BookPDF Available

Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures

Authors:

Abstract

Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures. Global Institute for Agri-Tech Economics, Food, Land & Agribusiness Management Department, Harper Adams University. Newport, United Kingdom, 19-20 September 2022
Proceedings of the 5th Symposium on
Agri-Tech Economics for
Sustainable Futures
19 20th September 2022, Harper Adams University,
Newport, United Kingdom.
Global Institute for Agri-Tech Economics,
Food, Land and Agribusiness Management Department,
Harper Adams University
https://www.harper-adams.ac.uk/research/giate/
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures ii
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable
Futures
COPYRIGHT NOTICE: Copyright 2022 by submitting Authors listed in papers. All rights reserved.
Readers may make verbatim copies of this document for non-commercial purposes by any
means, provided that this copyright notice appears on all such copies.
Global Institute for Agri-Tech Economics (GIATE)
Food, Land & Agribusiness Management Department
Harper Adams University
Newport, Shropshire, United Kingdom TF10 8NB
Website: https://www.harper-adams.ac.uk/research/giate/
Symposium Website: https://www.agritechecon.co.uk/
ISBN: 978-1-7398183-3-3
Edited by D. Paparas and K. Behrendt
Published by HAU Publications (Ebooks)
Cover Image: Hands Free Hectare, Harper Adams University
Citation: [Authors, 2022. Title.] In: D. Paparas and K. Behrendt (eds.) Proceedings of the 5th
Symposium on Agri-Tech Economics for Sustainable Futures. Global Institute for Agri-Tech
Economics, Food, Land & Agribusiness Management Department, Harper Adams University.
HAU Publications, Newport, United Kingdom, 19-20 September 2022, [pp].
All Full Papers published in this volume have been subject to single-blind peer-review
administered by the proceeding’s editors. Reviews have been conducted by expert referees,
who have been requested to provide unbiased and constructive comments aimed, whenever
possible, at improving the work. The proceeding’s editors have taken all reasonable steps to
ensure the quality of the materials they publish and their decision to accept or reject a paper
for publication has been based only on the merits of the work and its relevance to the
symposium.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures iii
Symposium Organisation
Symposium Organising Committee
Dr Dimitrios Paparas (Chair)
Principal Lecturer in Economics
Harper Adams University,
Food, Land and Agribusiness Management
Department (FLAM)
Newport, Shropshire United Kingdom
TF10 8NB
Email: dpaparas@harper-adams.ac.uk
Professor Karl Behrendt (Chair)
Elizabeth Creak Chair in Agri-Tech
Economic Modelling
Director GIATE
Harper Adams University, FLAM
Newport, Shropshire, United Kingdom
TF10 8NB
Email: kbehrendt@harper-adams.ac.uk
Nigel Hill
Associate Head of Department,
Farm Business Management and Senior
Lecturer
Harper Adams University, FLAM
Newport, Shropshire, United Kingdom
TF10 8NB
Professor James Lowenberg-DeBoer
Elizabeth Creak Chair in Agri-Tech
Economics
Senior Advisor GIATE
Harper Adams University, FLAM
Newport, Shropshire, United Kingdom
TF10 8NB
Christian Oberst, German Economic
Institute, Germany
Josep-Maria Arauzo-Carod, Universitat
Rovira i Virgili, Spain
Pamela Theofanous, Harper Adams
University, UK
Ourania Tremma, Harper Adams
University, UK
Scientific Committee
Karl Behrendt, Harper Adams University,
UK
James Lowenberg-DeBoer, Harper Adams
University, UK
Dimitrios Paparas, Harper Adams
University, UK
Nadja El-Benni, Agroscope, Switzerland
Andreas Meyer-Aurich, ATB, Germany
Ioannis Kostakis, Harokopeio University,
Greece
Daniel May, Harper Adams University, UK
Nigel Hill, Harper Adams University, UK
Ourania Tremma, Harper Adams
University, UK
Eleni Sardianou, Harokopeio University,
Greece
Paul Thomassin, McGill University, Canada
Mostafa E. AboElsoud, The British
University in Egypt, Egypt
Ioannis Panagiotopoulos, University of the
Aegean, Greece
Bilal Kargi, Ankara Yildirim Beyazit
University, Turkey.
Pietro Calandra, National Council of
Research, Italy
Rasha Aly, London South Bank University,
UK
Bikramaditya Ghosh, Symbiosis Institute of
Business Management, India
GIATE Advisory Group
Paul Thomassin, McGill University, Canada
Nadja El-Benni, Agroscope, Switzerland
Yelto Zimmer, agri benchmark Thuenin
Institute, Germany
Andreas Meyer-Aurich, ATB, Germany
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures iv
Symposium Supporters
GIATE Research Collaborators
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures v
Contents
Symposium Organisation .......................................................................................................... iii
Symposium Supporters ............................................................................................................. iv
GIATE Research Collaborators ................................................................................................... iv
Symposium Program ................................................................................................................ viii
Keynote Presentation: The circular economy is a priority but no panacea! ........................... 13
Anders Wijkman
Keynote Presentation: Economics of agri-tech policy, regulation and standards ................... 14
Professor James Lowenberg-DeBoer
Keynote Presentation: Exploring agriculture-based mitigation in the pursuit of circular
economy. Food tree crops ecosystems as a net sink of CO2 .................................................... 15
Professor Konstantinos Bithas
The Impact of Female Tertiary Education and Climate Change on Economic Growth in
Developing Countries ............................................................................................................... 16
Aya Moataz and Christian Richter
Exploring the factors affecting consumers’ willingness to purchase alternative fertilisers in the
UK ............................................................................................................................................. 29
Cameron HewardA,B, Ourania TremmaA, Eric SiqueirosA and Daniel MayA
Factors affecting farm business resilience ............................................................................... 34
Iona HuangA, Karl BehrendtA, Nigel HillA, Steve DunkleyB and Sarah HurfordB
Estimating Biomass Carbon stocks in Agriculture Land for the Mediterranean using remote
sensing data .............................................................................................................................. 35
Petridou Kariofillia*, Angelos Mimis and Kostas Bithas
Sustainable Urban Resilience: Cities in the face of modern challenges. Case study: The city of
Elliniko-Argyroupoli, Greece .................................................................................................... 45
Roido Mitoula and Natalia Gkagkosi
Smart Contract in Food Supply-Chain ...................................................................................... 64
Bikramaditya Ghosh
Keynote Presentation: Economics and Adoption of Precision Agriculture .............................. 67
David Bullock
Do the Extensive Field Experiments in Variable Rate Nitrogen Application Help Farmers make
Higher Profits? .......................................................................................................................... 68
Jaeseok Hwang
Using On-farm Precision Experimentation Data to Analyse Maximum Return to Nitrogen
(MRTN) Recommendations ...................................................................................................... 70
Aolin GongA, Taro MienoB and David S. BullockA
Economics of strip intercropping with autonomous machines ............................................... 92
A. K. M. Abdullah Al-AminA,B, James Lowenberg DeBoerA, Bruce J EricksonC, Kit FranklinA and Karl BehrendtA
Evaluating the use of electrical conductivity for defining variable-rate management of nitrogen
and seed for corn production .................................................................................................. 94
Brittani EdgeA*, David BullockA and Taro MienoB
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures vi
A Methodology to Investigate Challenges for Digital Twin Technology in Smart Agriculture
................................................................................................................................................ 107
Gülçin BüyüközkanA*, Deniz UztürkB
The Economic Performances of Different Trial Designs in On-Farm Precision Experimentation:
A Monte Carlo Evaluation ...................................................................................................... 118
Xiaofei LiA*, Taro MienoB and David S. BullockC
Keynote Presentation: Readiness for robotics: adoption, ethics, regulation ........................ 142
David Rose
Public perception of smart farming technologies .................................................................. 143
Jeanine AmmannA,B*, Gabriele MackA,B and Nadja El BenniB
The role of Artificial Intelligence (AI) in agriculture and its impact on economy .................. 147
Agnieszka Wójcik-Czerniawska
Smart Agriculture Technology Evaluation: A Linguistic-based MCDM Methodology ........... 161
Deniz UztürkA and Gülçin BüyüközkanB*
A Technology Mapping Approach to the Value Proposition for Agri-food Firms and Supply
Chains of Digital Transformation ........................................................................................... 175
Derek Baker
Keynote Presentation: Food chain strategies to achieve zero GHG by 2050 ........................ 179
Inmaculada Martínez-Zarzoso
Investigating EKC in oil-exporting countries .......................................................................... 180
Rashid SbiaA, Ioannis KostakisB*
Environmental sustainability, energy consumption and economic growth: empirical evidence
from OECD countries .............................................................................................................. 181
Ioannis KostakisA*, Dimitrios PaparasB, Konstantinos TsagarakisA
Sustainable food value chains in the European Union: Linking policies and multi-stakeholders’
initiatives ................................................................................................................................ 183
I. R. Moreira-DantasA*, I. Martínez-ZarzosoA,B, J.A. Torres-MunguíaA, S. JafarzadehC, M. Pujol MartinC, M.
ThakurC
The circular economy and sustainable development in European countries ....................... 187
David KnäbleA,B, Esther de Quevedo PuenteA, Clara Pérez CornejoA, Thomas BaumgärtlerB
Dimensions in circular economy: a content analysis of current definitions .......................... 189
Vasilis NikouA, Eleni SardianouA, Konstantinos EvangelinosB, Ioannis NikolaouC
Price Linkages in major EU olive oil Markets ......................................................................... 190
Pamela TheofanousA*, Ourania TremmaA, Karl BehrendtA, Louise ManningB and Dimitrios PaparasA
A multicriteria framework for measuring national energy performance .............................. 191
Stratos Kartsonakis*, Evangelos Grigoroudis and Constantine Zopounidis
Will Fiscal Expenditure for Agriculture Aggravates Water Pressure of Regional Grain
Production? An Empirical Evidence From China .................................................................... 193
LI Ziqiang, LI Xiaoyun* and LIU Yuxin
Price transmission as an aspect of business sustainability: the case of the Lithuanian pork
market .................................................................................................................................... 195
Nelė JurkėnaitėA and Dimitrios PaparasA*
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures vii
Farmers risk attitude and the adoption of sustainable land management practices in Southeast
Nigeria .................................................................................................................................... 198
Cynthia Olumba*, Guy Garrod and Areal Franscisco
Carbon offset due to using plastic pallets .............................................................................. 202
Krzysztof Witos, Agnieszka Wójcik-Czerniawska and Zbigniew Grzymała
The state and prospects of compound aquafeed production in Ukraine .............................. 203
Liudmyla Fihurska and Bogdan Iegorov
Adoption of Coping Strategies to Rabbit Haemorrhagic Disease Outbreak by Rabbit Farmers in
Kwara State, Nigeria ............................................................................................................... 207
Muhammad Adeiza Bello*, Mathew Olaniyi Adewumi, Mathew Durojaiye Ayeni, Grace Oluwabukunmi
Akinsola, Ismail Abiodun Ahmed and Muhammed Jamiu Dauda
Relationship between economic development & environmental sustainability in selected
European countries ................................................................................................................ 219
Stijn Joosten and Dimitrios Paparas
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures viii
Symposium Program
All times are for the United Kingdom (BST / UTC+1)
Opening Session
08:45 to 10:45 Monday 19th September 2022
Session Chair: Dimitrios Paparas & Karl Behrendt (Harper Adams University)
Prof. Ken Sloan (VC of HAU)
Welcome and Harper Adams University directions
Rebecca Payne (Head FLAM, HAU)
Thank you and FLAM strategy
Anders Wijkman
Keynote: The circular economy is a priority but no panacea!
Prof. James Lowenberg- DeBoer
Keynote: Economics of agri-tech policy, regulation and
standards
Session 2: Sustainability
School of Sustainable Food and Farming (HAU)
12:30 to 15:30 Monday 19th September 2022
Session Chair: Rose Judeh-Elwell (SSFF School Business Manager)
Prof Michael Lee (Deputy VC
HAU)
SSFF and HAU Developments
Prof Kostas Bithas
Keynote: Exploring agriculture-based mitigation in the pursuit of
circular economy. Food tree crops ecosystems as a net sink of
CO2
Aya Moataz, Christian Richter
The Impact of Female Tertiary Education and Climate Change on
Economic Growth in Developing Countries.
Eric Siqueiros
Exploring the factors affecting consumers’ willingness to
purchase alternative fertilisers in the UK
Iona Huang
Factors affecting farm business resilience
Petridou Kariofillia
Estimating Biomass Carbon stocks in Agriculture Land for the
Mediterranean using remote sensing data
Natalia Gkagkosi, Roido Mitoula
Sustainable Urban Resilience: Cities in the face of modern
challenges. Case study: The city of Elliniko-Argyroupoli, Greece
Bikramaditya Ghosh
Smart Contract in Food Supply-Chain
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures ix
Session 3: Economics and Adoption of Precision Agriculture
International Society of Precision Agriculture Economics Community
16:00 to 18:30 Monday 19th September 2022
Session Chair: Karl Behrendt (ISPA Economics Community Leader)
Keynote: Economics and Adoption of Precision Agriculture
Do the Extensive Field Experiments in Variable Rate Nitrogen
Application Help Farmers Make Higher Profits?
Using On-farm Precision Experimentation Data to Analyse
Maximum Return to Nitrogen (MRTN) Recommendations
Economics of strip intercropping with autonomous machines
Evaluating the use of electrical conductivity for defining variable-
rate management of nitrogen and seed for corn production
A Methodology to Investigate Challenges for Digital Twin
Technology in Smart Agriculture
The Economic Performances of Different Trial Designs in On-Farm
Precision Experimentation: A Monte Carlo Evaluation
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures x
Session 4: Robotics and AI: replacing humans in agriculture?
Centre for Effective Innovation in Agriculture
09:00 to 11:45 Tuesday 20th September 2022
Session Chair: Kate Pressland (Centre for Effective Innovation in Agriculture)
Keynote: Readiness for robotics: adoption, ethics, regulation
Public perception of smart farming technologies
The role of Artificial Intelligence (AI) in agriculture and its impact
on economy
Smart Agriculture Technology Evaluation: A Linguistic-based
MCDM Methodology
A Technology Mapping Approach to the Value Proposition for
Agri- food Firms and Supply Chains of Digital Transformation
Agro-apps: case studies and learning from farmers
Robotics and AI on the farm. Followed by discussion.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures xi
Session 5: Sustainable Futures
International Network for Economic Research
12:00 to 14:20 Tuesday 20th September 2022
Session Chair: Christian Oberst (INFER Vice Chair)
Keynote: Food chain strategies to achieve zero GHG by 2050
Investigating EKC in oil-exporting countries
The impact of fossil and non-fossil fuel energy consumption on
country sustainability: Empirical evidence from the OECD
Sustainable food value chains in the European Union: Linking
policies and multi-stakeholders’ initiatives
The circular economy and sustainable development in European
countries
Dimensions in circular economy: a content analysis of current
definitions
Session 6: Agricultural Economics
14:50 to 16:30 Tuesday 20th September 2022
Session Chair: Daniel May/Ourania Tremma (HAU)
Price Linkages in major EU olive oil Markets
A multicriteria framework for measuring national energy
performance
Will Fiscal Expenditure for Agriculture Aggravates Water Pressure
of Regional Grain Production? An Empirical Evidence From China
Price transmission as an aspect of business sustainability: the case
of the Lithuanian pork market
Farmers’ risk attitude and the adoption sustainable land
management practices in Southeast Nigeria
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures xii
Session 7: Food and Alternative Systems
16:50 to 18:30 Tuesday 20th September 2022
Session Chair: Nigel Hill/Iona Huang (HAU)
Carbon offset due to using plastic pallets
The state and prospects of compound aquafeed production in
Ukraine
Adoption of Coping Strategies to Rabbit Haemorrhagic Disease
Outbreak by Rabbit Farmers in Kwara State, Nigeria
Examining the relationship between economic development and
environmental sustainability in selected European countries
Closing Remarks
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 13
Keynote Presentation: The circular economy is a priority but
no panacea!
Anders Wijkman
Honorary President of the Club of Rome, Chairman Climate-KIC, Sweden
Presenter Profile
Anders Wijkman is an opinionmaker and author. Anders is a former member of the European
Parliament, honorary president of the Club of Rome, member of the IRP (International
Resource Panel) - a UN expert- body to build and share the knowledge needed to improve
the use of our resources worldwide”. He is, as well, Chair of Circular Sweden, a platform for
producers, retailers and recycling companies to advance the Circular Economy. He is a
member of the Royal Swedish Academy of Sciences, the World Academy of Art and Science
and the World Future Council.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 14
Keynote Presentation: Economics of agri-tech policy,
regulation and standards
Professor James Lowenberg-DeBoer
Land, Food & Agribusiness Management Department, Harper Adams University, Shropshire,
Newport, TF10 8NB, UK.
Presenter Profile
Prof. James Lowenberg-DeBoer holds the Elizabeth Creak Chair in Agri-Tech Applied
Economics at Harper Adams University (HAU), Newport, Shropshire, UK. He is responsible for
economics in the Hands Free Farm (HFF) team at HAU. He is also co-editor of the journal
Precision Agriculture and past president of the International Society of Precision Agriculture
(ISPA). His research focuses on the economics of agricultural technology, especially precision
agriculture and crop robotics. Lowenberg-DeBoer’s research and outreach is founded in
hands-on experience in agriculture, including production of maize and soybeans in NW Iowa
in the USA.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 15
Keynote Presentation: Exploring agriculture-based
mitigation in the pursuit of circular economy. Food tree
crops ecosystems as a net sink of CO2
Professor Konstantinos Bithas
Panteion University, Greece
Presenter Profile
Kostas Bithas is a Professor in Environmental and Natural Resources Economics at the
Panteion University, Department of Economic and Regional Development, Athens, Greece and
Member of the Board of Directors of the Institute of Urban Environment and Human
Resources Research team on Environmental Economics and Sustainable Development
(www.eesd.gr). Academic fields: Sustainable Development, Ecological Economics, Natural
Resources Economics, Environmental - Economic modeling, Environmental impact
assessment, Transport Economics, Decision making, Policy evaluation.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 16
The Impact of Female Tertiary Education and Climate
Change on Economic Growth in Developing Countries
Aya Moataz and Christian Richter
Coventry University in Egypt at The Knowledge Hub Universities, Cairo, Egypt
Abstract
This study examines how female tertiary education and climate change affect economic
growth in a set of 33 chosen developing countries from around the world. Previous literature
examines the relationship between gender inequality and economic growth and climate
change and economic growth both theoretically and empirically, in this study empirical
analysis of panel data set will be made using a cross section fixed effects model.
Annual growth rate of female tertiary graduates with a ten-year lag, gross fixed capital
formation, and gross domestic product growth rate with a one-year lag have been found to
have a positive and significant effect on the economic growth rate for developing countries. A
significant and positive relationship has been found between the annual growth rate of mean
temperature and annual growth rate of gross domestic product where the annual growth rate
of gross domestic product is the independent variable.
Enrolment rates or years of schooling of primary and secondary levels have been used in
previous literature as proxies for female education; in this study the annual growth rate of
female tertiary graduates is used to highlight the importance of tertiary level education and
graduate growth rate is used to provide better proxy for the completion of the whole period
of study and not only enrolment. Additionally, climate change is usually included in economic
models as a dependent variable, in this study an attempt to explore climate change as an
independent variable is made to provide more insights into the nature of the relationship
between climate change and economic growth.
Keywords
Developing countries; economic growth; female tertiary education; gender inequality; climate
change; panel data.
Presenter Profiles
Aya Moataz graduated from the German University in Cairo with double majors in Finance and
Economics. She then started her academic career as a teaching assistant and then an Assistant
Lecturer of Economics at the German University in Cairo. She received her master’s degree in
Economic Development with highest honors from the GUC and managed to study two more
majors, namely, Strategic Management and Marketing. Currently, Aya is an Assistant Lecturer
of Finance and Economics at the Business School at Coventry University branch in Egypt at The
Knowledge Hub Universities.
* Corresponding Author: Aya Moataz, Coventry University in Egypt at The Knowledge Hub
Universities, Cairo, Egypt, 11865, email: ayamoataz@hotmail.com
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 17
Introduction
This study aims to examine the impact of female tertiary education and climate change on
economic growth in a set of 33 developing countries from the years 2001-2019. In previous
literature the focus has been mainly on female primary and secondary schooling effects,
limited studies have examined the effect of female tertiary education on economic growth.
This study focuses on the tertiary educational level in attempt to further explore a less visited
aspect of female education and its effect on economic growth. Also, previous literature mainly
focuses on climate change as a dependent variable and not an independent one, which
encouraged the inclusion of this specific variable in the study to test for a different direction
for the relationship between climate change and economic growth.
This paper is structured as follows: Firstly, previous literature on gender inequality, education,
climate change and economic growth along with the theoretical approach on which the study
is based is provided. Secondly, the methodological approach used is discussed. Thirdly, results
of the analysis are explained. Followed by a discussion section where results are compared
with those of previous scholars. Finally, a conclusion with the main finding is provided along
with limitations, policy, and future recommendations of the study.
Gender Inequality in Developing Countries
Although women and girls have made significant efforts towards achieving gender equality
since 1990, they are yet to achieve their goal. Gender inequality is the discrimination against
women which leads to hindering female’s development; it includes yet is not exclusive to
discrimination in health, education, political affairs, job opportunities, etc. A main source of
this gender inequality is the hindrances that women and girls face in societies (UNDP HDR,
2015).
The commonly used method for determining the relationship between gender inequality and
economic growth has been through examining effect of gender gaps on economic growth
through the regression of growth variables, some of which are proxies for gender inequality
on a country’s growth rate represented by per capita income (Cuberes and Teignier,2014). A
positive relation between women’s status and developing socially and economically has been
emphasized by social workers over time. The educational gender gap was highlighted by
comparing between the richest and poorest quartiles in 1990, where in the richest quartile
51% of adult women had obtained secondary level education, while the percentage was an
88% for men. On the other hand, the poorest quartile only 5% of adult women had any
secondary education which is half of the level for men (Dollar and Gatti,1999). Disparities in
both productivity and salaries between women and men arise due to the isolation of women
in a limited number of fields. Examples of this segregation include Nigeria and India, where in
Nigeria in the year 2007 the ratio of women to men’s earnings was 60c:1 dollar and in India it
was 64c:1 dollar (World Development Report,2012).
On the other hand, previous literature indicates there can be a positive effect of the gender
gap given that the pay gap remains constant, and the educational gender gap is reduced, this
provides qualified female labour that accept low wages. Although there have been arguments
against this finding since on the long-term wages cannot remain low and eventually will be
subject to pressure that will elevate female wages (Seguino,2000 a, b).
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 18
Theoretical background
One of the most prominent growth models in literature is the Solow Neoclassical Growth
Model (1956). The model indicates that given the fact that two economies share equal rates
of savings, depreciation, growth of labour force and growth in productivity will lead to the
conditional convergence to same income level (Solow, 1956).
Y = Kα. (AL)1-α (1)
In the model equation (1), gross domestic product is represented by Y, Capital Stock (both
human and physical capital) represented by K, labour represented by L and A as an indicator
of labour productivity given that its growth rate is external (at approximately 2% for developed
countries but variant for developing countries depending on whether they are in a period of
stagnation or improvement). The assumptions of the Solow Growth Model are:
1. Compensation for factors of production whether capital or labour depends on
marginal physical productivities.
2. Flexibility of both prices and wages in economy.
3. Full employment of both labour and capital available.
4. Possibility of substituting labour for capital and vice versa.
5. Neutrality of Technological progress
6. A constant saving ratio.
Assumptions 1-3 imply a perfectly competitive market. Model has been found to be more
relevant in developed economies rather than developing ones (Todaro, 2009).
According to Figure 1 for Unemployment percentage for the developing countries that have
been used in this research, none of the countries fulfil the assumption of full employment
level in the economy proposed by Solow (1956), therefore violation of one or more of the
assumptions of the model affects the eligibility of the model thus requires its modification.
The proposed modifications upon which our model is built is to use the annual rate of growth
of female tertiary graduates instead of Labour and using annual growth rate of gross fixed
capital formation as a representative of physical capital in the model. Additionally, climate
change is represented in the model through annual growth rate of mean temperature, as in
more recent decades the impact of climate change has become more prominent than earlier
years (1956) when the Solow model was first developed.
Figure 1: Unemployment, total (% of total labour force) (2001 2019). Source: World Bank
data (2021) (https://bit.ly/3rC2szH)
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 19
Education, Economic Growth and Sustainable Development Studies
The achievement of sustainable development and a wholesome, productive life for all
depends on the provision of quality education and lasting learning opportunities
(Guterres,2017). “Whether we view sustainable development as our greatest challenge
(Annan, in UNESCO 2005) or a subversive litany (Lomborg 2001), every phase of our education
system is being urged to declare its support for education for sustainable development (ESD)”
(Vare & Scott,2007).
Differences in educational standards and public expenditure on education shape the two most
common reasons behind the existing per capita income gap between developed and less
developed countries. Improvement in developed countries has not been exclusive to literacy
rates in general, but more specifically the reduction of the disparity between the female to
male rates (Akram et al.,2011). Despite the advancements made in gender equality,
empowerment of women and enrolment in different educational levels, the higher
educational levels suffer from the widest gender disparities in several regions and countries
(Guterres,2017).
The importance of examining the relationship between education and economic growth can
be attributed to two main reasons. Firstly, from a generic perspective to either be a beneficiary
of or contributor to the progression of science, education is a must. Secondly, and more
precisely, a vast pool of econometric research has made a link between one’s attainable
income level and the educational level reached. If there are wage differences that arise in
many cases due to differentials in education, then the same could apply for countries as well.
If production per labour is dependent on the individual’s education, and expenditure on
education does provide a kind of return, in the same manner that expenditure on fixed capital
does. Then it is reasonable to view expenditure on human capital as an alternative to that of
fixed (Oztunc et al.,2015).
Empirical analysis on gender inequality in education and economic growth mostly covers
period from 1960-2000. The literature in this period analyses the effect of female education
on economic growth from two perspectives; the first perceives effect of each female and male
education independently while the second uses a ratio for female to male education in the
analytical process (Licumba et al.,2015).
Firstly, (Barro and Lee,1994) paper was one of the first in the perception of female and male
education independently and their effect on economic growth. The (1994) paper by the title
of Sources of Economic Growth used a sample of 115 countries and years of schooling as a
proxy for female education. It indicated that both secondary school attainment and life
expectancy are significant when it comes to growth regressions, emphasizing that when it
comes to comparing both, life expectancy has the more significant effect. They also refer to
the long run effect on growth which arises from the impact that schooling has on decisions
regarding both quantity and quality of children.
Four of the countries in the sample of Barro and Lee’s (1994) study namely (Hong Kong,
Singapore, Taiwan and Korea) are characterized by advanced growth levels and low levels of
female education which lead to attributing the study results reached to the presence of these
four countries and the indication that if the female variable were to be removed the statistical
significance of the male educational variable would be in question (Stokey,1994). In a different
study, a division according to degree of industrialization in the sample of developing countries
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 20
was made, resulting in the significance of female secondary education in only the
industrialized portion of the sample (Dollar and Gatti,1999).
A classification according to a country’s level of human capital was applied in another study
to the sample of developing countries and accordingly 11 developing countries were split
into economies of high and low human capital. Relevance of female primary education was
present only in developing countries characterized by low human capital (Kalaitzidakis et
al.,2001).
Brummet (2008) used Barro and Lee’s (1994) data set, yet only 72 out of 138 countries were
used due to the lack of available data the period studies extended from 1960-1985. As
previously mentioned, Barro and Lee’s (1994) data set suffered from multicollinearity issues,
multicollinearity was accounted for by Brummet (2008) by introducing the natural log of the
ratio between men’s and women’s education, this adjustment decreased the multicollinearity
problem greatly yet did not manage to eliminate it completely. Results for the study
highlighted the inverse relation between underinvestment in women’s education and
economic growth. Also highlighted when comparing discrepancies in primary education and
secondary education, primary education had the larger impact, and those results were more
prominent in developing nations. In their study (Baliamoune - Lutz and McGillivray, 2009) used
panel data for 31sub- Saharan African and 10 Arab countries throughout a period from 1974
to 2001 to test for the relation between the ratio of 1524-year-old literate females to males
and growth for countries in sample. The finding indicates the negative relationship between
gender inequalities in literacy and growth.
In a study conducted on a sample of countries from the MENA region covering the period from
2000-2014, it was found that despite the significant and fast increase in educational
attainment female labour force participation did not match that increase. It was also
highlighted that literature commonly attributed this to supply side effects, while the study
argued that changes in the nature of employment opportunities for women such as decrease
in public sector employment might have led to this decreased participation (Ragui et al., 2018).
In another paper that surveyed and analysed the trends of female labour force participation
in developing countries, it was found that increased female education, economic growth and
decreased fertility do not necessarily reflect positively on the female participation rate, but
specific conditions must be provisioned for this to happen. Such conditions are associated with
phase of educational growth, household situation, the extent to which educated women are
limited to specific jobs, and expansion in employment opportunities preferred by educated
women (Klasen,2019).
One of many variables that affect GDP is climate change. The link between female education,
GDP growth and climate change can be highlighted in Blankespoor’s et al. (2010) study where
developing countries were studied throughout the period 1960 2003, the study concluded
that countries which had higher percentages of educated females were more capable of
enduring the climate change related disasters in comparison to other countries that were less
fortunate even though they enjoyed similar income and climate.
Impact of Climate change on Economic Growth
The degree of economic activity determines the extent of humans’ generation of greenhouse
gases (GHG). Therefore, models of economic growth have been extensively used in literature
on climate change. Nevertheless, the likelihood of climate change impacting economic growth
is also present. There are varying and intricate methods to which those impacts affect
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 21
economies through trends in production and consumption, available resources, and
productivity (Eboli et al.,2010). Intra-generational equity is another characteristic of climate
change, where more wealthy economies have more moderate climates in comparison to
much poorer ones such as sub-Saharan Africa, which also happens to have less financial and
institutional capabilities to mitigate effects of climate change (Tsigaris and Wood,2016).
In a study that uses a multi-regional Computable General Equilibrium (CGE) Model, it was
found that climate change impacts were experienced by developing countries the most, where
it acts as a hurdle in the path of income convergence and equity. Developing countries such
as China and India suffered from a significant negative impact on real GDP (Eboli et al.,2010).
In another study where, overall economic damaged cause by climate change was assessed, it
was projected that losses in the range of 2-20% of GDP are expected to occur in the poorest
third of countries by the end of the 21st century (Solomon et al.,2017). In a different study, a
cross validation exercise was performed on 800 models depicting the temperature-GDP
relationship. Results showed that the impact of marginal temperature on GDP growth globally
was not statistically significant (Newell et al.,2021).
In previous literature the focus has been mainly on female primary and secondary schooling
effects on economic growth, yet limited studies have examined the effect of female tertiary
level education on economic growth. This study focuses on the tertiary educational level in
attempt to further explore a less visited aspect of female education. Additionally, from a
climate change perspective, this study attempts to incorporate mean temperature in a
modified Solow growth model to account for how climate changes can impact GDP growth
where in previous literature this relation is mainly study in separate models as mentioned
earlier such as CGE models. Accordingly, the proposed hypotheses for this study are:
H1: Female tertiary education does affects economic growth.
H2: Mean temperature affects economic growth.
Methods
Study area and data collection
A balanced panel of data is used consisting of 297 observations from 33 developing countries
from all over the world covering the period from 2001-2019, namely: Kazakhstan, Kyrgyz
Republic, Azerbaijan, Armenia, India, Pakistan, Vietnam, Thailand, Philippines China, Bahrain,
Lebanon, Saudi Arabia, El Salvador, Mexico, Panama, Brazil, Colombia, Paraguay, Ecuador,
Uruguay, Algeria, Egypt, Nigeria, Democratic Republic of Congo, South Africa, Kenya,
Mozambique, Burkina Faso, Senegal, Rwanda, Burundi and Eswatini. The choice of these
specific countries and timeframe is based on the Millennium Development Goals 2015 report
and its Regional Fact Sheet, as specific regions were applauded for their progress in the
millennium development goals and more specifically education. Accordingly, this study’s
developing countries were targeted from the aforementioned regions. The period from 2001-
2019 was chosen to coincide with the timeframe set for achievement of the goals from 2000-
2015 so that impact of the goals is highlighted whether for education or environmental
stability.
The cross-sectional fixed effects model is used for the panel data analysis with a period
random effects specification. The dependent variable is the annual growth rate of real gross
domestic product per capita (GR_R_GDP) obtained from the World Bank Data. Independent
variables are annual growth rate of gross fixed capital formation (GR_FC) obtained from World
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 22
Bank Data, annual growth rate of female tertiary graduates (GR_F_TG) data was triangulated
and interpolated from three sources, namely: UNESCO institute of Statistics, Barro and Lee
dataset (2013) and World Bank Data and annual growth rate of mean temperature variable is
obtained from National Centers for Environmental Information (NOAA).
This research study uses secondary data, panel data has been used for availability purposes as
no sufficient time series data could be collected for individual countries. In addition, both
missing and unobserved variables are considered under panel estimation (Arellano and
Bond,1991; Matyas and Sevestre,2013).
Measurement of the variables
In this study the dependent variable is represented by annual growth rate of gross domestic
product per capita (GR_R_GDP), while independent variables are annual growth rate of female
graduates from tertiary education with a ten-year lag (GR_F_TG(-10)), annual growth rate of
gross fixed capital formation (GR_FC), annual growth rate of mean temperature (GR_MT),
annual growth rate of gross domestic product per capita with a one-year lag are the
independent variables (GR_R_GDP(-1)).
Data analysis and tools
Multiple regression analysis using ordinary least squares method was used to test the
relationship between the dependent and independent variables. The used software was e-
Views.
Results
A multiple regression using ordinary least squares was carried out to test the proposed
hypotheses. The final model that was reached after taking into consideration multi-collinearity
(no significant correlation was present between the independent variables) and heterogeneity
is represented below in equation (2):
GR_R_GDP = c+ β1GR_R_GDP(-1) + β2GR_F_TG(-10) + β3GR_MT + β4 GR_FC (2)
Table (1) below shows the estimation results of equation (2) using least squares and cross
section fixed effects and period random effects methods before checking for
Heteroskedasticity.
Table 1: Estimation results of equation (2) using least squares and cross section fixed
effects and period random effects.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 23
A Breusch Pagan test was run to test for heteroskedasticity in the model. The below Table (2)
shows the output of the test for equation (2). It is indicated that there is a high degree of
heteroskedasticity from a cross-sectional perspective since p is at a 0 while a much lower
degree of heteroskedasticity is present from a period perspective where p is equal to 0.8. The
high heteroskedasticity of the cross-sectional effect is accounted for through white cross-
section adjustment.
Table 2: Breusch Pagan test output for equation (2)
To correct for the heteroskedasticity White cross-section adjustment was performed. Table
(3) below shows output for White cross-section adjustment for estimation results of equation
(2).
Table 3: White cross-section adjustment output
The adjusted R-squared shows that the model explains 57% of the variation in the gross
domestic product growth rate (dependent variable). As expected, coefficient for female
tertiary graduates (GR_F_TG) with a 10-year lag, gross fixed capital formation growth rate
(GR_FC) and annual growth rate of Gross domestic product with a 1-year lag (GR_R_GDP(-1))
are positive and significant at a 1% significance level indicating a directly proportional relation
to the gross domestic product growth rate (GR_R_GDP). Unexpectedly, coefficient for annual
growth rate of mean temperature is positive and significant at a 5% significance level,
indicating a positive relationship between mean temperatures and GDP growth.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 24
The coefficient of female tertiary graduates (GR_F_TG) with a 10-year lag, shows that when
rate of female tertiary graduates increases by 1% rate of GDP growth increases by 0.012%, the
10-year lag indicates the time needed for this to take effect; this can reflect time needed for
employment of educated females and might be indicative of hindrances that females in
developing countries face: lack of adequate employment opportunities matching their skill
set, social and cultural hinderances.
As for coefficient of gross fixed capital formation it indicates that as rate of gross fixed capital
formation increases by 1%, GDP growth rate increases by 0.05%, which is justifiable since gross
fixed capital formation is an indication of net investments. The small coefficient might be
attributable to the fact that the sample consists of developing countries that are not always
the most favourable attraction for investments especially foreign ones.
When the annual growth rate of GDP with a 1year lag increases by 1% this leads to an
increase in the annual growth rate of GDP by 0.23%, this can be attributable to the nature of
the business cycle.
As for mean temperatures, when annual growth rate in mean temperature increases by 1%
annual growth rate of GDP increases by 0.04% which was an unexpected result as in most of
the previous literature on climate change a negative impact is usually present. Those
unexpected results led to the questioning of the direction of the relationship between climate
change and economic growth in this study. Accordingly, the below Granger causality test was
performed to assess the direction of causality:
Table 4: Granger Causality Test for Growth rate of real GDP and growth rate of Mean
Temperature (6 year lag)
From the above table, it can be deduced that direction of causality is opposite to what is
proposed in this study, since the null hypothesis “GR_MT does not Granger Cause GR_R_GDP”
is not rejected and the null hypothesis “GR_R_GDP does not Granger Cause GR_MT” is
rejected. It should be noted that the opposite direction of causality found might be due to the
relatively short period studied as climate changes take place over much longer periods of time.
Descriptive statistics are displayed in Table (5) below for the independent variables.
The average growth rate of tertiary female graduates is around 6.53%, where maximum
growth rate is 158.9% and minimum is -50.6%. The rate of growth of gross fixed capital
formation is of average 10.71%, where maximum is 129% and minimum is -81.9%. The
average growth rate of annual mean temperature is around 0.42%, where maximum growth
rate is 81.25% and minimum is -42.75%.
“The crucial distinction between fixed and random effects is whether the unobserved
individual effect embodies elements that are correlated with the regressors in the model, not
whether these effects are stochastic or not” (Greene, 2008). The cross sectional fixed effects*
adjusted for annual growth rate in mean temperature coefficient for each of the 33 countries
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 25
are displayed in Figure (2) below. Despite that the average coefficient for mean temperature
shows a positive relationship to annual growth rate in GDP, when observing the cross-
sectional fixed effects for individual countries it can be noted that countries such as Lebanon
and Brazil showed a negative relation between mean temperature growth rate and GDP while
other countries showed a positive one such as India. These different percentages reflect the
magnitude of the possibly omitted variables that have not been included in the model given
that they are assumed to be fixed and thus do not change over the years.
*The standard error for female tertiary graduate’s variable was found to be bigger when
applying the Hausmann test than in the regression applying both the cross-sectional fixed and
period random effects, indicating that there is heteroskedasticity in the data and thus applying
the Hausmann test would lead to misleading conclusions.
Table 5: Descriptive Statistics for Female graduates from tertiary education (GR_F_TG),
Mean Temperature (GR_MT) and Gross fixed capital formation (GR_FC)
Figure 2: Percentage Effect of Annual Growth Rate of Mean Temperature on Growth rate of
GDP
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 26
Discussion and Conclusion
This study helped highlight the positive and direct relationship between female tertiary
education and economic growth, as well as the correct direction of the relationship between
climate change and economic growth for the sample countries. The coefficient for female
tertiary graduates (GR_F_TG) with a 10-year lag, the gross fixed capital formation growth rate
(GR_FC), the coefficient for mean temperature (GR_MT) and annual GDP growth rate
(GR_R_GDP(-1)) with a 1-year lag are all positive and significant indicating a directly
proportional relation to the GDP growth rate (GDPG_C).
In previous literature (Mitra, Bang and Biswas, 2015) similar findings to our study have been
found where secondary completion rate as a proxy for education was found to be positive and
significant yet at an only 10% significance level where a 1% increase in secondary completion
rate is accompanied by a 0.1% increase in GDP growth which is the closest results to the impact
of our female education coefficient at 0.012% increase in GDP yet at a 1% significance level.
The larger coefficient might be attributable to the larger number of female students enrolled
in secondary education versus those graduated from tertiary education in the sample studied.
Regarding investment, a positive and significant effect of 1% significance level has been found,
where a 1% increase in investment increases GDP growth by 0.149% slightly higher than our
investment coefficient of 0.05%. With regards to lagged growth rate of GDP the results show
a significant yet negative effect where a 1% increase in GDP growth of a 1-year lag causes an
0.549% decrease in GDP growth, on the other hand this study shows a both positive and
significant effect for lagged GDP of 1-year specifically an 0.23% increase in GDP. This difference
might be caused by the different periods studied and the nature of the business cycle at the
studied time period.
Previously mentioned results are consistent with results of (Knowles, Lorgelly and Owen,
2002) where it was found that female education coefficient is both positive and statistically
significant at a 5% significance level and the t-statistic is of a 2.92 value and female education
was represented by the average of schooling of the population aged 15 and above. Coefficient
of female education reflects that a 1% increase in female schooling causes an 0.663% increase
in output per worker, which is of a larger impact than our female education coefficient of
0.012%, although it is of a lower significance level. This difference can be due to the different
periods covered: our study covers years 2001-2019 while this study covers years 1960-1990,
additionally our paper uses a very specific proxy for female education, female tertiary
graduates, while the study uses a much more generic proxy.
Also consistent with our study is (Klasen, 2002) where ratio of years of schooling was used as
a proxy for education. Results of that study show that female-male ratio of expansion in
schooling has a significant and positive effect on economic growth at a1% significance level,
coefficient of female-male ratio of expansion of schooling reflects that when a 1% increase in
female- male ratio of expansion of schooling occurs it causes 0.69% increase in growth of GDP,
also indicating a higher impact for the coefficient when compared to our study’s coefficient of
0.012% increase. Positive investment coefficient was also found to be significant at a 5%
significance level, where it showed that when investment increased by 1% it reflected an
increase of 0.056% in GDP, identical to our study’s coefficient of 0.05% increase in GDP, yet of
a higher 1% significance level.
Our results were parallel to previous literature (Baliamoune-Lutz and McGillivary, 2009) where
the gap in youth literacy between females and males had a negative and significant impact on
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 27
income, where Coefficient for gap was significant at a 1% significance level, where a 1%
increase in the gap causes a 0.2% decrease in income growth reflecting a higher impact on
income growth than our study does at 0.012% percentage change in GDP. The coefficient of
investment was both positive and significant at a 1% significance level where a 1% increase in
investment caused an increase in income growth ranging between 0.13 - 0.16% again
compared to this study’s coefficient of 0.05% it is of relatively larger impact.
On the other hand, our findings were inconsistent with (Oztunc, Oo and Serin, 2015) where
female tertiary education is negatively related to annual GDP per capita growth, where GDP
decreases by 1 unit when tertiary female education is increased by 10 units reflecting an
influence of 10 % of female tertiary education on GDP per capita. We believe the reason for
the contradiction to our results is the nature of jobs available in the sample countries in this
specific study where it was stated that most jobs for female workforce are unskilled labor jobs
and thus obtaining a tertiary education is deemed unnecessary. Another finding that was
inconsistent with ours is (Licumba et al., 2015) that used human capital as a proxy of education
found that with a two-year lag it was both negative and insignificant for growth. Again,
contradiction to our results here may have originated from the fact that the sample under
study was restricted to 5 Southern African countries and the proxy was primary enrolment.
With regards to our climate change proxy variable, annual growth rate in mean temperature
has a positive and a 5% significance level coefficient reflecting the direct relationship to GDP
growth rate, which is contradictory to what previous literature highlighted where climate
change had a negative impact in most cases (Eboli et al., 2010; Solomon et al., 2017) or no
significant impact was observable from an aggregate worldwide perspective (Newell et al.,
2021). This study’s unexpected results led to rethinking the direction of the relationship and
conducting the previously mentioned Granger Causality test to deduce that the results are
significant, yet the relation should be tested in the opposite direction. Another
recommendation would be to increase the time period studied and to test for the direction of
the causality again.
References
Akram, N., Hamid, A. and Bashir, S., 2011. Gender differentials in education and their impact on economic growth
of Pakistan. Journal of Business & Economics, 3(1), p.102.
Arellano, M. and Bond, S., 1991. Some tests of specification for panel data: Monte Carlo evidence and an
application to employment equations. The review of economic studies, 58(2), pp.277-297.
Assaad, R.A., Hendy, R., Lassassi, M. and Yassin, S., 2018. Explaining the MENA paradox: Rising educational
attainment, yet stagnant female labor force participation.
BaliamouneLutz, M. and McGillivray, M., 2009. Does gender inequality reduce growth in subSaharan African and
Arab countries?. African Development Review, 21(2), pp.224-242.
Barro, R.J. and Lee, J.W., 1994, June. Sources of economic growth. In Carnegie-Rochester conference series on
public policy (Vol. 40, pp.1-46). North-Holland.
Barro, Robert and Jong-Wha Lee, 2013, “A New Data Set of Educational Attainment in the World, 1950-2010.
Journal of Development Economics, vol.104, pp.184-198.
Blankespoor, B., Dasgupta, S., Laplante, B. and Wheeler, D., 2010. Adaptation to climate extremes in developing
countries: the role of education. World Bank Policy Research Working Paper, (5342).
Brummet, Q., 2008. The effect of gender inequality on growth: a cross-country empirical study. The Park Place
Economist, 16(1), pp.12-23.
Cuberes, D. and Teignier, M., 2014. Gender inequality and economic growth: A critical review. Journal of
International Development,26(2), pp.260-276.DeSilva, S., & Bakhtiar, M. M. (2011). Women, schooling, and
marriage in rural Philippines.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 28
Dollar, D. and Gatti, R., 1999. Gender inequality, income, and growth: are good times good for women? (Vol.1).
Washington, DC: Development Research Group, The World Bank.
Eboli, F., Parrado, R., & Roson, R. (2010). Climate-change feedback on economic growth: explorations with a
dynamic general equilibrium model. Environment and Development Economics, 15(5), 515-533.
Greene W. H., 2008. Econometric Analysis. Prentice Hall, 100-210.
Guterres, A., 2017. The Sustainable Development Goals Report 2017. United Nations: New York, NY, USA.
Jāhāna, S., 2015. Human development report 2015: Work for human development. United Nations Development
Programme.
Kalaitzidakis, P., Mamuneas, T.P., Savvides, A. and Stengos, T., 2001. Measures of human capital and nonlinearities
in economic growth. Journal of Economic Growth, 6(3), pp.229-254.
Klasen, S., 2019. What explains uneven female labor force participation levels and trends in developing countries?.
The World Bank Research Observer, 34(2), pp.161-197.
Klasen, S., 2002. Low schooling for girls, slower growth for all? Crosscountry evidence on the effect of gender
inequality in education on economic development. The World Bank Economic Review, 16(3), pp.345-373.
Knowles, S., Lorgelly, P.K. and Owen, P.D., 2002. Are educational gender gaps a brake on economic development?
Some crosscountry empirical evidence. Oxford economic papers, 54(1), pp.118-149.
Licumba, E.A., Dzator, J. and Zhang, J.X., 2015. Gender equality in education and economic growth in selected
Southern African countries. The Journal of Developing Areas, 49(6), pp.349-360.
Mátyás, L. and Sevestre, P. eds., 2013. The econometrics of panel data: handbook of theory and applications
(Vol.28). Springer Science & Business Media.
Mitra, A., Bang, J.T. and Biswas, A., 2015. Gender equality and economic growth: Is it equality of opportunity or
equality of outcomes?. Feminist Economics, 21(1), pp.110-135.
Newell, R.G., Prest, B.C. and Sexton, S.E., 2021. The GDP-temperature relationship: implications for climate change
damages. Journal of Environmental Economics and Management, 108, p.102445.
NOAA National Centers for Environmental information, Climate at a Glance: Global Time Series, published
November 2021, retrieved on November 20, 2021 from https://www.ncdc.noaa.gov/cag/
Oztunc, H., Oo, Z.C. and Serin, Z.V., 2015. Effects of Female Education on Economic Growth: A Cross Country
Empirical Study. Educational Sciences: Theory and Practice, 15(2), pp.349-357.
Razavi, S., 2012. World development report 2012: Gender equality and development—A commentary.
Development and Change, 43(1), pp.423-437.
Seguino, S., 2000. Accounting for gender in Asian economic growth. Feminist Economics,6(3), pp.27-58.
Seguino, S., 2000. Gender inequality and economic growth: A cross-country analysis. World Development, 28(7),
pp.1211-1230.
Solow, R.M., 1956. A contribution to the theory of economic growth. The quarterly journal of economics, 70(1),
pp.65-94.
Hsiang, S., Kopp, R., Jina, A., Rising, J., Delgado, M., Mohan, S., Rasmussen, D.J., Muir-Wood, R., Wilson, P.,
Oppenheimer, M. and Larsen, K., 2017. Estimating economic damage from climate change in the United States.
Science, 356(6345), pp.1362-1369.
Stokey, N.L., 1994, June. Comments on Barro and Lee. In Carnegie-Rochester Conference Series on Public Policy
(Vol. 40, pp. 47-57). North-Holland.
Todaro, M.P. and Smith, S.C., 2021. Economic development.
Vare, P. and Scott, W., 2007. Learning for a change: Exploring the relationship between education and sustainable
development. Journal of Education for Sustainable Development, 1(2), pp.191-198.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 29
Exploring the factors affecting consumers’ willingness to
purchase alternative fertilisers in the UK
Cameron HewardA,B, Ourania TremmaA, Eric SiqueirosA and Daniel MayA
A Food, Land & Agribusiness Management Department, Harper Adams University, Newport
Shropshire, UK
B Lohas Recycling, Shropshire, UK
Extended Abstract
The UK population increased to 66.8 million in 2019 (ONS, 2021), making it crucial for
agriculture and farmers to meet the demand for produce while limiting the negative impact
on the environment due to intensive farming and fertilisers use. Therefore, prioritising
sustainability has been the goal for the farming community and the environmentally aware
consumer. In this regard, DEFRA (2021) is promoting alternative fertilisers (AF), and
consumers now appear more positively inclined towards them. Specifically, in recent years,
the popularity has increased towards AF such as chicken manure pellets (CMP), sheep’s wool
pellets and digestate in agriculture and the horticultural market due to high consumer
demand.
On the side of horticulture, the trend of adopting AF is followed with evidence supporting that
67% of UK gardeners claim to be eco-conscious and 46% stating that they are already using
organic fertilisers. This is reflected in the figures provided by the UK Organic Market Report in
2020 revealing that the market has seen a growth in the past eight years whereas in 2019 a
4.5% increase has been recorded in sales reaching £2.45bn. During the covid-19 pandemic,
the UK horticultural sector saw a substantial increase in gardening equipment and seeds sales.
During the peak of the 2020 lockdown, sales were reportedly 20 times higher than 2019
(Perrone, 2020). This is due to the trend observed from an increased number of consumers
who grew their own vegetables and fruits during the lockdown periods. This aligns with the
increase seen in environmental awareness amongst UK consumers in 2021 with 85% now
making more sustainable lifestyle choices (Deloitte, 2021). In this sense, the term “eco-
conscious” has been widely used to describe an individual who shows concern for the
environment. This increased awareness has led horticultural consumers to seek for AF such as
CMP due to their effectiveness as a non-CF and valuable nitrogen source for plants to grow
green leaves.
However, there is limited evidence regarding the factors influencing consumers' willingness
to purchase AF in the UK, and in particular CMP. Previous literature showed a gap into studies
exploring the sector including a lack of domestic research on AF, a scarcity of consumer
research on AF, and a lack of information on CMP. The limited evidence found on AF could be
attributed to the fact that the concept is relatively new and there are few AF available to the
market. Thus, the present study attempts to fill in this knowledge gap and to contribute to
existing literature regarding consumers’ views and purchase attitudes towards AF and CMP.
Gaining an understanding of these factors can assist in proposing strategies that could induce
the demand for AF by targeting some of these factors. Therefore, results have the potential
to induce beneficial environmental behaviour that can contribute to Net Zero. To this respect,
the present study explores consumers’ perceptions and attitudes affecting consumer
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 30
intention to purchase CMP as AF. In addition, the factors affecting consumers’ intention to
purchase CMP as AF are explored and the level of the awareness regarding the benefits of
CMP as AF is evaluated. This is pursued using the Theory of Planned Behaviour (TPB) expanded
with more variables that may influence the purchase behaviour. TPB was proposed by Ajzen
(1985), who estimated that the subjective norm, perceived behavioural control, and attitude
influence intention to purchase, which in turn affects actual behaviour. A semi-structured
questionnaire was created and distributed online in different social media accounts whereas
snowball and convenience sampling techniques were employed. The questionnaire was
composed of both open and closed ended questions such as binomial dichotomous questions
and 5-point Likert scale questions. The first section of the questionnaire included demographic
questions to create the profile of the participants as well questions related to consumers’
perceptions regarding AF and the benefits arising from the usage of AF were included and the
level of awareness and knowledge towards sustainability goals, AF and CMP was examined.
The next section involved questions related to fertiliser characteristics that may affect the
purchase along with subjective norm influences and 5-point Likert scale statements examining
the willingness to purchase CMP as AF. Prior to the data collection, a pilot survey was
conducted to 10 consumers allowing for minor spelling corrections to be made whereas the
final questionnaire was open for two weeks and results to 180 responses to be gathered. Data
was presented using descriptive statistics and inferential statistics employed included the
Spearman correlation analysis to identify relations between ordinal variables and multiple
regression analysis using backward Wald to explore significant causal relations between the
purchase intention and the factors that impact it. Moreover, Mann-Whitney U test and Kruskal
Wallis H test detected significant differences across the participant demographics on the
median willingness to purchase AF (Cronk, 2018). Principal Component Analysis (PCA) was
used to reduce the number of variables and the reliability of the new components was tested
with Cronbach alpha coefficient where 0.7 and higher indicated high reliability levels (Pallant,
2010). In terms of qualitative data, these were coded and analysed using thematic analysis to
detect patterns across the respondents.
Results showed that the most important element influencing consumers' willingness to buy
CMP was its nutritional content. This demonstrates consumers are concerned about CMP's
low NPK value compared to CF’ and multiple soil benefits associated to its use (Byju's, 2022).
To a lesser extent, price influenced buyers’ intention followed by alternative fertiliser made
from animal by-products; smell was least influential. Consumers were willing to pay less for
CMP compared to CF as also supported by the lower market prices. This attitude may be
explained by the products ‘introduction’ stage and time needed to be established in the
market (Taisch et al., 2011). Cheaper introductory prices would gain consumers interest,
increase purchase intention, and therefore demand and prices (Estelami and Bergstein, 2006).
This was also supported in the results where consumers who showed a higher level of trust in
CMP over CF exhibited a higher purchase intention. Also, preference towards AF made from
animal-by-product could be explained by the pasteurization process undertaken by
manufacturers making products safer to use (Tur-Cardona et al., 2018). Although the
volatilization process creates a strong odour due to ammonia discouraging many consumers
from purchasing CMP, smell played a neutral role to purchase intention in this survey. This
could be due to most participants residing in rural/semi-rural areas and being involved in the
agricultural sector; thus, being more familiar to this odour. Consumers’ purchase is mainly
affected by the products quality, then safety and sustainability attributes, because consumers
expect a level of safety when purchasing CMP products. The products quality is important to
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 31
consumers as this maintains their loyalty leading to an increase in profitability (Wiengarten
and Pagell, 2012). In addition, consumers perceive CMP as effective which may be linked to
the perception that it slowly releases nutrients into the ground. CMP slow release over a
period of three months helps root development and encourages overall plant health leading
to better overall growth (Purnomo et al., 2017). Lastly, a preference towards CMP made in the
UK rather than abroad was supported. This could be due to the UK importing most of its CMP
from EU countries, predominately Netherlands. The implications of import tariffs caused by
Brexit has promoted supporting local, empowering the UK economy, and saving money on
import tariffs. There were multiple factors seen to affect consumers’ intention to buy CMP as
supported by regression analysis. These included trust, lower price than chemical fertiliser,
external factors, prior awareness, and price. Product trust had a positive significant impact on
purchase intention with increased trust leading to increased purchase. If consumers trust a
product or service they invest more and are willing to spend more on this product (Woolley
and Fishbach, 2017). CMP’S Lower price than CF had a positive impact on purchase intention.
This is explained by consumers’ confidence in a product; as CMP is new to the domestic
market, consumers are willing to try it but only if cheaper than a product they trust (KUMAR,
1996).
External factors had a positive impact on purchase intention e.g., goals set by the government
for the country. This is explained by an increase in eco-friendly consumers from a culture
change in consumers wanting to look after the environment (Popovic et al., 2019). Product
prior awareness had a small positive impact on purchase intention; with increased prior
awareness consumers are more likely to purchase it over competitors’ products, as they have
a better understanding of the product, what it offers over competitors and increased trust
levels (Rao and Monroe, 1988). The final factor was price which played a negative impact on
purchase intention as increasing a products price means consumers are more likely to change
to a competitor. This is explained by higher priced products selling fewer units, leading to
competitors products becoming more appealing if they can offer the same purpose at a
cheaper rate (Zhao et al., 2021).
Participant demographics were not found to affect CMP purchase intention. This could be
explained by the fact that traditionally older demographics were more interested in
gardening. An increase however has been seen in younger gardeners due to several reasons
including climate change, Brexit and producing more food in the UK (Sia et al., 2022). There
were multiple levels of awareness regarding the benefits of CMP as AF. The participants who
studied in the agriculture sector were most likely to purchase CMP possibly because they can
understand that CMP offers overall more value in the form of macro and micronutrients and
soil health than CF can offer (Hoover et al., 2019). Also, the level of awareness about CMP’s
benefits as an alternative fertiliser was influenced by environmental consciousness. 74
participants said they were environmentally conscious, indicating a significant increase in
environmental care. This is explained by the government's and other companies' increased
efforts to set net zero goals for the public to strive for through their purchasing habits and
behaviour.
Based on these results, when companies are marketing AF such as CMP, it is important to
emphasise other beneficial features besides the NPK value, such as improved soil health.
Government could also focus on the advantages of utilising AF by linking their use to UK net
zero targets. Policy makers should subsidise research into the effects of AF on the horticultural
industry. There were some limitations associated to the study which affected the overall
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 32
results including sample size, data availability, sampling techniques and time frame. Thus,
further research could of interviews to gain an in depth understanding of consumers thoughts
on adopting AF over CF.
Keywords
Alternative fertilisers; net zero; sustainability
Presenter Profile
Dr Eric Siqueiros works as Innovation Manager for the European Regional Development Fund
project AGRI at Harper Adams University since 2018. He is also a lecturer for the Food Land
and Agribusiness Management Department. His main interests are in developing processes
and strategies for the sustainability metrics of the Food and Agricultural Sector. Eric holds a
PhD focused in Sustainable Energy and Waste Recovery from Newcastle University. In recent
years he has been working with sustainability assessment tools for farm management as well
as Life Cycle Assessment of different crop systems.
* Corresponding Author: Dr Ourania Tremma, Harper Adams University, Newport Shropshire, UK,
TF10 8NB, email: otremma@harper-adams.ac.uk
References
I. AJZEN & M. FISHBEIN. 1969. The prediction of behavioral intentions in a choice situation. Journal of
Experimental Social Psychology, 5(4), 400-416
BYJU’S. 2022. Fertilizers Vs Manure- Difference between Fertilizers and Manures. BYJUS.com.
https://byjus.com/biology/fertilizers-vs-manure/
DEFRA - Department for Environment, Food and Rural Affairs. 2021. Use organic fertiliser. GOV.UK.
https://www.gov.uk/guidance/use-organic-fertiliser
DELOITT. 2021. Four out of five UK consumers adopt more sustainable lifestyle choices during COVID-19 pandemic.
Deloitte United Kingdom. https://www2.deloitte.com/uk/en/pages/press-releases/articles/four-out-of-five-uk-
consumers-adopt-more-sustainable-lifestyle-choices-during-covid-19-pandemic.html
H. ESTELAMI & H. BERGSTEIN. 2006. The impact of market price volatility on consumer satisfaction with lowest-
price refunds. Journal of Services Marketing, 20(3), 169-177.
F. HARVEY. 2021. Farmers in England to be paid for looking after soil health from next year. the Guardian.
https://www.theguardian.com/environment/2021/dec/02/farmers-in-england-to-be-paid-for-looking-after-
soil-health-from-next-year
N.L. HOOVER, J. Y. LAW, L. A. M. LONG, R. S. KANWAR, & M. L. SOURIP. 2019. Long-term impact of poultry manure
on crop yield, soil and water quality, and crop revenue. Journal of Environmental Management, 252.
N. KUMAR. 1996. The power of trust in manufacturer-retailer relationships. Harvard Business Review, 74(6), 92-
106.
ONS - Office for National Statistics. 2021. Overview of the UK population - Office for National Statistics. ons.gov.uk.
https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/articl
es/overviewoftheukpopulation/january2021
J. PALLANT. 2010. SPSS survival manual: a step by step guide to data analysis using SPSS (4th ed.). McGraw Hill
H. N. PAHALVI, L. RAFIYA, S. RASHID, B. NISAR & A. N. KAMILI. 2021. Chemical Fertilizers and Their Impact on Soil
Health. Microbiota and Biofertilizers, 2, pp. 1-20.
J. PERRONE. 2020. How coronavirus changed gardening forever. ft.com. https://www.ft.com/content/c3abc0bb-
7ade-4ae1-8d2b-d3fa6be53416
I. POPOVIC, B.A.G. BOSSINK, & P. C VAN DER SIJDE. 2019. Factors Influencing ConsumersDecision to Purchase
Food in Environmentally Friendly Packaging: What Do We Know and Where Do We Go from Here?
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 33
Sustainability (Basel, Switzerland), 11(24), 7197.
C. PURNOMO, S. INDARTI, C. WULANDARI, H. HINODE, & K. NAKASAKIK. 2017. Slow Release Fertiliser Production
from Poultry Manure. Chemical Engineering Transactions, 56, 1531-1536. 10.3303/CET1756256
A. R. RAO, & K. B. MONROE. 1988. The Moderating Effect of Prior Knowledge on Cue Utilization in Product
Evaluations. Journal of Consumer Research, 15(2), 253-264. 10.1086/209162
A. SIA, P. Y. TAN, J. C. M. WONG, S. ARAIB, W. F. ANG & K. B. H. ER. 2022. The impact of gardening on mental
resilience in times of stress: A case study during the COVID-19 pandemic in Singapore. Urban Forestry and
Urban Greening, 68, 127448. 10.1016/j.ufug.2021.127448
M. TAISCH, B. P. CAMMARINO & J. CASSINA. (2011). Life cycle data management: first step towards a new product
lifecycle management standard. International Journal of Computer Integrated Manufacturing, 24(12), 1117-
1135
J. TUR -CARDONA, O. BONNICHSEN, S. SPEELMAN, A. VERSPECHT, L. CARPERNTIER, L. DEBRUYNE, F. MARCHAND,
B. H. JACOBSEN & J. BUYSSE. 2018. Farmers' reasons to accept bio-based fertilizers: A choice experiment in
seven different European countries. Journal of Cleaner Production, 197, 406-416.
10.1016/j.jclepro.2018.06.172
WELSH GOVERNEMENT. 2014. Nitrate Vulnerable Zones in Wales Guidance for Farmers.
https://gov.wales/sites/default/files/publications/2019-06/nitrate-vulnerable-zones-nvz-guidance-for-
farmers.pdf
F. WIENGARTEN & M. PAGELL. 2012. The importance of quality management for the success of environmental
management initiatives. International Journal of Production Economics, 140(1), 407- 415.
10.1016/j.ijpe.2012.06.024
K. WOOLLEY & A. FISHBACH. 2017. A recipe for friendship: Similar food consumption promotes trust and
cooperation. Journal of Consumer Psychology, 27(1), 1-10. 10.1016/j.jcps.2016.06.003
H. ZHAO, X. YAO, Z. LIU & Q. YANG. 2021. Impact of Pricing and Product Information on Consumer Buying Behavior
With Customer Satisfaction in a Mediating Role. Frontiers in Psychology, 0, 2. 10.3389/fpsyg.2021.720
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 34
Factors affecting farm business resilience
Iona HuangA, Karl BehrendtA, Nigel HillA, Steve DunkleyB and Sarah HurfordB
AHarper Adams University, Shropshire, Newport, TF10 8NB, UK
BAgriculture and Horticulture Development Board, UK
Abstract
Direct payments under the Basic Payment Scheme (BPS) will be phased out in England by 2027,
with some 38% of farm businesses having costs that exceed revenue when direct payments
are excluded (AHDB, 2021). Furthermore, 48% of farmers indicate that the loss of BPS will
have biggest impact on business going forwards (DEFRA, 2021). Post-BREXIT international
trade negotiations between the UK and the EU and other countries have added more
uncertainties for British farmers. To cope with the changing economic and institutional
conditions, resilience thinking is on the top of agenda in policy making. Meuwissen et al.
(2019) regarded farm resilience as capacities of robustness, adaptability, and transformability
in the face of economic, environmental, social, and institutional shocks and stresses.
This study aims to explore English farmers’ perceived business resilience and its influencing
factors based on 1769 responses obtained during September 2021 to May 2022. The survey
questionnaire included 20 statements to measure perceived farm business resilience in
addition to farm key performance indicators, farmers’ attitudes about future of farming and
socio-demographic attributes of the farmers and their farms.
The study found that nearly 40% of the farmers were “resilient” or “very resilient”. Younger
farmers, tenant farmers, and full-time farmers reported a higher level of business resilience
than other groups. The 65 and over age group, farmers with mixed ownership status or part-
time farmers reported the lowest level of business resilience. Dairy and cereal farmers
reported the highest level of resilience, whilst livestock farmers, particularly LFA livestock
farmers reported the lowest level of resilience on average. Confidence in responding to
changes, farm performance, farm size and having information to inform business planning
were the most important predictors of farm business resilience.
Keywords
Farm resilience; loss of Basic Payment Scheme (BPS); Farmers in England; Predictors of farm
resilience.
Presenter Profile
Dr Iona Yuelu Huang is a senior lecturer at Harper Adams University. She has been a member
of several research teams, including AgroCycle (a Horizon 2020 funded project on valorisation
of agri-food waste) and the Newton Fund Institutional Links project “Sustainable Agribusiness
Model for Poverty Reduction among Thai Small-scale Rubber Farmers”. Her research interests
fall into the broad categories of food waste management, governance of supply chain,
agribusiness decision making and economic impact of agri-tech and innovation adoption.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 35
Estimating Biomass Carbon stocks in Agriculture Land for
the Mediterranean using remote sensing data
Petridou Kariofillia*, Angelos Mimis and Kostas Bithas
Institute of Urban Environment and Human Resources, Department of Economic and
Regional Development, Panteion University of Social and Political Sciences, Athens, Greece
Abstract
Climate change has a crucial impact on European agriculture in plenty of ways. The role of
land use systems, such as agriculture, as a climate change mitigation and adaptation strategy
is important as these systems can collect atmospheric carbon dioxide (CO2) and store carbon
(C). Although biomass carbon storage in agriculture has been highly neglected. The
methodological difficulties in estimating the C stock of biomass and soil storage of Carbon are
reinforced by the lack of reliable estimates of the agriculture area. This research analyses the
relationship between changes in tree cover in agricultural areas of the Mediterranean area
(more specifically in the regions of Spain, Italy and Greece) and the storage of biomass carbon
(associated with the related mitigation of CO2 emissions). Remote sensing images have
become a valuable source of data for this analysis. Α set of remote sensing data with MODIS
satellite images was used and was combined with Tier 1 carbon storage estimates to estimate
carbon dioxide storage for the Mediterranean climate zones. The measurements for biomass
carbon were made at the overall level for the Mediterranean but also separately for the
national and regional levels of Italy, Greece and Spain. The findings of the research showed
that the distribution of tree cover in agricultural areas widely followed the climatic zones.
Most part of the agricultural land in Europe is estimated at levels around 10 t C / ha.
Keywords
Carbon stocks, agricultural land, MODIS satellite images, biomass, tree cover
Presenter Profile
Kariofillia Petridou is a PhD Student at Panteion University in the Department of Economic and
Regional Development. Her research interests focus on agent-based modelling, decision
making and agricultural policy. She holds a BSc in Geography from the Harokopio University
of Athens and a MSc in Urban and Regional Development from Panteion University of Athens.
* Corresponding Author: Kariofillia Petridou, Panteion University, Athens, Greece, 17671, email:
filiwpet@gmail.com
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 36
Introduction
Agriculture is a key sector as far as is concerned climate change. The main causes of climate
change are the greenhouse effect and global warming. Global warming, the rise in the
temperature of the Earth's atmosphere and oceans, is believed to be mainly due to rising
atmospheric concentrations of so-called Green House Gases (GHG), and carbon dioxide (CO2)
is a major GHG (Nair et al., 2009). Global land use change contributes to the effects of climate
change. Climate change requires measures to reduce greenhouse gas emissions and adapt
them globally and regionally. Agriculture is a factor that contributes significantly to climate
change but has the potential to reduce climate change. Changing land use in agriculture and
agricultural production has contributed and continues to contribute significantly to the effects
of global warming. Agriculture and tree cover have the potential to alleviate climate change.
Agricultural production and land use change significantly affect greenhouse gas (GHG)
emissions (Zomer et al., 2016). To slow down the effects of climate change, greenhouse gas
emissions must be reduced. Carbon dioxide (CO2) is the greenhouse gas most produced by
human activities and is responsible for 63% of global warming due to these activities. Various
factors determine the complex relationship between the influence of greenhouse gas
emissions and the concentration of these gases in the atmosphere. However, there are two
strategies available to mitigate CO2 growth: reducing emissions or increasing atmospheric
CO2 uptake by plants through photosynthesis thus increasing biomass in terrestrial
ecosystems (Zomer et al., 2008).
The global role of tree-based carbon sequestration on agricultural land has not been well
understood and may have been significantly underestimated. According to the European
Commission (2018), 16% of the current Mediterranean area is likely to become barren land by
the end of the century and in many southern European countries, the productivity of rural
work is to be reduced by 10-15% compared to current levels. Agricultural forestry
(agroforestry) is often discussed as a strategy that can be used to both adapt to and mitigate
climate change (Zomer et al., 2016). One of the approaches to reducing the concentration of
CO2 in the atmosphere is the capture of carbon (C), the process of removing C from the
atmosphere and depositing it in a tank (Nair et al., 2009; Ramachandran Nair et al., 2010).
While the importance of biomass carbon in forests (above and below ground) is widely
recognized, the biomass carbon reservoir on agricultural land is negligible. For these reasons,
there is a suitable ground for investigating the carbon uptake of biomass in agricultural land
(Smith, 2012).
The present study aims to assess the importance of trees in agricultural areas and their
contribution to the Mediterranean lands for the capture of biomass carbon. This analysis
concerns the Mediterranean region and more specifically estimates the biomass carbon at
national and regional levels for the Mediterranean countries (Italy, Spain, Greece) and Europe
as a whole. In addition, a comparison was implemented for the time periods 2000-2018 for
the existence and detection of changes and to be pinpointed spatial patterns both within the
country but also between countries and regions. These calculations were based on IPCC Tier
1 default estimates of carbon stored in different land types and bioclimatic zones and were
combined with tree cover data based on MODIS satellite remote sensing images.
Methods
Remote sensing techniques have many advantages in estimating above ground biomass over
traditional field measurement methods and provide the ability to estimate biomass at
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 37
different scales, using either linear or non-linear regression models (Houghton, 2005; D. Lu,
2005; Dengsheng Lu, 2006; T. Vashum, 2012). Remote sensing images can be used to estimate
biomass above ground in at least three ways: classification of vegetation cover and mapping
of vegetation type, indirect estimation of biomass through some quantitative relation
(regression equations, NDVI, etc.), dividing the spatial variability of vegetation cover into
relatively zones or classes, which can be used as a sampling frame for soil identification and
measurements (Ponce-Hernandez, 2004). Although there are no practical methods for directly
measuring all forest carbon stocks in a country, both terrestrial measurements and remote
sensing data on forest characteristics can be converted into estimates of national carbon
stocks using allometric relationships and Optical satellite data systems (MODIS, Landsat,
SPOT) commonly used for deforestation detection and can detect changes in forest area more
accurately (Gibbs et al., 2007; West et al., 2010).
The research methodology which is followed in this study is based on the methods of the
scientific article of Zomer et al. (2016). This study was undertaken to investigate the
significance of agricultural land for carbon sequestration and to mitigate the effects of climate
change in the Mediterranean zone. Estimating the carbon biomass; The first step was to be
found the percentages of tree cover in the agricultural land. To estimate the percentage of
tree cover only in agricultural areas, a set of remote sensing data with MODIS satellite images
from 2000 to 2018 was used and combined with the Global Land Cover 2000 database (GLC
2000) to export only categories belonging to agricultural land. The data used to perform this
procedure are as follows:
MOD44B MODIS / Terra Vegetation Continuous Fields Yearly Global 250m - Collection
6 (2000 through to 2018):
Percent Tree Cover
Global Land Cover 2000 (GLC 2000) Database • Land-cover categories
Tree coverage has been recorded from the VCF-Collection 6 data set for the years 2000 - 2018,
because the time period covered by the study is almost 20 years and to reduce the impact of
this variability on the estimates of change during period and in order to the results are more
reliable, the first three years of the data set (2000-2002), the three years (2008-2010) and the
last three years (2016-2018) were calculated on average. In this way, the 3-year average for
the different time periods was used to analyse the changes. In addition, three types of
agricultural uses from the Global Land Cover 2000 land use database were used to export the
categories belonging to agricultural land, which are the following:
Cultivated and Managed Areas (agriculture - intensive),
Cropland / Other Natural Vegetation (non-trees: mosaic agriculture / degraded
vegetation)
Cropland / Tree Cover Mosaic (agriculture / degraded forest)
With the help of ArcGIS software and after calculating the three-year average for the
percentage of tree cover, the pixels were extracted for all three years (2000, 2010, 2018)
where they belonged to the categories defined as agricultural land. Then, using the
percentage of tree cover only for the agricultural land, the carbon estimates of the biomass in
the specific areas were calculated. To quantify biomass carbon estimates on agricultural land,
the default IPCC Tier 1 biomass carbon estimates stored in different types of soil cover
depending on the climatic zones located and combined with the ground cover estimates were
used. According to the IPCC Guidelines of 2006 (Chapter 5, section 5.2.1) changes in carbon in
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 38
cultivated areas that remain in the same land use category can be estimated either by: (a)
annual growth and loss rates of biomass or by (b) carbon stocks at two time points, depending
on the Tier method used.
The "New Global Tier-1 Carbon Map for IPCC Tier-1 for the year of 2000" (available from the
Carbon Dioxide Information Analysis Center (CDIAC) Oakridge National Laboratory) was used
for global Tier 1 biomass estimates (Ruesch & Gibbs, 2008) synthesized and mapped the
default IPCC Tier-1 values using a global land cover map stratified by continent, ecosystem,
and forest disturbance, and aggregated a total of 124 carbon zones or areas with unique
deposit values based on IPCC Tier-1 methods. In order to take into account the added
contribution of tree cover to agricultural land, the default value of category 1 biomass carbon
for agricultural land (5tC / ha) was used as the base value, when there are no trees in this area
(tree cover = 0%), regardless of the climatic zone located receives a biomass carbon value of
5 tC / ha.
For the calculation of biomass, the percentage of tree coverage was divided according to the
climatic zone (carbon zone) to which it belongs. In the context of this dissertation, the values
for the Mixed Classes Forests (GLC2000 Classes 6-¬8) for 5 climate zones were used for Europe
by the New Global Tier-1 Carbon Map for IPCC Tier-1 for the year of 2000 which are the
following:
Subtropical Dry Forest
Subtropical Mountain Systems
Oceanic Forest Temperate
Continental Forest Temperate
Temperate Mountain Systems
According to the climate zone and the default carbon value obtained by the above climate
zones according to the table from the New Global Tier-1 Carbon Map for IPCC Tier-1 for the
year 2000 a linear increase of biomass carbon from 0% was calculated up to 100% tree
coverage depending on the climatic zone to which it belongs. Practically, using as a basis the
percentage of tree cover for each year was reclassified in tC from the minimum value of 5t C
/ ha to the maximum value obtained by biomass carbon in the 5 different climatic zones used,
biomass carbon values in agricultural areas if there is 100% tree coverage is equal to the
relative price for Mixed Forest Classes, in each climate zone. The results of the estimates were
calculated in tC / km2 and then converted to t C / ha. In addition, the difference in the carbon
level of biomass was calculated both for the decade 2000-2010 and for almost twenty years
from 2000-2018. For the calculation of biomass carbon for each country and its regions, the
geographical-administrative limits of Eurostat - Nuts 2016 were used. The calculation both at
country and region level was done in t C / km2 and then converted to tC / ha.
Results
Areas that are either non-agricultural or urban areas have been excluded from the tree cover
data. The area of agricultural land has been stratified for each value of tree cover from 0 to
100. The Mediterranean countries seem to have a low rate of tree cover up to 15%, a pattern
that is followed over time for all 3 years under consideration. Over a period of almost twenty
years (2000-2018), most European countries have low to moderate tree cover rates (10% -
30%) on agricultural land. Nevertheless, between years 2000 - 2018, there is a small decrease
of 2% of the tree coverage both between 2000 - 2010 and 2010 - 2018. More specifically, 82%
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 39
was the maximum value of the percentage of tree cover in 2000, in 2018 the maximum value
is at 78%. Over time, as shown in Figure 1, in Europe the percentage of tree cover in almost
twenty years (2000-2018) shows a decrease of up to -8% while the difference in the
percentage of tree coverage shows values from -72% to + 65%. In addition, it is found that a
small part of Greece and Italy show an increase of up to 15%. Between the years 2000-2018,
Europe has a low rate of tree coverage of up to 20%, a fact that is a following pattern in the
Mediterranean countries as well.
Figure 1: Percent of tree cover in agricultural areas for the years 2000, 2010 and 2018
respectively and change in the percentage of tree cover for the years 2000 2018.
Europe shows a low reduction in biomass carbon, this same pattern is followed and comparing
the changes between the years 2010-2018 and 2000-2018 (Table 1). However, observing the
changes from 2000 to 2018, it seems that Greece, Spain and Italy have an increase in biomass
carbon levels.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 40
Table 1: Average biomass carbon (tC / ha) for the years 2000, 2010 and 2018 and changes in
Mediterranean countries and Europe.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 41
Figure 2: Biomass carbon for the years 2000, 2010 and 2018
Figure 3. Change of biomass carbon between the years 2000 - 2010 and 2000 - 2018
respectively
Comparing the biomass carbon of the Mediterranean regions with the European average is
observed that 16 of the 56 Mediterranean regions are below the European average in 2000.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 42
More specifically, 11 of these regions are Spanish (see table 2 and Figure 3), 4 of these regions
are in Greece while the only Italian region is Sicilia which is presented below the European
average. The same pattern with slight differences seems to follow in 2010 as 16 regions are
below the European average. The same 4 Greek regions (Attica, North Aegean, South Aegean,
Eastern Macedonia and Thrace) continue to be lower than average, the Italian region of Sicilia
is the only one of the Italian regions that in 2010 has lower biomass carbon levels from Europe.
Spain follows similar patterns with 9 regions at lower levels than Europe. Apart from the
regions of Illes Balears and Comunidad Valenciana which are at higher levels than Europe in
2010. In 2018, 12 regions are at lower levels of biomass carbon than the European average
but none of the regions of Italy. The regions with the lowest levels belong to Greece and Spain;
4 of them are Greek and the remaining 8 are Spanish.
Table 2: Average biomass carbon (tC/ha) for the years 2000, 2010 and 2018 and its change
Conclusion
The distribution of tree cover in agricultural areas widely followed the climatic zones.
Mediterranean countries seem to have a low rate of tree cover up to 15%, a pattern followed
over the years analysis (2000 - 2018). Between the years 2000-2018, Europe has a low
percentage of tree cover up to 20%, a fact that is strongly prominent in the Mediterranean
countries. The percentage of tree cover in the Mediterranean presents small percentage
changes from - 8% to 6% between the years 2000 - 2018. As far as concerned biomass carbon,
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 43
most agricultural areas have fairly low to moderate levels of biomass carbon. Most agricultural
land in Europe is estimated at levels below 10 t C / ha. Mediterranean countries show an
increase in biomass carbon in 2018 compared to the initial year 2000. In addition, Italy and
Greece are at higher levels than the European average. Greece and Italy seem to have the
largest increases in biomass carbon stored on agricultural land. At the regional level in the last
twenty years (2000-2018) positive elements are identified as most of the Mediterranean
regions have an increase in biomass carbon levels compared to 2000. The growth levels for
the regions range from 0.1 - 3, 5 t C / ha. On average, the Mediterranean regions in the variable
of biomass carbon per hectare in agricultural land follow an increasing trend of up to 3 t C /
ha from 2000 to 2018. All regions of Greece and Spain have an increase in biomass carbon
compared to 2000. This a trend that does not seem to be followed by the Italian regions.
Climate change is having an impact on European agriculture in several ways. Slowing down
soil degradation and enhancing carbon sequestration on EU soil is a win-win climate and food
security strategy that reduces CO2 emissions while increasing the fertility and productivity of
EU agricultural land (Jacobs et al., 2019). The EU Climate Change Adaptation Strategy and the
Common Agricultural Policy have enabled adaptation actions in the agricultural sector. The
Common Agricultural Policy (CAP) constitutes the main framework of the European Union's
agricultural policy. Policymakers can implement the potential of agroforestry as a strategy and
a key component both for the adaptation and mitigation of climate change. Biomass carbon
on agricultural land deserves attention for its mitigation potential.
References
Gibbs, H. K., Brown, S., Niles, J. O., & Foley, J. A. (2007). Monitoring and estimating tropical forest carbon stocks:
Making REDD a reality. Environmental Research Letters, 2(4). https://doi.org/10.1088/1748-9326/2/4/045023
Houghton, R. A. (2005). Aboveground forest biomass and the global carbon balance. Global Change Biology, 11(6),
945–958. https://doi.org/10.1111/j.1365-2486.2005.00955.x
Jacobs, C., Berglund, M., Kurnik, B., Dworak, T., Marras, S., Mereu, V., & Michetti, M. (2019). Climate change
adaptation in the agriculture sector in Europe (4/2019). In EEA Report (Issue 04/2019).
Lu, D. (2005). Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon. International
Journal of Remote Sensing, 26(12), 2509–2525. https://doi.org/10.1080/01431160500142145
Lu, Dengsheng. (2006). The potential and challenge of remote sensing-based biomass estimation. International
Journal of Remote Sensing, 27(7), 1297–1328. https://doi.org/10.1080/01431160500486732
Nair, P. K. R., Kumar, B. M., & Nair, V. D. (2009). Agroforestry as a strategy for carbon sequestration. Journal of Plant
Nutrition and Soil Science, 172(1), 1023. https://doi.org/10.1002/jpln.200800030
Ponce-Hernandez, R. (2004). Assessing carbon stocks. Organization, 1, 1–156.
http://books.google.com/books?hl=en&lr=&id=c5gS5HfBZQ4C&oi=fnd&pg=PA1&dq=
Assessing+carbon+stocks+and+modelling+win- win+scenarios+of+carbon+sequestration+through+land-
use+changes&ots=iX4h8Lr_yE&sig=akQE607KUcweRZ-EObxgyoKCSAQ
Ramachandran Nair, P. K., Nair, V. D., Mohan Kumar, B., & Showalter, J. M. (2010). Carbon sequestration in
agroforestry systems. Advances in Agronomy, 108(C), 237–307. https://doi.org/10.1016/S0065-2113(10)08005-
3
Smith, P. (2012). Agricultural greenhouse gas mitigation potential globally, in Europe and in the UK: What have we
learnt in the last 20 years? Global Change Biology, 18(1), 35–43. https://doi.org/10.1111/j.1365-
2486.2011.02517.x
T. Vashum, K. (2012). Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review.
Journal of Ecosystem & Ecography, 02(04). https://doi.org/10.4172/2157-7625.1000116
West, P. C., Gibbs, H. K., Monfreda, C., Wagner, J., Barford, C. C., Carpenter, S. R., & Foley, J. A. (2010). Trading
carbon for food: Global comparison of carbon stocks vs. crop yields on agricultural land. Proceedings of the
National Academy of Sciences of the United States of America, 107(46), 19645–19648.
https://doi.org/10.1073/pnas.1011078107
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 44
Zomer, R. J., Neufeldt, H., Xu, J., Ahrends, A., Bossio, D., Trabucco, A., Van Noordwijk, M., & Wang, M. (2016).
Global Tree Cover and Biomass Carbon on Agricultural Land: The contribution of agroforestry to global and
national carbon budgets. Scientific Reports, 6(July), 1–12. https://doi.org/10.1038/srep29987
Zomer, R. J., Trabucco, A., Bossio, D. A., & Verchot, L. V. (2008). Climate change mitigation: A spatial analysis of
global land suitability for clean development mechanism afforestation and reforestation. Agriculture,
Ecosystems and Environment, 126(1–2), 67–80. https://doi.org/10.1016/j.agee.2008.01.014.
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 45
Sustainable Urban Resilience: Cities in the face of modern
challenges. Case study: The city of Elliniko-Argyroupoli,
Greece
Roido Mitoula and Natalia Gkagkosi
A Department of Economics and Sustainable Development, Harokopio University
Abstract
The present paper deals with the analysis of the current situation of the Municipality of Elliniko
- Argyroupoli, in the region of Attica in Greece, regarding the sustainable urban resilience to
impending disasters. The disasters are divided into natural and technological, of which natural
disasters have affected the Municipality of Elliniko - Argyroupoli in recent years. Climate
change, the increasing trend of urbanization, and the city's complexity are among the main
reasons that necessitate urban resilience to prevent, respond to, and recover from a variety
of impending disasters. The operational plans for civil protection, combined with the
sustainable urban mobility plans and the waste management plans of the Municipality of
Elliniko - Argyroupoli, make it a model municipality for achieving urban resilience. Through the
results of the questionnaire, conclusions are drawn that could be considered useful both for
the further analysis of the current situation and for the design of future policies.
Keywords
Sustainable urban resilience, Municipality of Elliniko Argyroupoli, fractures, city resilient
Presenter Profile
Roido Mitoula is Professor at Harokopio University of Athens. She has scientific publications
and has participated in numerous Greek and international Conferences. She specialises in
issues of “Local and Regional Development - Urban Reconstruction”. She is Editor of
www.sdct-journal.com (ISSN 2241-4010) and Editor of Greek Journal www.sdct-journal.gr
(ISSN 2241-4002). he has organized Scientific Seminars, Scientific Conferences and Scientific
Meetings on Urban Environment and Regional Development.
* Corresponding Author: Roido Mitoula, Professor, Department of Economics and Sustainable
Development, Harokopio University, Greece, email: mitoula@hua.gr
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 46
Introduction
Human civilizations and societies from ancient times until today, have faced countless and
diverse challenges and disasters. The continuous increase in urbanization, climate change and
the complexity of the city are some of the various causes, which make the urban resilience of
cities necessary to face modern challenges. This paper deals with the assessment of the
current situation of the Municipality of Elliniko Argyroupoli in the context of urban resilience.
This paper aims to analyse and explain the current situation of the Municipality of Elliniko -
Argyroupoli regarding the challenges that cities are called to manage so that they can be
considered urban resilience for the prevention and confrontation of various challenges.
The first part constitutes a general theoretical framework to better understand conceptual
determinations. The definition of urbanization and climate change and the correlation
between the two terms are mentioned. In addition, the terms disaster and risk are clarified
with a view to a better understanding of natural and technological disasters. The term urban
resilience, which is the most important part of the present work, the term sustainable
development and the interrelated link between the two terms, are defined.
The second part is the research part of the work which concerns entirely the case study of the
Municipality of Elliniko-Argyroupoli. Firstly, examples of natural disasters that have taken
place in the municipality that has been studied for the last ten years are cited. In addition, the
operational plans for civil protection for the Municipality of Elliniko - Argyroupoli are
mentioned in the context of preventing and dealing with impending disasters and the
sustainable urban mobility plan of the municipality of study is presented. Finally, the
management plan for the waste of the Municipality of Elliniko Argyroupoli is presented.
The third chapter makes a detailed assessment of the current situation of the study area. In
particular, the SWOT analysis is presented to better understand the current situation of the
Municipality of Elliniko - Argyroupoli. Following the collection of anonymous questionnaire
replies, analysis and statistical processing are carried out with means of statistical analysis to
explain the results of the questionnaire "Urban Resilience: Cities against contemporary
challenges".
This research aims to draw some conclusions for the assessment of the urban resilience of the
Municipality of Elliniko-Argyroupoli.
Cities and contemporary challenges
Urbanization and climate change
Urbanization is a phenomenon that has been observed since ancient times. The reasons vary,
such as social, economic as well as environmental (United Nations; Environment programme).
Today, half of the world's population lives in urban areas. In 1950 a third of the world's
population lived in urban areas and according to the United Nations in 2050 it is estimated
that 70% of the world's population will live in large urban areas. However, sustainable
development depends to a considerable extent on managing urban development to achieve
sustainable cities in both developed and developing countries (World Urbanization Prospects,
2018).
The quality of life in cities is inextricably linked to the rate at which cities are drawing on and
managing the natural resources at their disposal. Urbanization is linked to the great pressure
on the environment and land, the increased demand for basic services, infrastructure and jobs
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 47
(United Nations? Environment programme). Therefore, changes are taking place in the way
of life, culture and behaviour of citizens, resulting in the formation of the demographic and
social relationship of urban areas. Due to urbanisation, there is a continuous upward trend in
the number of inhabitants living in urban areas in relation to rural dwellers (World
Urbanization Prospects, 2018). The increased concentration of people in large cities results in
increased economic activities, increased demand for infrastructure and housing. Because of
the above, cities are more vulnerable to natural disasters such as the effects of climate change.
The successful implementation of urban resilience contributes to the reduction of social and
economic losses because it requires the adoption and implementation of immediate policies
to achieve sustainability and address urbanisation to protect the environment (United
Nations? Environment programme).
The definition of climate change is linked to the long term to weather phenomena on Earth,
such as temperature, sea level and frost. The earth's climate has changed rapidly several times
since the planet was created, 4.5 billion years ago. It has undergone extended periods of hot
temperatures as well as periods of glaciers. These cycles have lasted about tens of thousands
or even millions of years. Over the last 150 years, known as the "industrial age", temperatures
have risen faster than in any other era (the European Union).
Abrupt climate change has obvious effects, which are distinguished from changing
temperatures and rising sea levels resulting in the melting of polar glaciers as well as more
frequent occurrences of rainfall and flooding. These effects can bring about fundamental
changes in economic, social and environmental terms. In particular, they can be able to they
alter water resources, the integrity of ecosystems, public health, industry, agricultural
production as well as transport (Ministry of Environment & Energy).
The draft of the Intergovernmental Panel on Climate Change (IPCC) points out that climate
change, and in particular global warming, is causing far-reaching consequences affecting the
oceans, winds and rainfall in many regions of the world (International Panel on Climate
Change, 201) 9). The high intensity of extreme weather events combined with the increased
frequency results in overheating of the temperature of marine waters. In addition, a 2°C rise
in temperature will have a particularly significant impact on both the environment and people.
Efforts to eliminate the greenhouse effect by reducing carbon dioxide emissions and
greenhouse gas emissions will reduce the effects of climate change (European Council of the
European Union).
Global warming as well as the phenomenon of urbanisation contribute to warming in cities
and their surroundings, especially during events related to elevated temperatures, such as
heatwaves. Temperatures during the night are more affected by this phenomenon than the
temperatures of the day (International Panel on Climate Change, 2019).
Natural and technological disasters
A disaster is defined as any rapid or slow development of a natural or technological event in
marine, land and airspace which may cause far-reaching adverse effects on both man and the
natural or man-made environment. For a disaster to be included in the database of the United
Nations International Strategy for Disaster Reduction (EM-DAT) at least one of the following
criteria must be met: 10 or more dead, 100 people reported to have been infected, call for
international assistance and declaration of a state of emergency (EM-DAT, The International
Disaster Database for Research on the Epidemiology of Disasters - CRED).
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 48
Often in the literature, the terms destruction and danger are mistakenly confused and
therefore it is necessary to differentiate the two terms (Abhaya S. Prasad & Francescutti,
2017). The United Nations International Strategy for Disaster Reduction (2004) defines as a
risk any natural events or human behaviour that can have consequences for man, social
disturbance, destruction of property or deterioration of the environment. However, a disaster
is the possible consequence of a risk in which a community or a population cannot handle the
effects of the risk, given the resources at its disposal. Therefore, a risk can be an event that
will take place independently of human intervention, but the impact of a feed could be
reduced or even avoided (Abhaya S. Prasad & Francescutti, 2017).
Risks can be grouped into three categories: technological, physical and environmental.
Technological risks are characterised as industrial, nuclear and even pollution, while
environmental risks relate to the degradation of the environment permeating the ecosystem,
the environment, or natural resources, such as climate change. Natural hazards are events
that are the direct result of natural processes, while technological and environmental hazards
have come because of human behaviour (Lekkas, 2000).
The natural disaster is a serious, large-scale, adverse event that originated because of natural
processes of the biosphere and the earth (Sapountzaki & Dandoulaki, 2016). A natural disaster
can be a rapid, large or momentary collision between the natural environment and the social
environment. economic system (Lekkas, 2000). This results in loss of property and life,
problems in human health as well as injuries, damage to the natural and man-made
environment. At the same time, it can cause extensive economic and social losses, the size
and severity of which depend on adaptability, vulnerability, and the ability to recover (Bankoff
et al., 2004).
A technological disaster is defined as a major accident that occurs in a high-risk installation. It
is defined by the International Labour Organisation as "an incident such as a large emission,
fire or explosion resulting from uncontrolled developments during an industrial activity,
leading to serious a danger to man, immediate or delayed, inside or outside the installation,
and the environment, involving one or more dangerous substances' (International Labor
Organization, 1988).
Urban resilience and sustainable development
Urban resilience is defined as the carrying capacity of cities to operate in such a way that
people living and working in cities, especially the vulnerable and the poor, survive and thrive
regardless of the unexpected crises or even disasters they face (Index, City Resilience, 2014).
With the continuing increasing trend of urbanisation, cities are faced with a variety of acute
shocks resulting both from long-term pressures, such as the effects of climate change, and
from natural and technological disasters. As a result, they can cause incalculable effects on
people's health and safety, the economy, and the natural environment. As a result, they can
have incalculable effects on people's health and safety, the economy, and the natural
environment. As a result, they can have incalculable effects on people's health and safety, the
economy, and the natural environment. As a result, urban resilience becomes necessary,
without however being limited only to the traditional approach to the prevention and
management of risks, but also focusing on the creation of preventive and adaptive policies to
deal with any unexpected threat (Labaka et al., 2019).
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 49
The scale of urban risk is increasing, while at the same time it is becoming more unpredictable
due to the complexity of the city as well as the uncertainty associated with various risks. Urban
resilience helps to bridge the gap between disaster risk reduction, resilience to climate
change, and ensuring the well-being of society. One of the main objectives of urban resilience
is to improve the performance of a system for prevention and to address multiple risks (Index,
City Resilience, 2014).
The concept of sustainable development is defined as the form of development policy that
aims to meet the economic, social and environmental needs of society to ensure both short-
term and long-term prosperity (European Commission). Sustainable development must be
based on and respond to existing needs while at the same time ensuring the well-being of
future generations. The aim is not to degrade or alter the environment while contributing to
long-term economic growth (European Commission). On the other hand, the environment has
been sacrificed and a large number of natural resources have gradually been exhausted,
making sustainable development a major issue. It is therefore necessary to achieve it,
cooperation between the government of each country, its local government and non-
governmental organizations (Council for Sustainable Development).
The immediate aim of the Council of the Federation of Enterprises and Industries (SEV) for
sustainable development is that by 2050, 9 billion people will live in satisfactory living
conditions on the planet (Council for Sustainable Development). Today, humanity consumes
more than the earth can produce, so it is no longer possible to focus only on economic growth
and development. The burden on the environment, climate change, the increasing trend of
urbanisation, food shortages and social inequalities are some of the factors that threaten
humanity. However, businesses committed to sustainable development are a key factor in the
delineation of change, pointing to sustainability to other social partners such as governments
and local authorities. The axes of extroversion, competitiveness and innovation create jobs as
well as a cohesive society by developing a productive economy with respect for the
environment (Council for Sustainable Development).
Analysis of the existing situation of the Municipality of Elliniko - Argyroupolis
The union of the Municipality of Hellinikon (Municipal Community of Hellinikon) and the
Municipality of Argyroupoli (Municipal Community of Argyroupoli), which resulted from the
Kallikratis Programme in 2010, created the Municipality of Elliniko - Argyroupoli (Law
3852/2010 Government Gazette Α 87/7-6-2010). The Municipality of Elliniko - Argyroupoli
belongs to the Regional Unit of the Southern Sector of Athens, consisting of 51,356 permanent
residents, according to the census of the Hellenic Statistical Authority (ELSTAT). that took
place in 2011 and occupies an area equal to 15.4 sq.km. (Municipality of Elliniko Argyroupolis).
The altitude of the municipality corresponds to 56 meters and the climate is Mediterranean,
according to the Köppen scale classification: Csa (DB. City. com). It is located by the sea while
at the same time a part of it is located at the foot of mount Hymettus.
Examples of natural disasters in the Municipality of Elliniko - Argyroupoli
Various natural disasters have affected, on a small scale, the Municipality of Elliniko -
Argyroupoli in the last ten years, but no disaster related to a technological accident has been
recorded. Several fires have taken place in the Municipality of Elliniko - Argyroupoli but they
were small scale and were extinguished immediately without causing adverse effects on the
property or the environment and without human casualties. In May 2021, a small fire was
recorded in a forest area of Argyroupoli but thanks to the rapid response of the fire brigade,
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 50
it did not take a large area. Moreover, according to the official website of the municipality
another fire had broken out but was quickly noticed by the voluntary forest protection body
of the municipality. It is necessary to mention that there have been attempts at arson in forest
areas near the Municipality of Elliniko - Argyroupoli and several fires that broke out were
investigated and attributed to inflammatory actions (Municipality of Elliniko Argyroupoli).
In addition, the geographical position of Greece, which is located above the tectonic plates,
favors earthquakes. Specifically, in the Municipality of Elliniko - Argyroupoli took place an
earthquake of 2.6 on the Richter scale in 2020 and another earthquake of 5.1 on the Richter
scale in 2019. The consequences of the two earthquakes were not serious and did not cause
large-scale disasters. Thanks to the information and awareness of the citizens through the
official website of the municipality as well as the social media, there were no victims
(Municipality of Elliniko Argyroupoli).
Also, due to climate change, extreme phenomena have been observed, such as severe
weather, heat waves, heavy rainfall, and snowfall. The consequences of climate change may
affect and cause adverse effects even at a local level, due to the coastal area of the
Municipality of Elliniko - Argyroupoli. A possible impact of climate change is the rise of sea
levels, which can affect all residents and employees of the municipality and the sector that
will be affected at an average level is the building stock and materials (Giaourdimou, 2020).
Although the municipality of Elliniko - Argyroupoli is included with a percentage of 100%
within a water district in the catchment area of the Attica basin, a flood event has historically
been recorded but it was not significant and therefore, it has been characterized as a low-risk
flood zone according to the "Kallikratis" program. A river basin means "the land area from
which all rainfall and/or snowfall of a river is drained of all the rainfall and/or snowfall of an
area through the hydrographic network (successive streams, streams, rivers, and possibly
lakes) and is drained into the sea through the delta of a river" (Flood Risk Management Plan
of the River Basins of the Attica Water District, 2017).
Finally, the COVID-19 pandemic is a natural disaster that has been taking place on a global
level since the end of 2019 and has naturally affected at a local level the Municipality of Elliniko
- Argyroupoli in various aspects of people's daily lives and in areas such as public health,
building stock and tourism with a high level of risk, while sectors such as transport and energy
are affected at lower levels of risk. However, due to the complexity of the city, all sectors are
interrelated as the increase or decrease of one sector can negatively affect another sector
resulting in adverse effects both on a social, economic, and even environmental level
(Yaourdimou, 2020).
Civil protection operational plan
One of the main priorities and obligations of each municipality is the protection of human life,
property and the health of the citizens in the context of its social mission (Law 3013/02,
Government Gazette 102/A/1-5-2002). The purpose of any operational plan for Civil
Protection is to prevent and deal with possible natural or technological disasters through the
formation of a system of effective mobilization and preparation of competent services. the
Municipality of Elliniko - Argyroupoli and the stakeholders (Politis, 2018).
For the Civil Protection Plans of the Municipality of Elliniko-Argyroupoli to be effective, it is
necessary to prepare for emergency response, detailed planning, effective organization and
staffing, adequacy of material resources as well as integrated coordination of these
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 51
(Emergency Action Plan, 2018). Finally, it is necessary to meet the requirements of effective
and timely management of various risks, which should be based on prevention, preparedness,
response and finally recovery. One of the most basic planning principles in response to and
management of mass emergencies is coordination and excellent cooperation between the
competent bodies, with clear and specific roles, before, during and after the outbreak of a
disaster (Emergency action plan, 2018).
The Municipality of Elliniko Argyroupoli on its official website has published an updated plan
of actions for the organized evacuation of citizens for reasons of protection from impending
destruction due to forest fires in August 2020, which was undertaken by the Directorate of
Environment and Civil Protection (Plan for dealing with emergencies due to forest fires). In
addition, it has published another Operational Policy Plan Protection for the confrontation of
natural disasters, which contains all the necessary information for the immediate response to
forest fires, emergencies, earthquake and flood cases (Emergency Action Plan, 2018). In
addition, in the context of the implementation of a system of effective information and
prevention of the Directorate of Environment and Civil Protection has published a protection
guide under the name "Elli and Argyris learn about the fire, the earthquake, the flood" which
addresses in the form of comics a strong message to the students at the school community
(Directorate of Environment and Civil Protection).
In addition, the Municipality of Elliniko - Argyroupoli has made sure to publish on its official
page on social media, useful instructions as well as information on the self-protection of
citizens in cases such as severe weather conditions, heatwaves, fires as well as earthquakes.
daily based on the internet, thus making it more immediate and timelier to inform citizens as
well as to raise their awareness.
Finally, a major earthquake response exercise was carried out under the name "SEIZHON
2019", which included four seminars aiming at the readiness for rescue, the effectiveness of
the stakeholders involved as well as the optimization of their cooperation (Fire Brigade of
Greece, 2019).
It is necessary to mention at this point that the Municipality of Elliniko - Argyroupoli is a
model of the municipality. This is reflected by the fact that it was awarded in 2019 in the
framework of the annual bravo sustain and ability, dialogue and awards for its
multidimensional effort in the organization and execution of Civil Protection plans and
prevention measures for the Protection of the Natural Environment (Quality Net Foundation,
2019).
Sustainable urban mobility plan
A Sustainable Urban Mobility Plan is defined as the Strategic Mobility Plan which aims to meet
the needs for people's mobility by reducing the use of private cars and increasing travel
through more sustainable modes of transport. In addition, it aims to ensure a better quality
of life through the transport of goods to the urban and peri-urban fabric. It builds on existing
planning practices and includes all areas indirectly or directly involved in the scope of
employment of a sustainable urban mobility plan (Sustainable Urban Mobility Plan).
Sustainable urban mobility plans contribute to the sustainable development of urban areas
through the design of policies and actions to reduce air pollution, energy consumption, traffic
congestion, etc. (Municipality of Elliniko Argyroupoli).
Proceedings of the 5th Symposium on Agri-Tech Economics for Sustainable Futures 52
The Municipality of Elliniko - Argyroupoli, through the Integrated Sustainable Urban Mobility
Plan (SUMP), aims to ensure accessibility of services and jobs to all citizens, to improve both
the protection and safety of commuters. In addition, it contributes to the mitigation of air
pollution and noise, while increasing economic efficiency and result. the quality of the
transport of people and goods. In addition, it contributes to the improvement of the quality
and attractiveness of the urban environment (Sustainable Urban Mobility Plan of the
Municipality of Elliniko Argyroupoli). The SUMP of the Municipality of Elliniko - Argyroupoli
has as its primary objective the creation of a network of mild mobility roads that will operate
within the municipality but also in neighbouring municipalities to improve the movement of
residents. In particular, the aim is to reduce the problems found in the traffic network. More
specifically, it aims to increase mild forms of transport, such as the promotion of walking and
public transport, to reduce the use of private cars and the parking problems they entail. In
addition, as part of the implementation of the SUMP, a bicycle path has been built in
Argyroupoli to operate a single network of cycle paths in both municipal units (Municipality of
Elliniko-Argyroupoli, 2018).
The sustainable development of cities develops and raises the standard of living of the region.
The successful implementation of a SUMP is based on the bodies and their responsibilities to
be clear for the implementation of an action. The sustainable urban mobility plan of the
Municipality of Elliniko - Argyroupoli operates with a