from ~30% of GDP in the Central African Republic to ~5%

of GDP in South Africa and Nigeria, although some countries will

experience increases in net agricultural exports (Nath, 2020). While

these reallocation effects may be large, current evidence is mixed

regarding whether such adjustment of production will dampen or

amplify overall social costs of climate change in Africa (Costinot etal.,

2012; Bren d’Amour etal., 2016; Wenz and Levermann, 2016; Nath,

2020), as food prices are projected to rise by 2080–2099 across all

African countries under a scenario with high challenges to mitigation

and adaptation (SSP3 and RCP8.5), with the largest price effects (up to

120%) experienced in Chad, Niger and Sudan (Nath, 2020). Moreover,

reallocating production of agriculture abroad could be maladaptive if

it leads to decline or replacement of traditional sectors by industrial

and service sectors, which could lead to land abandonment, food

insecurity and loss of traditional practices and cultural heritage (Thorn

etal., 2020; Gebre and Rahut, 2021; Nyiwul, 2021).

African countries have high inequality: the average within-country

share of income accruing to the top 10% of households was estimated

at 50% for 2019 (Robilliard, 2020). However, analysis of INDCs across 54

1389

Africa Chapter 9

African countries suggests current climate policies do not, on average,

target social inequality in energy, water and food security; proposed

mitigation and adaptation actions fell about 23% for every 1% rise

in social inequality across these sectors (Nyiwul, 2021). In contrast,

adaptation actions can be designed in ways that actively work towards

reducing inequality, whether gender, income, employment, education

or otherwise (Andrijevic etal., 2020).

In rural Africa, poor and female-headed households face greater

livelihood risks from climate hazards (high conﬁdence). Women

often constitute a high proportion of the informal workforce and

are also more likely to be unemployed than men (ILO, 2018a).

These factors leave women, and particularly female-headed

households, at greater risk of poverty and food insecurity from

climate hazards. Controlling for multiple factors, income of female-

headed households in agricultural districts in South Africa is more

vulnerable to precipitation variability than those headed by men

(Davidson, 2016; Flatø etal., 2017). Across nine countries in east

and west Africa women tend to control smaller plots of land that is

often of poorer quality, have less access to inputs such as fertilizer,

tools and improved seeds, have lower educational attainment and

beneﬁt less from extension services, government agencies and non-

governmental organisations (Perez etal., 2015). Gender assessments

prior to adaptation programmes can identify disparities in division

of labour and income and socio-cultural norms, hindering women

from holding leadership positions or determining livelihood and

resource-use activities, thereby helping ensure equitable beneﬁts

from livelihood diversiﬁcation and improving women’s working

conditions (ILO, 2018a). Gender-responsive policy instruments can

measure success using sex-disaggregated data to monitor impact

and meaningful participation in decision making (GCF, 2018b).

Exposure to climate hazards can trap poorer households in a cycle of

poverty (Dercon and Christiaensen, 2011; Sesmero etal., 2018) and

poor people in Africa are often more exposed to climate hazards

than non-poor people. For example, poor people live in hotter areas

in Nigeria and in multiple African countries, poor households are

more exposed to ﬂooding (Section 9.9.2; Hallegatte et al., 2016).

Daily wage labourers and residents of urban informal settlements

are vulnerable to heat stress because of the urban heat island effect

combined with congestion, little shade and ventilation (Bartlett, 2008).

Climate change can negatively affect household poverty through

price spikes, destroying assets or ability to invest in new assets and

reducing productivity (Hallegatte etal., 2016) with important impact

pathways operating through agriculture, ecosystem functioning and

health (Sections9.6; 9.8; 9.10; Chapters 5; 7; 8). Non-poor people can

lose more in absolute terms from climate shocks because of having

more assets and higher incomes, but in relative terms, poor people

often lose more than the non-poor. These relative losses matter most

for livelihoods and welfare (Hallegatte etal., 2016).

In Malawi, wealthier households were able to maintain more diversiﬁed

livelihoods, buffering them from extreme weather-related income

losses (Sesmero etal., 2018). Poorer households have limited access to

resources such as savings, credit, irrigation technologies and insurance,

which can lead to larger crop and other income losses from climate

hazards, preventing investments to improve resilience to future climate

shocks (Castells-Quintana etal., 2018). Poor households may reduce risk

or aid recovery by cooperating with other households in their community

to adapt collectively to climate change, for example, through informal

insurance networks (Paul etal., 2016; Wuepper etal., 2018). Prioritising

poor households for interventions including social protection, EbA,

universal healthcare, climate-smart buildings and agriculture, ﬂexible

work hours under extreme heat and early warning systems will increase

adaptation to climate shocks (Section 9.6.4; Chapter 6; Angula and

Menjono, 2014; Moosa and Tuana, 2014; Hallegatte etal., 2016; Day

etal., 2019). Pro-poor policies that link mitigation and adaptation, such

as using renewable energy to increase rural electriﬁcation or using

revenues from a carbon tax, combined with international ﬁnancial

support to increase social assistance, could support sustainable

eradication of poverty under near-term climate change (Hallegatte

etal., 2016; Aklin etal., 2018; Simpson etal., 2021c). Integrating urban

green infrastructure into adaptation planning in informal settlements

can simultaneously unlock pathways for inclusivity and social justice

(Section9.9.5; Tozer etal., 2020; Wijesinghe and Thorn, 2021).

Social protection has been used for decades, particularly in eastern and

southern Africa, to safeguard poor and vulnerable populations from

poverty and food insecurity (Niño-Zarazúa etal., 2012). Instruments of

social protection include public works programmes, cash transfers, in-

kind transfers, social insurance and microinsurance schemes that assist

individuals and households to cope during times of crisis and minimise

social inequality. Evidence from Ethiopia, Kenya and Uganda indicates

national social protection programmes are effective in improving

individual and household resilience to climate-related shocks, regardless

of whether they aim speciﬁcally to address climate risks (Ulrichs etal.,

2019). Strengthening social protection and better integrating climate

risk management into design of social protection programmes can help

build long-term resilience to climate change (Hallegatte etal., 2016;

Agrawal etal., 2019). For example, public works programmes can build

climate resilience by targeting soil, water and ecosystem conservation

and carbon sequestration, such as South Africa’s Working for Water

Programme that restores river catchments to reduce ﬁre risk and

increase water supplies (Turpie etal., 2008; Norton etal., 2020).

9.11.4.1 Climate Insurance

African countries and communities are inadequately insured against

climate risk. Insurance penetration is less than 2% of GDP (Swis Re,

2019) and 90% of natural catastrophe losses were uninsured in Africa

in 2018 (Swis Re, 2019) leaving a large risk protection gap. The cost of

reinsurance in Africa’s most mature insurance market—South Africa—

has increased since 2017 due to climate-related payouts (SAIA, 2018;

Simpson, 2020), which is expected to further reduce the extent of

insurance coverage. Emerging trends that seek to address this gap

include innovative weather and drought index-based insurance

schemes to transfer risk, forward-looking climate data and models to

manage risk and insurers transitioning from risk transfer providers to

proactive risk managers.

The most signiﬁcant area of climate risk insurance innovation has

occurred in weather and drought index-based insurance schemes that

pay out ﬁxed amounts based on the occurrence of an event instead

of full indemniﬁcation against assessed losses (Table9.12). However,

1390

Chapter 9 Africa

despite the relatively low cost, uptake remains low due to affordability

constraints, lack of awareness, access to and trust in products,

distribution challenges, basis risk, poor transparency, challenges

regarding the integration of complementary interventions (e.g., access

to improved inputs or informal savings/credit) and poor perceptions/

norms of insurance and risk transfer. Lack of data and models further

hinders insurers’ ability to price risk correctly, which reduces value to

clients (Greatrex et al., 2015; Di Marcantonio and Kayitakire, 2017;

WEF, 2021). Impact assessments point to potential but remain context-

speciﬁc (Awondo, 2019; Hansen etal., 2019b; Noritomo and Takahashi,

2020). In addition, there is no comprehensive overview of the number

of people covered by such schemes, nor of the value they provide in

terms of actual claims payouts. Lastly, donor and/or public funds still

play an outsized role in launching and/or sustaining these schemes

and schemes beyond weather and drought remain limited (Table9.12).

Insurers and their clients are often unaware of their risk exposure,

partly due to data and modelling gaps. Climate information services

and related collaborations are increasingly helping to address this

problem (see Section9.4.5). Climate change attribution methods to

estimate the contribution of human-casued climate change to the

cost of parametric insurance offers possibilities for a sharing of the

premium between the impacted African country and a global climate

fund, such as the GCF (New etal., 2020). Technology companies and

start-ups (including FinTechs) are also emerging as solutions to ﬁll risk

gaps, leveraging new approaches to data and technology through

the use of sensors, drones and satellite imaging to speak to mainly

agricultural risks, but also urban risks such as informal settlement ﬁres,

exacerbated by heat and drought (Table9.12).

Ten African insurers formally committed to help manage climate risk on

the continent through the Nairobi Declaration of the UNEP Principles

for Sustainable Insurance (PSI) in 2021 (UNEP PSI, 2021). Some

early examples of public–private partnerships with municipalities

and governments to better manage climate risk are also emerging

(Table9.12).

9.11.5 COVID-19 Recovery Stimulus Packages for Climate

Action

The COVID-19 pandemic recovery effort includes signiﬁcant opportunities

for African countries to reduce future vulnerability to compound climate,

economic and health risks. Fiscal recovery packages could set economies

on a pathway towards net-zero emissions, reducing future climate risk or

entrench fossil-fuel intensive systems, exacerbating risk (Hepburn etal.,

2020; Dibley etal., 2021; IEA, 2021). Investments in renewable energy,

building efﬁciency retroﬁts, education and training, natural capital (i.e.,

ecosystem restoration and EbA), R&D, connectivity infrastructure and

sustainable agriculture can help meet both economic recovery and

climate goals (Hepburn etal., 2020; Dibley etal., 2021).

The impacts of the COVID-19 pandemic have been substantially

worsened by climate hazards in many places. In others, outbreak

response has been disrupted (Phillips et al., 2020; Kruczkiewicz

etal., 2021). These vulnerabilities are rooted in insufﬁcient disaster

preparedness infrastructure but are almost always worsened by social

and economic inequality. Ensuring the most vulnerable populations

are properly protected from climate change has co-beneﬁts for

recovery from the COVID-19 pandemic (Manzanedo and Manning,

2020). In particular, efforts to reduce syndemic vulnerabilities across

key sectors (especially health, livelihoods and food security) will lessen

climate change impacts and will also reduce the risk and impacts of

future epidemics and pandemics, for example, during the pandemic,

water scarcity has been a barrier to a key risk mitigation behaviour

(hand washing). In the long-term, development efforts focused on

WASH will reduce this vulnerability and also reduce the health toll of

diarrheal disease linked to climate change (Anim and Ofori-Asenso,

2020; Zvobgo and Do, 2020). Spending recovery funds on social

safety nets will reduce inequality and protect the most vulnerable

communities (especially women and low-income and marginalised

communities) from the social and economic impacts of disasters. Key

among these safety nets is universal health coverage, including low- or

Table9.12 | Insurance opportunities to mitigate climate risk.

Initiatives Drought/

heatwave Flood Cyclone Fire Example Policyholders/

beneﬁciaries Reference

Index and

parametric

schemes—

smallholder farmer

X X

ACRE Africa, Pula, R4 Rural

Resilience Initiative, KLIP, FISP,

Ghana Agricultural Insurance

Pool, Oko Crop Assurance

Smallholder

farmers

Greatrex etal. (2015); CTA (2019); Global

Index Insurance Facility (2019); WFP

(2020); Fava etal. (2021); OKO Finance

(2021); Pula (2021); Tsan etal. (2021)

Index and

parametric schemes

– sovereign and

sub-sovereign

X X X African Risk Capacity Governments ARC (2019)

Index and

parametric schemes

– global

X X

African and Asian Resilience

in Disaster Insurance Scheme

(ARDIS)

Individuals and

smallholder farmers Global Parametrics (2018)

Risk management

and data

collaboration

X X X X

UNEP PSI

Santam

Tripartite Agreement

Insurers and

reinsurers, local

municipalities,

governments

Santam (2018); Forsyth etal. (2019);

UNEP-FI (2019a); InsurResilience (2020);

Simpson (2020)

FinTech X X X Lumkani, WorldCover, Econet,

PlaNet Guarantee

Individuals,

smallholder farmers

Greatrex etal. (2015); Hunter etal. (2018);

CTA (2019); UK Space Agency (2020); Tsan

etal. (2021)

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Africa Chapter 9

Box9.8 | Climate change, migration and displacement in Africa

Climatic conditions are important drivers of migration and displacement with migration responses to climate hazards strongly inﬂuenced

by economic, social, political and demographic processes (Cross-Chapter BoxMIGRATE in Chapter 7).

Most climate-related migration and displacement observed currently is within countries or between neighbouring countries, rather than

to more geographically distant high-income countries (Hoffmann etal., 2020; Kaczan and Orgill-Meyer, 2020). Natural disaster-related

displacements in sub-Saharan Africa were over 2.6million in 2018 and 3.4million in 2019 (13.9% of the global total and one of the

highest historical ﬁgures for the region), with east (1,437,7000) and west Africa (798,000) being hotspots in 2018 (Table Box9.8.1;

Mastrorillo etal., 2016; IDMC, 2019; IDMC, 2020). Estimates indicate future climate change effects on internal migration in Africa will be

considerable (Table Box9.8.1;Rigaud etal., 2018).

Internal migration, displacement and urbanisation

Climate change can have opposing inﬂuences on migration ﬂows. Deteriorating economic conditions caused by climate hazards can

encourage out-migration (Wiederkehr etal., 2018). However, these same economic losses undermine household resources needed to

migrate (Cattaneo and Peri, 2016). The net effect of these two forces leads to mixed results across study methodologies and contexts

(Carleton and Hsiang, 2016; Borderon etal., 2019; Cattaneo etal., 2019; Hoffmann etal., 2020).

Urbanisation in Africa is affected by climate conditions in rural agricultural areas (high conﬁdence). Urbanisation can increase when

reduced moisture availability depresses farm incomes or pastoral livelihoods become unviable (Marchiori etal., 2012; Henderson etal.,

2014; Mastrorillo etal., 2016). The inﬂuence of rainfall on rural–urban migration increased since decolonisation, possibly due to more

lenient legislation on internal mobility, with each 1% reduction in precipitation below a long-term average associated with a 0.45%

increase in urbanisation (Barrios et al., 2006). The rate of rural–urban migration is anticipated to increase (Neumann etal., 2015)

as a result of increasing vulnerability of agricultural livelihoods to climate change (Serdeczny etal., 2017). Nevertheless, rural–urban

migration is not a simple one-way process. Peri-urban and rural areas provide developmental feedback loops, helping create a ‘regional

agglomeration’ effect, for instance, through growing food demand, family and social connections, and ﬂows back to rural areas of goods

and services and ﬁnancial investments (UN-Habitat, 2016; Dodman etal., 2017).

Migration is an important and potentially effective climate change adaptation strategy in Africa and must be considered in adaptation

planning (high conﬁdence) (Williams etal., 2021). The more agency migrants have (that is, degree of voluntarity and freedom of movement),

the greater the potential beneﬁts for sending and receiving areas (high agreement, medium evidence) (Cross-Chapter BoxMIGRATE in

Chapter 7). In a synthesis of 63studies covering over 9700 rural households in dryland sub-Saharan Africa, 23% of households employed

migration (primarily temporary economic) to adapt to changes in rainfed agriculture (Wiederkehr etal., 2018). Migration responses

to climate change tend to be stronger among wealthier households, as poorer households often lack ﬁnancial resources necessary to

migrate (Kaczan and Orgill-Meyer, 2020).

International migration

Studies on propensity to emigrate have uncovered conﬂicting results. Some ﬁndings suggest in low-income countries high temperatures

‘trap’ people at home and lower migration rates abroad, but in middle-income countries, these same high temperatures encourage

emigration (Cattaneo and Peri, 2016). However, other research ﬁnds in poor and agriculturally dependent countries, high temperatures

encourage international out-migration, particularly to the OECD (Cai etal., 2016). Some evidence indicates people who leave tend to

be more educated, possibly leading to ‘brain drain’ (Mbaye, 2017). Recent evidence suggests hotter-than-normal temperatures across

103countries, including many in Africa, increased asylum applications to the European Union (Missirian and Schlenker, 2017). Assuming

no change in present-day vulnerability, asylum applications are projected to increase 34% across Africa (relative to 2000–2014) at 2.2°C

global warming (Missirian and Schlenker, 2017), although this ﬁnding has been challenged in the literature (Abel etal., 2019; Boas etal.,

2019).

International remittances are a vital resource for developing countries that can help aid recovery from climate shocks (Hallegatte etal.

2016). Estimated at USD48billion in 2019 their importance is expected to grow further due to foreign direct investment declines during

the COVID-19 pandemic (World Bank, 2020a). Furthermore, domestic remittances from rural–urban migration can help rural households

respond to climate risks (KNOMAD, 2016). However, adequate ﬁnance and banking infrastructure are essential for remittances and, on

average, cash transfer costs for sub-Saharan African countries remain the highest globally (World Bank, 2020a). Mobile money technologies

1392

Chapter 9 Africa

and regulation that promotes competition in the remittances market can reduce transaction costs (World Bank, 2020a). Governments can

further address challenges facing internal and international migrants by including them in health services and other social programmes

and protecting them from discrimination (World Bank, 2020a).

TableBox9.8.1 | Reported impacts of climate on migration in Africa. (Findings on the linkages between climatic conditions and migration vary greatly across countries

in Africa.)

Climate driver Country Climate – Migration linkages Reference

Temperature

Kenya Cool temperatures linked to internal labour migration among males. Gray and Wise (2016)

Uganda

High temperatures linked to increased non-labour migration among females.

Short hot spells linked to increased temporary migration. Long-term heat stress linked to

permanent migration through an agricultural livelihoods pathway.

Gray and Wise (2016); Call and Gray (2020)

Tanzania Temperature-induced income shocks linked to decreased long-term rural–urban migration

among men. Hirvonen (2016)

Precipitation

Kenya Increased precipitation linked to decreased rural–urban migration. Mueller etal. (2020)

Zambia Increased precipitation linked to increased internal migration. Mueller etal. (2020)

Burkina Faso

Drier regions linked to increased temporary and permanent migrations to other rural

areas. Short-term precipitation deﬁcits linked to increased long-term migration to rural

areas and decreased risk of short-term migration to distant destinations.

Henry etal. (2004)

Ethiopia

Drought linked to men’s rural–urban labour migration, especially in land-poor households.

Drought linked to decreased marriage-related migration by women.

Precipitation variability and drought linked to rural–urban labour migration.

Precipitation variability and drought linked to out-migration to communities where

precipitation variability and drought probability are lower.

High precipitation variability linked to increased migration, either through increased

non-farm activities, which enable migration through economic resources or through

insufﬁcient agricultural production, which increase migration needs.

Gray and Mueller (2012); Morrissey (2013);

Hermans-Neumann etal. (2017); Groth

etal. (2021)

Ghana Increased severity of drought and household insecurity linked to reduced future migration

intentions of households. Adger etal. (2021)

Malawi

Precipitation shocks linked to rural out-migration to communities where precipitation

variability and drought probability are lower.

Precipitation shocks (ﬂood and droughts) linked to longer-term urban migration and/or

reverse (i.e., urban–rural) migration.

Lewin etal. (2012); Suckall etal. (2015)

Mali

Decreased precipitation linked to overall increase in out-migration—where farming

families or individuals from farming communities will leave their origin community—and

some changes in duration and destination of trips. These moves can be either permanent

or short-term, domestic or international.

Grace etal. (2018)

Niger Drought linked to economically induced migration of households from rural areas to

cities. Drought also linked to temporary international migration. Aﬁﬁ (2011)

Temperature and

precipitation

Burkina Faso

High temperatures linked to negative effects on all migration streams including

international migration, much of which is to neighbouring countries. International

migration also declines with precipitation.

Gray and Wise (2016)

Senegal No detected linkages between climate and migration. Gray and Wise (2016)

Nigeria No detected linkages between climate and migration. Gray and Wise (2016)

Botswana Increased temperatures and precipitation linked to decreased internal migration. Mueller etal. (2020)

South Africa Higher temperatures and precipitation extremes linked to increased rural out-migration,

especially among black and low-income South Africans. Mastrorillo etal. (2016)

Senegal Precipitation variability, drought and increased temperatures linked to seasonal migration

from rural to urban areas. Hummel (2016)

Zambia Hotter and drier climate linked to inter-district migration of wealthy districts. Poor districts

characterised by climate-related immobility. Nawrotzki and DeWaard (2018)

Box9.8 (continued)

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Africa Chapter 9

TableBox9.8.2 | Projected numbers and shares of internal climate migrants in 2050 by sub-regions of sub-Saharan Africa. Projections are for internal migration

driven by three slow-onset climate hazards (water stress, crop failure and SLR), and excluding rapid-onset hazards such as ﬂoods and tropical cyclones. As such, they

present a lower-bound estimate of potential climate change impacts on internal migration. Projections are for two warming scenarios: low emissions (RCP2.6) and high

emissions (RCP8.5), both coupled with a socioeconomic pathway (SSP4) in which low-income countries have high population growth, high rates of urbanisation, and

increasing inequality within and among countries. By 2050, between 17.4million (RCP2.6) and 85million (RCP8.5) people (up to 4% of the region’s total population)

could be moving as a consequence of climate impacts on water stress, crop productivity and SLR. More inclusive socioeconomic pathways with lower population growth

are projected to reduce these risks. West Africa has the highest levels of climate migrants, potentially reaching more than 50million, suggesting that climate impacts will

have a particularly pronounced impact on future migration in the region. In east Africa, out-migration hotspots include coastal regions of Kenya and Tanzania, western

Uganda and parts of the northern highlands of Ethiopia. Kampala, Nairobi and Lilongwe may become hotspots of climate in-migration, coupled with existing rural to urban

migration trends, and a high likelihood of movement toward non-climate-related sources of income in cities. Source: (Rigaud etal., 2018).

Region

Global warming around 2.5°C

above pre-industrial by 2050

(RCP8.5)

Global warming around 1.7°C

above pre-industrial by 2050

(RCP2.6)

East Africa Average number of internal migrants by 2050 (million) 10.1 6.9

Internal climate migrants as percent of population 1.28% 0.87%

West Africa Average number of internal migrants by 2050 (million) 54.4 17.9

Internal climate migrants as percent of population 6.87% 2.27%

Central Africa Average number of internal migrants by 2050 (million) 5.1 2.6

Internal climate migrants as percent of population 1.31% 0.66%

Southern Africa Average number of internal migrants by 2050 (million) 1.5 0.9

Internal climate migrants as percent of population 2.31% 1.40%

Sub-Saharan Africa

Average number of internal migrants by 2050 (million) 71.1 28.3

Minimum (left) and maximum (right) million 56.6 85.7 17.4 39.9

Internal climate migrants as percent of population 3.49% 1.39%

Minimum (left) and maximum (right) percent 2.71% 4.03% 0.91% 2.04%

no-cost access to essential medicine, high-quality preventative care,

ﬁnancial protections against medical debt and increased geographic

and population coverage for all services (Hallegatte etal., 2016). All of

these are key components of climate change adaptation for health and

will reduce both the rate at which future outbreaks start and their total

scope and impact (Carlson etal., 2021). The co-beneﬁts of multilateral

cooperation on the attainment of universal health coverage will be a

key determinant of success or failure in both climate change adaptation

and pandemic preparedness.

9.12 Heritage

Africa is a rich reservoir of heritage resources and Indigenous

Knowledge, showcased by about 96 sites inscribed by the United

Nations Educational, Scientiﬁc and Cultural Organization (UNESCO)

as World Heritage Sites (UNESCO, 2018b). These include 53 sites

speciﬁcally denoted as having great cultural importance and ﬁve sites

with mixed heritage values. Unfortunately, valuable cultural heritage

in forms of tangible evidence of past human endeavour, and the

intangible heritage encapsulated by diverse cultural practices of many

communities (Feary etal., 2016), is under great threat from climate

change.

9.12.1 Observed Impacts on Cultural Heritage.

For more than 10,000years, Africans recorded over 8000 painted and

engraved images on rock shelters and rock outcroppings across 800

known exceptional rock art sites of incalculable value (Hall etal., 2007;

di Lernia and Gallinaro, 2011; di Lernia, 2017; Clarke and Brooks, 2018;

Barnett, 2019), but which are exceptionally fragile to the elements.

Unfortunately, there has been a poor study of direct climate change

impacts on rock art across Africa.

Underwater heritage includes shipwrecks and artefacts lost at sea

and extends to prehistoric sites, sunken towns and ancient ports that

are now submerged due to climatic or geological changes (Spalding,

2011). Off the shores of Africa, about 111 shipwrecks have been

documented, with South Africa having a major share of about 41

sites. The sunken Egyptian city of Thonis-Heracleion and its associated

60+ shipwrecks reﬂect the richness of Africa’s waters. Unfortunately,

increased storm surges and violent weather currently threaten the

integrity of shipwrecks by accelerating the destruction of wooden

parts and other features (Harkin etal., 2020). However, climate change

impacts on underwater cultural heritage sites are poorly studied, as

it requires specialist assessment techniques (Feary etal., 2016), and

marine archaeology studies are not well established in Africa.

Box9.8 (continued)

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Chapter 9 Africa

Box9.9 | Climate Change and Security: Interpersonal Violence and Large-scale Civil Conﬂict

There is substantial evidence that climate variability inﬂuences human security across Africa (see Chapter7 Sections7.2.7; 7.3.3 7).

However, the strength and nature of this link depend on socioeconomic and institutional conditions, and climate is just one of many

factors inﬂuencing violence and civil conﬂict (Schleussner etal., 2016a; von Uexkull etal., 2016; Linke etal., 2018; Mach etal., 2019; van

Weezel, 2019; Ide etal., 2020).

Projections of security implications of long-run climate change in Africa are uncertain, as they rely on extrapolating observed effects of

short-run climate variability (Burke etal., 2014). Lack of detection and attribution studies limit assessment of the impacts of observed

human-caused climate change on security.

Interpersonal violent crime

Evidence from across the globe ﬁnds that interpersonal violence, ranging from use of profanity to violent crime, increases with temperature

and sometimes low rainfall (Hsiang etal., 2013a; Burke etal., 2014; Gates etal., 2019). The effect of temperature may be driven by a

physiological mechanism (Morrison etal., 2008; Seo etal., 2008; Ray etal., 2011), while effects of rainfall may operate through an

agricultural yield impacts channel (Burke etal., 2014). While few studies link interpersonal violence to climate in Africa, Gates etal.

(2019) documents homicide risks increasing under high temperatures in South Africa, and similarity across diverse study settings suggests

temperature-induced violent crime likely generalises to Africa (Burke etal., 2014).

Large-scale intergroup conﬂict

Climatic conditions also change the risk of large-scale conﬂicts such as riots, ethnic conﬂicts and civil war (Burke etal., 2014; Koubi, 2019).

The effects of temperature are particularly well-studied in Africa. Risk of violent conﬂict rises with temperature in Sudan and South Sudan

(Maystadt and Ecker, 2014; Maystadt etal., 2014; Scheffran etal., 2014), Kenya (Hsiang etal., 2013b; Scheffran etal., 2014), the east

African region (O’Loughlin etal., 2012) and across sub-Saharan Africa (Burke etal., 2009; O’Loughlin etal., 2014; Witmer etal., 2017).

Estimates indicate that warming trends since 1980 have elevated conﬂict risk across sub-Saharan Africa by 11% (Burke etal., 2009;

Carleton etal., 2016).

Periods of low rainfall or ﬂooding also contribute to social instability and upheaval across Africa (Miguel etal., 2004; Ralston, 2015; von

Uexkull etal., 2016; Harari and Ferrara, 2018; van Weezel, 2019; Ide etal., 2020). The link between rainfall and conﬂict appears likely

due to crop losses and declines in economic opportunity. One study found that dry growing seasons increase conﬂict incidence across

36 African nations, with spillover effects from the location of climate shock to neighbouring communities (Harari and Ferrara, 2018).

Conﬂict-inducing impacts of drought have also been uncovered in Somalia (Maystadt and Ecker, 2014), Uganda, Sudan, Ethiopia and

Kenya (Fjelde and von Uexkull, 2012; Hendrix and Salehyan, 2012; Couttenier and Soubeyran, 2014; Ralston, 2015; Linke etal., 2018;

van Weezel, 2019), the DRC (von Uexkull etal., 2020) and in a pooled sample of African and Asian countries (von Uexkull etal., 2016).

Extremely high rainfall may also incite conﬂict risk, although results are mixed (Hendrix and Salehyan, 2012; Raleigh and Kniveton, 2012).

This uncertainty, combined with large uncertainties in rainfall projections under climate change, render future impacts of human-caused

greenhouse gas emissions on rainfall-induced conﬂict in Africa highly uncertain.

While conﬂict–climate links have been repeatedly identiﬁed in Africa, climate is one of many interacting conﬂict risk factors and appears

to explain only a small share of total variation in conﬂict incidence (von Uexkull etal., 2016; Mach etal., 2019; van Weezel, 2019).

Opportunities for adaptation

Adaptive capacity with respect to climate and conﬂict remains low in Africa (Sitati etal., 2021). For example, one study found that,

relative to each country’s optimal annual temperature, realised temperatures across sub-Saharan Africa increase the annual incidence

of war by 29.3% on average (Carleton etal., 2016). Another ﬁnds that rising temperatures due to climate change may lead to higher

levels of violence in sub-Saharan Africa if political rights do not improve from current conditions (Witmer etal., 2017). Available studies

on adaptation in conﬂict-affected areas tend to have a narrow focus, particularly on agriculture-related adaptation in rural contexts and

adaptation by low-income actors, with little known beyond these contexts (Sitati etal., 2021). Literature on the gender dimension of

climate adaptation in conﬂict-affected countries is also limited (Sitati etal., 2021).

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Africa Chapter 9

Migration is a common response (Sitati etal., 2021) and may be an effective adaptive response to climate-induced conﬂict. Bosetti etal.

(2018) ﬁnd that countries with high emigration propensity display lower sensitivity of conﬂict to temperature, with no evidence of

detrimental impacts on the destination countries. IK has also been applied to enable adaptation amidst conﬂict, for example, in Libya, to

deal with erratic rainfall (Biagetti, 2017).

Other socioeconomic factors have been identiﬁed as adaptive opportunities. Rising incomes may mitigate conﬂict–climate relationships

(Carleton etal., 2016), while weak institutions, lack of political freedom, agricultural dependence and exclusion of ethnic groups increase

their strength (Schleussner etal., 2016a; von Uexkull etal., 2016; Witmer etal., 2017; Ide etal., 2020). In particular, agriculturally dependent

and politically excluded groups in Africa are especially vulnerable to the impact of drought on conﬂict (von Uexkull etal., 2016; Koubi,

2019). Household-level resilience to economic shocks has been shown to lower support for violence after drought (von Uexkull etal., 2020).

Local-level institutions have also been shown to support non-violence under adverse climate conditions (Bogale and Korf, 2007).

These ﬁndings suggest that ameliorating ethnic tensions, improving political institutions and investing in economic diversiﬁcation and

household resilience could mitigate future impacts of climate change on conﬂict.

Box9.9 (continued)

Intangible heritage includes instruments, objects, artefacts and cultural

spaces associated with communities, and are almost always held orally

(UNESCO, 2003). Loss of heritage assets may be a direct consequence

of climate change/variability (Markham etal., 2016), or a consequence

of indirect factors resulting from climate change, for example, economic

instability and poor decision making in areas of governance. In northern

Nigeria, climate change exacerbates the impact of poor land use

decisions, reducing the ﬂow of the Yobe River and negatively impacting

the Bade ﬁshing festival because the available ﬁsh species continue

to decline (Oruonye, 2010). Similarly, Lake Sanké in Mali has been

degraded by a combination of urban development and poor rainfall,

threatening the Sanké mon collective ﬁshing rite (UNESCO, 2018b).

Migration related to climate change and climatic events could offer

openings to women and young people to become de facto family

heads (Kaag etal., 2019). However, such societal changes also increase

community vulnerability to the loss of cultural knowledge held by village

elders. For example, in Mauritius, the Sega tambour Chagos music is at

risk, as elders familiar with the landscape pass on (Boswell, 2008).

9.12.1.1 Case Study: Traditional Earthen ‘Green Energy’ Buildings

Historically, Africa has had a unique and sustainable architecture (Diop,

2018) characterised by area-speciﬁc, traditional earthen materials and

associated Indigenous technology. Key examples include Tiébélé in

Burkina Faso, Walata in Mauritania, Akan in Ghana, Ghadames in Libya,

Old Towns of Djenné in Mali (World Heritage Site) and other diverse

earthen architecture across sub-Saharan Africa. Adegun and Adedeji

(2017) indicate that earthen materials provide advantages in thermal

conductivity, resistivity and diffusivity, indoor and outdoor temperature,

as well as cooling and heating capacities. Moreover, earthen materials

are recyclable and environmentally ‘cleaner’ (Sanya, 2012) because of

the absence or small quantity of cement in production, thus reducing

carbon emissions. Despite these advantages, the expertise and socio-

cultural ceremonies that accompany building and renewal of earthen

architecture are disappearing fast (Adegun and Adedeji, 2017). Further,

earthen construction is being threatened by extreme climatic variability

and changing climate that exacerbates decay (Brimblecombe et al.,

2011; Bosman and Van der Westhuizen, 2014; Brooks etal., 2020).

9.12.2 Projected Risks

Sea level rise (SLR) and its associated hazards will present increasing

climate risk to African heritage in the coming decades (Figure9.38;

Marzeion and Levermann, 2014; Reimann etal., 2018; Brito and Naia,

2020). Although no continental assessment has quantiﬁed climate

risk to African heritage and little is known of near-term exposure to

hazards such as SLR and erosion, for a handful of coastal heritage

sites included in global or Mediterranean studies, 10 cultural sites are

identiﬁed to be physically exposed to SLR by 2100 at high emissions

scenarios (RCP8.5) (Marzeion and Levermann, 2014; Reimann etal.,

2018), of which, seven World Heritage Sites in the Mediterranean are

also projected to face medium or high risk of erosion (Figure9.38;

Reimann etal., 2018). Further, Brito and Naia (2020) identify natural

heritage sites across 27 African countries that will be affected by

SLR by 2100 (RCP8.5), of which 15 sites covering eight countries

demonstrated a high need for proactive management actions because

of high levels of biodiversity, international conservation relevance and

exposure to SLR (Figure9.38). These nascent studies highlight the

potential severity of risk and loss and damage from climate change

to African heritage, as well as gaps in knowledge of climate risk to

African cultural and natural, particularly concerning bio-cultural

heritage.

Although climate change is a signiﬁcant risk to heritage sites (Brito

and Naia, 2020), there is little research on how heritage management

is adapting to climate change, and particularly, whether the capacity

of current heritage management systems can prepare for and deal with

consequences of climate change (Phillips, 2015; see also Cross-Chapter

BoxSLR in Chapter 3).

Worsening climate impacts are cumulative and often exacerbate

the vulnerability of cultural heritage sites to other existing risks,

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Chapter 9 Africa

including conﬂict, terrorism, poverty, invasive species, competition

for natural resources and pollution (Markham et al., 2016). These

issues may affect a broad range of tourism segments, including beach

vacation sites, safari tourism, cultural tourism and visits to historic

cities (UNWTO, 2008). Climate change impacts have the potential to

increase tourist safety concerns, especially at sites where increased

intensity of extreme weather events or vulnerability to ﬂoods and

landslides are projected (Markham etal., 2016) (see also Cross-Chapter

BoxEXTREMES in Chapter 2). There may also be circumstances where

interventions required to preserve and protect the resource alter its

cultural signiﬁcance (van Wyk, 2017).

9.12.3 Adaptation

Research highlights potential in integrating Indigenous Knowledge,

land use practices, scientiﬁc knowledge and heritage values to co-

produce tools that reﬁne our understanding of climate change and

variability and develop comprehensive heritage adaptation policy

(Table9.13; Ekblom etal., 2019).

Conservation of heritage may require offsetting the impact of loss

through partial or total excavation under certain circumstances, like

environment instability, or where in situ heritage preservation is

exorbitant in cost (Maarleveld and Guérin, 2013).

Risk to Africa’s cultural and natural coastal heritage sites from sea level rise and erosion by 2100 (RCP8.5)

(a) Cultural sites exposed to sea level rise and erosion

(b) 15 natural sites of conservation priority exposed to sea level rise

* = Cultural sites exposed to sea level rise and facing

medium and high risk of erosion

Figure9.38 | Risk to Africa’s cultural and natural coastal heritage sites from see level rise (SLR) and erosion by 2100.

(a) World Heritage Sites projected to be exposed to ﬂooding from SLR under a high emission scenario (RCP8.5) by 2100 (Marzeion and Levermann, 2014; Reimann etal., 2018).

For north Africa, multiple sites are already identiﬁed to be at medium or high risk from erosion under both current and future SLR conditions (Reimann etal., 2018). At the time of

assessment erosion risk had not been assessed for other African regions

(b) The 15 African natural sites (coastal protected areas) projected to be most exposed to negative impacts from SLR and thus as priority sites for adaptation (Brito and Naia, 2020).

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Africa Chapter 9

Table9.13 | Examples of responses to climate change impacts to heritage sites.

Heritage Type Example

Type of

climate

impact

Intervention

focus or

activity

Main

intervention

activity

State of materials Final state

of heritage Literature

Tangible

Ancient

Historic

buildings

Ounga

Byzantine Fort

and associated

archaeological

remains, Tunisia

Coastal

erosion

Archaeological

conservation

of fort

Building repairs

to outer walls

of fort but other

archaeological

areas no

intervention

Mixed. Fort is in

good condition,

but other parts of

the site are under

threat of coastal

erosion, particularly

lesser archaeological

remains of other

periods.

Some aspects

of site well

preserved,

other parts

damaged.

Slim etal.

(2004)

Archaeological

sites

Sabratha,

Roman City,

Libyan coast

SLR, local

ﬂooding

and coastal

erosion

Monitoring of

condition None

Loss of

archaeological

remains into the sea.

Some aspects

of site well

preserved,

other parts

damaged.

Abdalahh

(2011)

Living

Cities/towns

Lamu Old Town

and archipelago,

Kenya

SLR

impacting

low-lying

areas and

climate

variability

impacting

protective

mangroves

Lamu Old

Town managed

by National

Museums of

Kenya the

mangrove forests

by Community

Forest

Associations

and Forest

Conservation and

Management Act

of 2016

Changes in

biodiversity and

cultural resilience

to climate shocks

Draft for

National Policy

for Disaster

Management in

Kenya

Mangrove forests

provide protection

from storm surges

and coastal erosion.

Changing biodiversity

of mangroves

is threatening

mangroves which

threaten Lamu Old

Town.

Continuing

deterioration.

Wanderi

(2019)

Mud buildings Tiébélé, Burkina

Faso

Climate

variability

causing

ﬂooding,

erosion.

Local community

conservation

Improvements

to drainage and

land security,

development of

conservation and

management

plans

Current and ongoing

conservation. Stable.

Birabi and

Nawangwe

(2011)

Bio-cultural Rock art

Golden Gate

Highlands,

South Africa

Precipitation

and

atmospheric

changes

causing

luxuriant

lichen

growth

Monitoring of

condition

No known

intervention

Biodeterioration of

condition of rock

surface.

Increasing

loss of rock

surfaces and

images on the

rock surfaces.

Viles and

Cutler

(2012)

Although many underwater shipwrecks and ruins of cities are currently

preserved better in situ than similar sites on land (Feary etal., 2016),

preserving such heritage is often ﬁnancially prohibitive with many

physical and technical challenges. Further, skill capacities of heritage

agencies are limited to a few qualiﬁed archaeologists in Africa

(Maarleveld and Guérin, 2013).

For centuries, Africans have drawn on intangible heritage to enhance

their resilience to climatic variability and support adaptation practices.

For example, pastoralist communities have historically translated their

experiences into memories that can be ‘translated’ into diverse adaptive

practices (Oba, 2014). In coastal Kenya, Mijikenda communities rely

on Indigenous Knowledge and practices used in the management of

the sacred Kaya Forests to adapt their farming to a changing climate

(Wekesa etal., 2015).

Hence, preservation measures for transforming oral information into

written records should ensure viability of intangible cultural heritage by

giving due consideration to the conﬁdentiality of culturally sensitive

information and intellectual property rights (Feary etal., 2016).

1398

Chapter 9 Africa

Heritage Type Example

Type of

climate

impact

Intervention

focus or

activity

Main

intervention

activity

State of materials Final state

of heritage Literature

Intangible

(Indigenous)

Language

!Xun and Khwe

Indigenous

Youth of South

Africa

Climate

variability

causing

drought

and loss of

plants

Groups (youth) Documentation Non-formal, local. Enhancement,

promotion.

Bodunrin

(2019)

Indigenous

Language Use

in Agricultural

Radio

Programming in

Nigeria

Climate

variability

increasing

frequency of

drought

Farmer groups,

communities

Research,

documentation Formal, local Promotion,

transmission.

Adeyeye

etal.

(2020)

Rituals

Enkipaata,

Eunoto and

Olng’esherr

Maasai male

rites of passage

Climate

variability

causing

drought

Maasai

community

groups

Identiﬁcation,

documentation,

research

Formal, non-formal,

local, foreign. Promotion. UNESCO

(2018a)

Customs &

beliefs

Sanké mon

ﬁshing festival

in Mali

Climate

variability

reducing

rainfall

Malinkés,

Bambara

and Buwa

communities

Identiﬁcation,

documentation,

preservation

Formal, non-formal,

local. Promotion. UNESCO

(2009)

Indigenous

engineering

systems

Water

measurers of

the Foggara

irrigation system

in Algeria

Increased

siltation and

sandstorms

Climate

variability

causing

ﬂooding

Touat and Tidikelt

communities

Research,

identiﬁcation,

documentation

Formal, local. Transmission.

Mokadem

etal.

(2018)

Arts and crafts Traditional crafts

made from

various parts

of the Date

Palm in Egypt,

Mauritania,

Morocco, Sudan,

Tunisia and

other countries

outside Africa

Climate

variability

causing

shift in plant

habitats

Residents of

oases, groups,

communities,

agricultural

cooperative

societies

Research,

identiﬁcation,

documentation,

preservation,

protection

Formal, non-formal,

local, foreign.

Transmission,

promotion,

enhancement,

revitalisation.

UNESCO

(2003)

Shabani

etal.

(2012)

Inclusion of cultural landscapes and intangible heritage in the landscape

approach at the regional scale development planning processes may

have signiﬁcant impacts on protected area management (Feary etal.,

2016). For example, at the Domboshava rock art site in Zimbabwe, all

management decisions are taken in direct consultation with traditional

leaders and other stakeholders from surrounding communities (Chirikure

etal., 2010). Such adaptation strategies promote a more open-minded

approach to heritage by leveraging local development (UNESCO, 2018b).

Lack of expertise and resources, together with legislation that privileges

certain typologies of heritage, seem to limit implementation of approved

policies (Ndoro, 2015). Additionally, cultural heritage has least priority

in terms of budgetary allocation, capacity building and inclusion into

school curricula. Failure to consider the views of people who attach

spiritual signiﬁcance to places is detrimental to the conservation of

heritage places (Bwasiri, 2011). In particular, documented cases of local

people having to pay an entrance fee, like tourists, to access burial

grounds and places of pilgrimage negate local participation in cultural

site management (Ndoro, 2015).

In the long term, heritage managers and local authorities could shift

from planning primarily for disaster response and recovery to strategies

that focus on disaster preparedness, reducing the vulnerability of

sites and strengthening resilience of local communities (UNFCCC,

2007; Domke and Pretzsch, 2016). This could evolve into innovative

approaches that integrate community, government and the research

sector in productive cultural heritage management partnerships.

There is a need for institutions to establish, maintain and update a

comprehensive inventory of underwater cultural heritage. This can be

done using non-intrusive, detailed mapping of the wreck site and a

three-dimensional model from which scientists can reconstruct the site

in detail (Maarleveld and Guérin, 2013).

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Africa Chapter 9

Frequently Asked Questions

FAQ 9.1 | Which climate hazards impact African livelihoods, economies, health and well-being the most?

Climate extremes, particularly extreme heat, drought and heavy rainfall events, impact the livelihoods, health, and well-being of millions of

Africans. They will also continue to impact African economies, limiting adaptation capacity. Interventions based on resilient infrastructure and

technologies can achieve numerous developmental and adaptation co-beneﬁts.

Multi-year droughts have become more frequent in west Africa, and the 2015–2017 Cape Town drought was three

times more likely due to human-caused climate change. Above 2°C global warming, drought frequency is projected

to increase, and duration will double from approximately 2 to 4months over north Africa, the western Sahel and

southern Africa. Estimates of increased exposure to water stress are higher than those for decreases. By 2050,

climate change could expose an additional 951 million people in sub-Saharan Africa to water stress while also

reducing exposure to water stress by 459million people. Compared to population in 2000, human displacement

due to river ﬂooding in sub-Saharan Africa is projected to triple for a scenario of low population growth and 1.6°C

global warming. Changing rainfall distributions together with warming temperatures will alter the distributions

of disease vectors like mosquitoes and midges. Malaria vector hotspots and prevalence are projected to increase

in east and southern Africa and the Sahel under even moderate greenhouse gas emissions scenarios by the 2030s,

exposing an additional 50.6–62.1million people to malaria risk.

Increases in the number of hot days and nights, as well as in heatwave intensity and duration, have had negative

impacts on agriculture, human health, water availability, energy demand and livelihoods. By some estimates, African

countries’ Gross Domestic Product per capita is on average 13.6% lower since 1991 than if human-caused global warm-

ing had not occurred. In the future, high temperatures combined with high humidity exceed the threshold for human

and livestock tolerance over larger parts of Africa and with greater frequency. Increased average temperatures and

lower rainfall will further reduce economic output and growth in Africa, with larger negative impacts than on other

regions of the world.

Resilient infrastructure and technologies are required to cope with the increasing climate variability and change

(FigureFAQ9.1.1). These include improving housing to limit heat and exposure, along with improving water and

sanitation infrastructure. Such interventions to ensure that the most vulnerable are properly protected from climate

change have many co-beneﬁts, including for pandemic recovery and prevention.

1400

Chapter 9 Africa

Climate hazards

Extreme weather

Extreme temperatures, heat

Reduced precipitation, drought

Direct influences on Health & wellbeing

Food

Water

Ecosystem

Shelter/housing

Poverty

Cities/community

A schematic illustration of the interconnectedness of different sectors and impacts

FigureFAQ9.1.1 | A schematic illustration of the interconnectedness of different sectors and impacts that spillover to affect the health and

well-being of African people.

Box FAQ 9.1 (continued)

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Africa Chapter 9

Frequently Asked Questions

FAQ 9.2 | What are the limits and beneﬁts of climate change adaptation in Africa?

The capacity for African ecosystems to adapt to changing environmental conditions is limited by a range of factors, from heat tolerance to

land availability. Adaptation across human settlements and food systems are further constrained by insufﬁcient planning and affordability.

Integrated development planning and increasing ﬁnance ﬂows can improve African climate change adaptation.

With increasing warming, there is a lower likelihood species can migrate rapidly enough to track shifting climates,

increasing extinction risk across more of Africa. At 2°C global warming more than 10% of African species are at

risk of extinction. Species ability to disperse between areas to track shifting climates is limited by fencing, transport

infrastructure, and the transformation of landscapes to agriculture and urban areas. Many species will lose large

portions of their suitable habitats due to increases in temperature by 2100. Coupled with projected losses of Africa’s

protected areas, higher temperatures will also reduce carbon sinks and other ecosystem services. Many nature-based

adaptation measures (e.g., for coral reefs, mangroves, marshes) are less effective or no longer effective above

1.5°C of global warming. Human-based adaptation strategies for ecosystems reach their limits as availability and

affordability of land decreases, resulting in migration, displacement and relocation.

The limits to adaptation for human settlements arise largely from developmental challenges associated with

Africa’s rapid urbanisation, poor development planning, and increasing numbers of urban poor residing in informal

settlements. Further limits arise from insufﬁcient consideration of climate change in adaptation planning and

infrastructure investment and insufﬁcient ﬁnancial resources. There are also limits to adaptation for food production

strategies. Increasing climate extreme events—droughts and ﬂoods—impose speciﬁc adaptation responses which

poorer households cannot afford. For instance, the use of early maturing or drought-tolerant crop varieties may

increase resilience, but adoption by smallholder farmers is hindered by the unavailability or unaffordability of seed.

Adaptation in Africa can reduce risks at current levels of global warming. However, there is very limited evidence

for the effectiveness of current adaptation at increased global warming levels. Ambitious, near-term mitigation

would yield the largest single contribution to successful adaptation in Africa.

Current adaptation ﬁnance ﬂows are billions of USD less than the needs of African countries and around half

of ﬁnance commitments to Africa reported by developed countries remain undisbursed. Increasing adaptation

ﬁnance ﬂows by billions of dollars (including public and private sources), removing barriers to accessing ﬁnance and

providing targeted country support can improve climate change adaptation across Africa.

Frequently Asked Questions

FAQ 9.3 | How can African countries secure enough food in changing climate conditions for their growing

populations?

Climate change is already impacting African food systems and will worsen food insecurity in sub-Saharan Africa in the future. An integrated

approach to adaptation planning can serve as a ﬂexible and cost-effective solution for addressing African food security challenges.

Maize and wheat yields have decreased an average of 5.8% and 2.3%, respectively, in sub-Saharan Africa due to

climate change. Among the 135million acutely food-insecure people in crisis globally, more than half (73million)

are in Africa. This is partly due to the growing severity of drought with increasing temperatures also a severe risk

factor. Adding to these challenges, Africa has the fastest-growing population in the world that is projected to grow

to around 40% of the world’s population by 2100.

Sustainable agricultural development combined with enabling institutional conditions, such as supportive governance

systems and policy, can provide farmers with greater yield stability in uncertain climate conditions. It is also widely

acknowledged that an integrated approach for adaptation planning that combines (a) climate information services,

(b) capacity building, (c) Indigenous and local knowledge systems and (d) strategic ﬁnancial investment can serve as

a ﬂexible and cost-effective solution for addressing African food security challenges.

1402

Chapter 9 Africa

Frequently Asked Questions

FAQ 9.4 | How can African local knowledge serve climate adaptation planning more effectively?

A strong relationship between scientiﬁc knowledge and local knowledge is desirable, especially in developing contexts where technology for

prediction and modelling is least accessible.

In many African settings, farmers use the local knowledge gained over time—through experience and passed on

orally from generation to generation—to cope with climate challenges. Indigenous Knowledge systems of weather

and climate patterns include early warning systems, agroecological farming systems and observation of natural

or non-natural climate indicators. For instance, biodiversity and crop diversiﬁcation are used as a buffer against

environmental challenges: if one crop fails, another could survive. Local knowledge of seasons, storms and wind

patterns is used to guide and plan farming and other activities.

Collaborative partnerships between research, agricultural extension services and local communities would create

new avenues for the co-production of knowledge in climate change adaptation to better inform adaptation policies

and practices across Africa.

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Building resilience and enhancing nutrition in Africa's food systems

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Vulnerability of Urban Housing to Climate Change in Cameroon

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Apr 2025

Climate change impacts on human settlements and community well-being is a significant concern, especially in vulnerable countries like Cameroon, which has a wide range of ecological zones, including Coastal Lowlands, Equatorial Rainforest, Western Highlands, Sudan-Savannah, and the Sahel. The objectives of this study are (1) evaluate changing climatic conditions in Cameroon’s ecological zones; (2) analyse the vulnerability of urban residential housing to changing climatic conditions; (3) propose adaptation strategies and sustainable architectural designs to mitigate the impact of climate change, (4) assess policy implications and stakeholder engagement for sustainable urban housing development. A literature review was conducted to achieve these objectives on the nexus between climate and human settlements. Meteorological data (rainfall) were also analysed and 200 structured questionnaires were administered to municipal authorities to assess the vulnerability and adaptation of urban residential housing. Findings revealed that the rapidly urbanising coastal cities of Douala, Limbe, and Kribi are experiencing extreme precipitation, flooding, and sea level rise. Similarly, the capital city, Yaounde, is facing severe rainfall, leading to floods and landslides. In the Western Highlands, human settlements in Bafoussam and Bamenda are at risk of landslides and runoff. In the northern Sudano-Sahelian region, extreme heat and desertification pose significant threats to residential housing development. Nature-based Climate Solutions (NbS) such as green corridors are recommended to absorb and filter stormwater to promote climate-resilient communities. Developing climate-resilient residential housing in Cameroonian cities requires tailored community-level interventions for each ecological zone.

INTEGRATING INDIGENOUS KNOWLEDGE SYSTEMS (IKS) IN CLIMATE CHANGE POLICIES IN AFRICA: BARRIERS, STRATEGIES AND FUTURE DIRECTIONS. EMPHASIS ON AGRICULTURE

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Apr 2025

This article examines the crucial role of indigenous knowledge systems (IKS) in climate change adaptation and mitigation from an African perspective. Despite recognition in the Intergovernmental Panel on Climate Change (IPCC)'s Fifth and Sixth Assessment Reports (AR5 and AR6) as vital contributors to climate solutions, the inclusion of indigenous communities in climate research and policy remains limited. We review peer-reviewed literature to evaluate the extent and effectiveness of IKS in addressing climate equity and community resilience across Africa, highlighting disparities in its deployment. The urgency is underscored by projections indicating a temperature rise exceeding 3°C, even with compliance to Intended Nationally Determined Contributions. We discuss how traditional localized knowledge can address climate change, as acknowledged by the IPCC, and the decline of IKS due to modernization. The review aims to assess the significance of IKS in climate strategies, identify barriers to their incorporation into science-based guidelines, and suggest pathways for integrating indigenous insights into Africa's climate policies. By shedding light on these critical themes, we advocate for a collaborative approach that values indigenous voices in tackling the pressing challenges presented by climate change.

Forecasting and monitoring of extreme rainfall over Africa

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Jan 2025

Detection of fast-changing intra-seasonal vegetation dynamics of drylands using solar-induced chlorophyll fluorescence (SIF)

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Apr 2025
BG

Dryland ecosystems are the habitat supporting 2 billion people on Earth, and they strongly impact the global terrestrial carbon sink. Vegetation growth in drylands is mainly controlled by water availability with strong intra-seasonal variability. Timely availability of information at such scales (e.g., from days to weeks) is essential for early warning of potential catastrophic impacts of emerging climate extremes on crops and natural vegetation. However, the large-scale monitoring of intra-seasonal vegetation dynamics has been very challenging for drylands. Satellite solar-induced chlorophyll fluorescence (SIF) has emerged as a promising tool to characterize the spatiotemporal dynamics of photosynthetic carbon uptake and has the potential to detect intra-seasonal vegetation growth dynamics. However, few studies have evaluated its capability of detecting fast-changing intra-seasonal vegetation dynamics and advantages over traditional approaches in drylands based on vegetation indices (VIs). To fill this knowledge gap, this study utilized the vast dryland ecosystems in the Horn of Africa (HoA) as a testbed to characterize their intra-seasonal dynamics inferred from satellite SIF. The HoA is an ideal testbed because its dryland ecosystems have highly dynamic responses to short-term environmental changes. The satellite-data-based analysis was corroborated with a unique in situ SIF dataset collected in Kenya – so far, the only ground SIF time series collected on the continent of Africa. We found that SIF from the TROPOspheric Monitoring Instrument (TROPOMI) with daily revisit frequency identified highly dynamic week-to-week variations in both shrublands and grasslands; such rapidly changing vegetation dynamics corresponded to the up- and downregulation by the fluctuations in environmental variables (e.g., air temperature, vapor pressure deficit, soil moisture). However, neither reconstructed SIF products nor near-infrared reflectance of terrestrial vegetation (NIRv) from the Moderate Resolution Imaging Spectroradiometer (MODIS), which is widely used in the literature, was able to capture such fast-changing intra-seasonal variations. The same findings hold at the site scale, where we found that only TROPOMI SIF revealed two separate within-season growth cycles in response to extreme soil moisture and rainfall amount and duration, consistent with in situ SIF measurements. This study generates novel insights on the monitoring of dryland vegetation dynamics and the evaluation of their climate sensitivities, enabling the development of predictive and scalable understanding of how dryland ecosystems may respond to future climate change and informing the future design of effective vegetation monitoring systems for dryland vegetation.

Implications of Climate Crisis in Southern Africa

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Apr 2025

This chapter discusses climate crisis within the framework of climate capitalism. Contrary to the conventional understanding of climate from an anthropocentric perspective, the discussion here emphasises fairness, equity, and inclusivity in crafting solutions that recognise the role of the history of colonialism and imperialism perpetuated by powerful countries and multinational corporations. Chapter concludes that only comprehensive strategies prioritising sustainability and inclusivity, beyond market-driven approaches will help build a more just and resilient future for Africa.

African climate change science is emerging as a region leader

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Mar 2023

Guy F. Midgley

ICT-Enabled Climate Change Education and Adaptation in Africa

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Apr 2025

Climate change is a global issue that is both inevitable and urgent, and Africa is particularly vulnerable to its impact. This chapter examines how ICT can be used for climate change education and adaptation in Africa. Despite the importance of ICT, there is limited information available in the literature about how it is presently and will be used in Africa’s efforts to adapt to climate change. The chapter highlights that ICT is crucial in addressing the significant challenges posed by climate change in Africa, and can be employed to facilitate the dissemination of knowledge required for climate change adaptation at the community level. This can be accomplished by raising awareness, providing access to critical information, and promoting learning and sharing of experiences.

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Debra Roberts

IPCC AR6 WGI Chapter11: Weather and Climate Extreme Events in a Changing Climate

Chapter

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Aug 2021

This chapter assesses changes in weather and climate extremes on regional and global scales, including observed changes and their attribution, as well as projected changes. The extremes considered include temperature extremes, heavy precipitation and pluvial floods, river floods, droughts, storms (including tropical cyclones), as well as compound events (multivariate and concurrent extremes). The assessment focuses on land regions excluding Antarctica. Changes in marine extremes are addressed in Chapter 9 and Cross-Chapter Box 9.1. Assessments of past changes and their drivers are from 1950 onward, unless indicated otherwise. Projections for changes in extremes are presented for different levels of global warming, supplemented with information for the conversion to emissions scenario-based projections (CrossChapter Box 11.1 and Table 4.2). Since the IPCC Fifth Assessment Report (AR5), there have been important new developments and knowledge advances on changes in weather and climate extremes, in particular regarding human influence on individual extreme events, on changes in droughts, tropical cyclones, and compound events, and on projections at different global warming levels (1.5°C–4°C). These, together with new evidence at regional scales, provide a stronger basis and more regional information for the AR6 assessment on weather and climate extremes

Quantifying international public finance for climate change adaptation in Africa

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Sep 2021
CLIM POLICY

Under the United Nations Framework Convention on Climate Change, international financial assistance is expected to support African and other developing countries as they prepare for and adapt to the impacts of climate change. The impact of this finance depends on how much finance is mobilized and where it is targeted. However, there has been no comprehensive quantitative mapping of adaptation-related finance flows to African countries to date. Here we track development finance principally targeting adaptation from bilateral and multilateral funders to Africa between 2014 and 2018. We find that the amounts of finance are well below the scale of investment needed for adaptation in Africa, which is a region with high vulnerability to climate change and low adaptation capacity. Finance targeting mitigation (US

30.6 billion) was almost double that for adaptation (US

16.5 billion). The relative share of each varies greatly among African countries. More adaptation-related finance was provided as loans (57%) than grants (42%) and half the adaptation finance has targeted just two sectors: agriculture; and water supply and sanitation. Disbursement ratios for adaptation in this period are 46%, much lower than for total development finance in Africa (at 96%). These are all problematic patterns for Africa, highlighting that more adaptation finance and targeted efforts are needed to ensure that financial commitments translate into meaningful change on the ground for African communities. Key policy insights • Between 2014 and 2018, adaptation-related finance committed by bilateral and multilateral funders to African countries remained well below US

5.5 billion per year, or roughly US

5 per person per year; these amounts are well below the estimates of adaptation costs in Africa. • Funders have not strategically targeted support for adaptation activities towards the most vulnerable to climate change African countries. • Lessons from countries that have been more successful in accessing finance point to the value of more sophisticated domestic adaptation policies and plans; of alignment with priorities of the NDC; of meeting funding requirements of specific funders; and of the strategic use of climate funds by national planners. • A low adaptation finance disbursement ratio in this period in Africa (at 46%) relates to barriers impeding the full implementation of adaptation projects: low grant to loan ratio; requirements for co-financing; rigid rules of climate funds; and inadequate programming capacity within many countries.

Governance of Urban Green Infrastructure in Informal Settlements of Windhoek, Namibia

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Aug 2021

Facing increased rural-urban migration, population growth, climate change impacts, and cascading natural, security, and health hazards, many municipalities in sub-Saharan Africa are beginning to consider the benefits of urban green infrastructure for improving the resilience and wellbeing of residents living in informal settlements. However, present governance systems are often ill-equipped to deliver the scale of planning needed. Integration of urban green infrastructure into local government mandates, spatial planning and targeted action plans remains limited, further inhibited by scarce empirical research on the topic in Africa. Taking Windhoek, Namibia, and specifically Moses ǁGaroëb, Samora Machel, and Tobias Hainyeko constituencies as a case study, we fitted key informant interview (n = 23), focus group (n = 20), and participant observation data into existing governance theory to investigate (a) benefits and trade-offs of present urban green infrastructure in Windhoek’s informal settlements; (b) urban green infrastructure governance in terms of institutional frameworks, actors and coalitions, resources, and processes; and (c) the key desirable pathways for future urban green infrastructure governance in informal settlements. To this end, we used five green infrastructure initiatives to dissect governance intricacies and found diverse opportunities for innovative governance mechanisms. The urgent need for climate resilience in Namibia offers a policy and practice window to adopt context-specific approaches for multifunctional urban green infrastructure. However, for these initiatives to succeed, collaborative governance platforms and clearly delineated mandates are necessary, with explicit integration of urban green infrastructure into strategies for in-situ informal settlements upgrading and green job growth.

Global exposure of population and land‐use to meteorological droughts under different warming levels and SSPs: A CORDEX‐based study

Article

Full-text available

Aug 2021
INT J CLIMATOL

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population, forests, croplands and pastures exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), population projections from the NASA‐SEDAC dataset and land‐use projections from the Land‐Use Harmonization 2 project for 1981–2100. The exposure to drought hazard is presented for five Shared Socioeconomic Pathways (SSP1‐SSP5) at four Global Warming Levels (GWLs: 1.5°C to 4°C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the SSP3 at GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (versus 1981–2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation‐Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 at GWL4, approximately 2 × 10⁶ km² of forests and croplands (respectively, 6% and 11%) and 1.5 × 10⁶ km² of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI this extent will rise to 17 × 10⁶ km² of forests (49%), 6 × 10⁶ km² of pastures (78%) and 12 × 10⁶ km² of croplands (67%), being mid‐latitudes the most affected. The projected likely increase of drought frequency and severity significantly increases population and land‐use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.

Feasibility assessment of climate change adaptation options across Africa: An evidence-based review

Article

Full-text available

Jul 2021
ENVIRON RES LETT

Considering the feasibility and effectiveness of adaptation options is essential for guiding responses to climate change that reduce risk. Here, we assessed the feasibility of adaptation options for the African context. Using the Global Adaptation Mapping Initiative, a stocktake of adaptation-related responses to climate change from the peer-reviewed literature in 2013–2020, we found 827 records of adaptation actions in Africa. We categorised and evaluated 24 adaptation options and for each option, six dimensions of feasibility were considered: economic, environmental, social, institutional, technological, and evidence of effectiveness. Over half (51%) of all adaptation actions were reported in the food sector where sustainable water management was the most reported option. The fewest actions were reported for cities (5%). The majority of actions (53%) were recorded in just 6 countries: Ghana, Ethiopia, Kenya, Tanzania, Nigeria and South Africa. Encouragingly, effectiveness was assessed as medium or high for 95% of adaptation options. However, no options had high feasibility on any other dimension. Technological and institutional factors present major barriers to implementation. Crop management, sustainable water management, sustainable agricultural practices, agroforestry, livelihood diversification, ecosystem governance and planning, health governance and planning, infrastructure and built environment, all had moderate feasibility across three or more dimensions. Human migration has low feasibility but high potential for risk reduction. Major knowledge gaps exist for environmental feasibility, for assessing adaptation limits at increasing levels of climate hazard, for economic trade-offs and synergies, and for Central and Northern Africa. Our results highlight sectors where enablers for adaptation can be increased. Future assessments can apply the method established here to extend findings to other national and local levels.

Large potential for crop production adaptation depends on available future varieties

Article

Full-text available

May 2021

Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. In this study, we investigate the effects of variety adaptation on global caloric production under four different future climate change scenarios for maize, rice, soybean, and wheat. Thereby, we empirically identify areas that could require new varieties and areas where variety adaptation could be achieved by shifting existing varieties into new regions. The study uses an ensemble of seven global gridded crop models and five CMIP6 climate models. We found that 39% (SSP5‐8.5) of global cropland could require new crop varieties to avoid yield loss from climate change by the end of the century. At low levels of warming (SSP1‐2.6), 85% of currently cultivated land can draw from existing varieties to shift within an agro‐ecological zone for adaptation. The assumptions on available varieties for adaptation have major impacts on the effectiveness of variety adaptation, which could more than half in SSP5‐8.5. The results highlight that region‐specific breeding efforts are required to allow for a successful adaptation to climate change.

The evolution of empirical adaptation research in the global South from 2010 to 2020

Article

Full-text available

Feb 2021

This paper applies a scoping review approach to inductively assess the evolution of empirical adaptation research in the global South over the period 2010 to 2020 using, as indicators of the literature, three leading adaptation journals covering different scales of analysis: Global Environmental Change, Regional Environmental Change and Climate and Development. The review confirms that previous calls for an increase in empirical adaptation research have been heeded. Research covers both policy and practice, and also different scales, with a particular focus on agricultural and rural settings. There is significant and growing interest in the determinants of adaptation and adaptive capacity (including the role of barriers and enablers), and a small but growing interest in the role of gender. The overall increase in total publications does not show even geographical or sectoral coverage. Large swathes of sub-Saharan Africa and the Middle East/North Africa remain severely under-researched; and the overwhelming majority of papers focus on rural and agricultural issues rather than cities. This analysis offers tangible evidence to highlight where geographical and thematic gaps exist in our research on adaptation in the global South.

Supporting transformative climate adaptation: community-level capacity building and knowledge co-creation in South Africa

Article

Full-text available

Jan 2021

Calls for transformative adaptation to climate change require attention to the type of capacity building that can support it. Community-level capacity building can help to ensure ownership and legitimacy of longer-term interventions. Given that marginalized communities are highly vulnerable to climate risk, it is important to build their capacity to adapt locally and to integrate their perspectives into higher-level adaptation measures. Current adaptation policy does not pay sufficient attention to this. Using a Cape Town-based project on water governance in low-income urban settlements, this paper explores how a transdisciplinary research project supported capacity building. Our findings suggest that knowledge co-creation at the community level is central to the capacity building that is needed in order to inform transformative adaptation. The collaborative methodology used is also important; we illustrate how a transdisciplinary approach can contribute to transformative adaptation where knowledge is co-produced to empower community-level actors and organizations to assert their perspectives with greater confidence and legitimacy. We argue that if capacity building processes shift from the top-down transferal of existing knowledge to the co-creation of contextual understandings, they have the potential to deliver more transformative adaptation. By considering diverse sources of knowledge and knowledge systems, capacity building can start to confront inequalities and shift dominant power dynamics. Adaptation policy could provide more guidance and support for community-level transdisciplinary processes that can enable this type of transformative adaptation. Key policy insights • To address equity and justice issues as well as climate risk, adaptation policy needs to better support transformative adaptation. • Community-level capacity building, called for by developing countries, will benefit from more attention to bottom-up approaches as a complement to top-down ones. • Community-led research that draws on a diversity of knowledge systems can effectively inform the development of transformative adaptation interventions. • Transdisciplinary research methods present a promising pedagogical approach to building transformative adaptation capacity. • Adaptation policy for capacity building would benefit from a broader understanding of governance that includes local participation and values bottom-up contributions. • A priority for capacity building is getting previously excluded actors a spot at the negotiating table as well as skills to substantiate their arguments.

Climate change impacts on water security in global drylands

Article

Jun 2021

Water scarcity affects 1–2 billion people globally, most of whom live in drylands. Under projected climate change, millions more people will be living under conditions of severe water stress in the coming decades. This review examines observed and projected climate change impacts on water security across the world's drylands to the year 2100. We find that efficient water management, technology, and infrastructure, and better demand and supply management, can offer more equitable access to water resources. People are already adapting but need to be supported with coherent system-oriented policies and institutions that situate water security at their core, in line with the components of integrated water resources management. Dryland water governance urgently needs to better account for synergies and trade-offs between water security and other dimensions of sustainable development, to support an equitable approach in which no one gets left behind.

Lentic-Lotic Water System Response to Anthropogenic and Climatic Factors in Kenya and Their Sustainable Management

Chapter

Feb 2021

Kenya has many lakes which have evolved through geological time; most of the modern ones were created during the Lower to Middle Pleistocene. While all of them react to climate changes over geological timescales, a number of them are highly sensitive to even seasonal climate variations, fluctuating quite dramatically in surface area and level, and are, therefore, commonly referred to as “amplifier” lakes. There is a range of biological diversity in the lakes, and the rivers and wetlands within the lake basins, in diverse ecosystems that provide various goods and services to the local communities around them. However, there is mounting evidence that the impacts of human activity (e.g., deforestation, agriculture, water abstractions) and hydrological variability related to global warming effects on climate (rainfall, temperature) are already affecting these natural aquatic resources, leading to changes in fauna and flora distributions and in their overall resource values. The consequences are mostly adverse, but there are also beneficial ones. Climate, environment, and society interact in complex ways in lake basin ecosystems. For example, there has been no clear understanding of the cause(s) of the striking rise in lake levels in the central rift lakes of Kenya since 2010 which have resulted in submerged buildings and road infrastructure, and displacement and/or disruption of the socio-ecological system. Implementation of viable and sustainable management and use options is critical, but it is currently precluded by myriad factors, including lack of timely and adequate data for decision-making, siloed sectoral approaches, jurisdictional challenges at sub-national and regional scales, overlapping institutional mandates, and diverse and uncoordinated stakeholder groupings. A pathway for development of lake basin-specific management plans in Kenya is outlined, based on the Integrated Lake Basin Management (ILBM) approach, that can help to ensure the health and sustainability of the lakes and their basins and continued provision of goods and services to the people and wildlife that are dependent upon them.