Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
Global mismatch between
greenhouse gas emissions and the
burden of climate change
Glenn Althor1, James E. M. Watson1,2 & Richard A. Fuller3
Countries export much of the harm created by their greenhouse gas (GHG) emissions because the
Earth’s atmosphere intermixes globally. Yet, the extent to which this leads to inequity between GHG
emitters and those impacted by the resulting climate change depends on the distribution of climate
vulnerability. Here, we determine empirically the relationship between countries’ GHG emissions
and their vulnerability to negative eects of climate change. In line with the results of other studies,
we nd an enormous global inequality where 20 of the 36 highest emitting countries are among the
least vulnerable to negative impacts of future climate change. Conversely, 11 of the 17 countries
with low or moderate GHG emissions, are acutely vulnerable to negative impacts of climate change.
In 2010, only 28 (16%) countries had an equitable balance between emissions and vulnerability.
Moreover, future emissions scenarios show that this inequality will signicantly worsen by 2030. Many
countries are manifestly free riders causing others to bear a climate change burden, which acts as a
disincentive for them to mitigate their emissions. It is time that this persistent and worsening climate
inequity is resolved, and for the largest emitting countries to act on their commitment of common but
e current generation is the rst to feel the eects of anthropogenic climate change1,2. Despite their well-known
harmful impacts to the world’s climate system1,3, greenhouse gases (GHG) are deliberately emitted by countries
to drive economic growth and enhance human wellbeing4. Spatially localised environmental issues, such as city
air pollution5, may result from high GHG emissions, but the most damaging and long lasting consequence, that
of global climate change6, is not constrained within the border of the emitting country1. Rather, by polluting the
Earth’s atmosphere with GHG emissions through fossil fuel combustion, deforestation and agricultural activi-
ties, emitting countries are degrading the world’s climate system, a common resource shared by all biodiversity,
Because the impacts of GHG emissions can be felt beyond a country’s border, and the impacts of climate
change on countries are highly variable, there is potential for some emitters to contribute more or less to the
causes of climate change than is proportionate to their vulnerability to its eects9–11. is inequity has not gone
unnoticed in international climate negotiations or global reporting1,3. As far back as 1992, the United Nations
Framework Convention on Climate Change (UNFCCC) committed to the principle of “common but dierenti-
ated responsibilities”, in which countries have a common responsibility in reducing GHG emissions, but historic
emissions and dierences in current development levels mean that countries have dierent levels of emissions
reduction obligations9. Both of the previous IPCC Assessment Reports have acknowledged the inequity in
the causes and eects of climate change1,12 although operationalising the principle has proved dicult13. is
is primarily because developing and developed countries continue to disagree over the extent of each other’s
responsibilities13,14. One major impediment to resolving such debates is a poor quantitative understanding of the
magnitude of the global inequity in emissions and impacts. ‘Free rider’ countries contribute disproportionately to
global GHG emissions with only limited vulnerability to the eects of the resulting climate change, while ‘forced
rider’ countries are most vulnerable to climate change but have contributed little to its genesis15,16. is is an issue
of environmental equity on a truly global scale17.
1School of Geography, Planning and Environmental Management, University of Queensland, Queensland, 4072,
Australia. 2Wildlife Conservation Society, Global Conservation Program, 2300 Southern Boulevard, Bronx, NY 10460-
1068, USA. 3School of Biological Sciences, University of Queensland, Queensland, 4072, Australia. Correspondence
and requests for materials should be addressed to G.A. (email: email@example.com)
Received: 30 July 2015
Accepted: 30 December 2015
Published: 05 February 2016
Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
Here, we measure the current pattern of global climate change equity, and assess whether the situation will
improve or worsen by 2030, using data on GHG emissions17 and newly available national climate change vul-
nerability assessments18. We address the lack of a contemporary, qualitative assessment of global climate equity
that incorporates key variables. Previous studies have been limited to CO2 emissions datasets, omitting the most
potent and long lasting GHGs1,6,16, and used vulnerability variables that do not capture the complexity of climate
change threats, and cannot be forecasted. Here, we use the most recently available datasets based on comprehen-
sive national vulnerability assessments and comprehensive GHG emissions data to produce an easily replicable
snapshot of the relationship between countries’ GHG emissions and their vulnerability to the negative eects
of climate change17,18, and forecast this to 2030. We employ economic metrics, the Gini and Robin Hood coe-
cients19, to quantify the present level of equity in GHG emissions. Only through a proper empirical understanding
of the pattern of climate equity now, and how it will change in the near future, can signatories of the UNFCCC
make meaningful progress toward resolving the inequity in the burden of climate change impacts.
Greenhouse gas emissions are spread highly unevenly across the world’s countries (Fig.1), with the top ten GHG
emitting countries generating > 60% of total emissions, and three countries, China (21.1%), the United States
of America (14.1%) and India (5.2%) being by far the largest contributors. A Gini coecient of 80.9 indicated
extreme inequality in the distribution of emissions among countries, given that the index can only vary between
0 (perfectly even responsibility) and 100 (one country responsible for all emissions)19. A Robin Hood index of
64 indicated that 64% of GHG emissions would need to be redistributed to achieve an even distribution among
countries19. Vulnerability to the impacts of climate change was also unevenly spread among countries, with 17
countries acutely vulnerable to climate change impacts in 2010 (Fig.2). e majority of these were island coun-
tries located in the Atlantic, Pacic and Indian oceans (n = 7, 35.3%) and African countries (n = 8, 47%). By 2030
Figure 1. Global inequity in the responsibility for climate change and the burden of its impacts. (a) Climate
change equity for 2010. (b) Climate change equity for 2030. Countries with emissions in the highest quintile
and vulnerability in the lowest quintile are shown in dark red (the climate free riders), and those countries with
emissions in the lowest quintile and vulnerability in the highest quintile are shown in dark green (the climate
forced riders). Intermediate levels of equity are shown in graduating colours, with countries in yellow producing
GHG emissions concomitant with their vulnerability to the resulting climate change. Data decient countries
are shown as grey. Maps generated using ESRI ArcGIS36.
Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
the number of acutely vulnerable countries is predicted to rise dramatically (n = 62; Fig.2), and the majority of
these will again be island (n = 20, 32.8%) and African (n = 27, 44.2%) countries.
Countries least vulnerable to the impacts of climate change were generally the highest GHG emitters, and con-
versely those most vulnerable to climate change were the least responsible for its genesis. is inequity held true
for both 2010 and 2030, with a negative relationship between emissions and climate vulnerability in both years
(2010: ρ = − 0.4, n = 175, p = 0; 2030: ρ = − 0.37, n = 175, p = 0). e only exception is in 2030, where countries
acutely vulnerable to climate change will have slightly higher average emissions than those in the severe category
(2030: severe = 48.83 mtC O2e, acute = 103.13 mtCO2e).
In 2010, of the 179 countries assessed, 28 (15.6%) were in the same quintile for GHG emissions and vulnera-
bility to the negative impacts of climate change. is indicates that their vulnerability to climate change approx-
imately matched their relative contribution to its genesis (Fig.1). Ninety countries (50.3%) had GHG emissions
in a higher quintile than their 2010 climate vulnerability, and 20 (11.2%) countries were free riders, with GHG
emissions in the highest quintile and climate vulnerability in the lowest quintile (Fig.1; see Supplementary Table
S4 online). Sixty-one (34%) countries had GHG emissions in a lower quintile than their climate vulnerability, and
six (3.4%) countries were forced riders, with GHG emissions in the lowest quintile and climate vulnerability in
the highest quintile (Comoros, Gambia, Guinea-Bissau, São Tomé and Príncipe, Solomon Islands and Vanuatu;
see Supplementary Table S4 online).
By 2030, climate change inequity will rise further, with an increase in the proportion of countries that are
forced riders (n = 20; 11.2%), but fewer free riders (n = 16; 8.9%) and equitable countries (n = 23; 12.8%; see
Supplementary Table S4 online). Free riders are typically located in the world’s sub-tropical and temperate
regions, while forced riders are frequently located in tropical regions (Fig.1).
Greenhouse gas emissions were positively correlated with GDP (2010: ρ = 0.84, n = 175, p = 0; Fig.2c), while
climate vulnerability declined with increasing GDP (2010: ρ = − 0.69, n = 175, p = 0; 2030: ρ = − 0.65, n = 175,
p = 0; Fig.2d). Our analysis considers the absolute contribution of each country to climate change, but we also
examined climate change equity in per capita terms to provide a more complete picture of emissions responsi-
bilities. e patterns were broadly similar, with, for example, Australia, Russia and the United States of America
remaining free riders (see Supplementary Fig. S3 online). However, several populous major emitters (e.g. United
Kingdom, China, and Brazil) were no longer categorised as free riders.
Climate change inequity is globally pervasive, and correlated with economic output. Some countries, such as
China and the United States of America, are in a win-win position of achieving economic growth through fossil
fuel use with few consequences from the resulting climate change, while many other, mostly Island and African,
Figure 2. Vulnerability to climate change, mean GHG emissions, and mean GDP. (a) Number of countries
in each climate change vulnerability category, derived from DARA vulnerability data18, for 2010 (blue bars) and
2030 (green bars). (b) Mean GHG emissions for 2010, derived from CAIT GHG emissions data17, shown in CO2
equivalent units and climate vulnerability categories for 2010 (blue bars, with standard error) and 2030 (green
bars, with standard error). (c) GDP shown in current US$ (in billions), derived from the World Bank GDP 2010
data28, and 2010 GHG emissions. (d) Mean GDP for 2010 shown in current US$ (in billions) and climate change
vulnerability for 2010 (blue bars, with standard error) and 2030 (green bars, with standard error).
Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
countries suer low economic growth and severe, negative climate change impacts (see Supplementary Table S4
online). e beneciaries of this climate inequity have few incentives to meaningfully reduce or halt their GHG
emissions. Despite many of the broad issues around climate equity being well known1, well-funded global mech-
anisms that are being implemented still do not exist. is has serious consequences for our ability to slow the rate
of climate change, and reduce the wellbeing implications for forced rider countries.
ere are several global policy frameworks currently being debated that could address elements of the prob-
lem. e Paris Agreement20, secured at the 21st UNFCCC Conference of the Parties (COP21), for example, sets
an ambitious target of limiting global warming to 1.5°C above preindustrial levels. However, the 160 indica-
tive nationally determined contributions (INDCs) pledges submitted by signatories to the UNFCCC prior to
COP2121, indicate that current targets for GHG emissions are unlikely to limit warming to below 2°C22 With
no binding agreement established at COP21 for INDCs, there is no clear indication of how successful the Paris
Agreement will be20. Addressing GHG emissions is clearly an important rst step in ensuring the burden of cli-
mate change is not amplied in the future. However, the historic commitment to GHG emissions reduction by
key free riders has been slow. Only 50 countries ratied the previous Doha Amendment to the Kyoto protocol,
which did not include key free riders such as the United States and Russia23. Furthermore, some countries have
actually backtracked on their commitments to emissions reductions (e.g. Canada and Australia)24,25.
Likewise, the Paris Agreement calls for urgent and adequate nancing of US$100 billion per year by 2020 for
climate mitigation and adaptation through the Financial Mechanism of the Convention (FMC)20. However, there
is no legally binding mechanism under which parties are responsible for providing this funding. History suggests
such funding goals are not always met. For example, the Green Climate Fund (GCF) was established in 2010
under the UNFCCC to mobilise funding support for the least developed countries that are most vulnerable to
climate change, yet it remains poorly funded, with only US$10.2 billion received in pledges by November 201526.
Addressing these issues around climate funding will play a critical role in addressing climate inequity27.
It is clear climate change inequity must be addressed. If the commitment to the principle of common but dieren-
tiated responsibilities that was widely accepted early on in the UNFCCC is to be acted upon, member states now
need to do much more to hold climate free riders to account. To ensure equitable outcomes from climate negotia-
tions, there needs to be a meaningful mobilization of policies, such as the Paris Agreement, that achieve national
level emissions reductions, and to ensure the vulnerable forced-rider countries are able to adapt rapidly to climate
change. e provisioning of these policy mechanisms will require a distribution of resources and responsibilities
and we believe our results provide one way to understand where these responsibilities lie. e Paris Agreement
may be a signicant step forward in global climate negotiations. However, as the Agreement’s key policies are yet
to be realized, member states have both an exceptional opportunity and a moral impetus to use these results to
address climate change equity in a meaningful manner.
We quantied climate change equity, dened as the distribution of climate change benets and burdens, using
data from two publicly available datasets and national GDP data. National level data sets suer from some weak-
nesses such as a lack of accounting for sub-national variability and scaling. Nonetheless, they are still highly useful
as global metrics as they provide aggregated assessments at the national level, which is the most meaningful for
international policy negotiations.
We extracted data on national vulnerability to the negative impacts of climate change from DARA’s Climate
Vulnerability Monitor (CVM)18. e CVM uses 22 climate vulnerability indicators across four impact areas
(Environmental Disasters, Habitat Change, Health Impact, and Industry Stress) to evaluate the vulnerability of
184 countries to climate change impacts for the years 2010 and 2030. Each of the 22 indicators is individually
aggregated from various data sources and models and then combined to determine a country’s overall climate
vulnerability, measured by impact to share of GDP and mortality (as these impacts are comparable across the
wide range of countries). e CVM calculates vulnerability projections for 2030 using human population growth,
mortality and GDP predictions. e CVM uses ve vulnerability categories (low, medium, high, severe and acute)
which are determined using a mean absolute standard deviation method18. e CVM categories do not of course
capture the full complexity of national climate vulnerability, as capturing this would require an impractical degree
of data. However, we consider the 22 indicators used by the CVM as capturing a high enough level of complexity
to provide a meaningful approximation of national vulnerability.
Data on GHG emissions (by countries) were exported from the World Resource Institute’s (WRI) Climate
Analysis Indicators Tool (CAIT)17, a database of national and international GHG emissions derived from multiple
sources. e CAIT data set compiles data for the six main GHG gasses (carbon dioxide (CO2), methane (CH4),
nitrous oxide (N2O), hydrouorocarbons (HFCs), peruorocarbons (PFCs) and sulfur hexauoride (SF6)) from
185 countries over the period from 1990–2012. We used the 2010 data for this study to match the CVM vulner-
ability data. e WRI compiled GHG data from UNFCCC reports and complemented with data from several
NGO sources17, including emissions data from six major sectors (Land Use Change & Forestry, Energy, Industrial
Processes, Agriculture, Waste, and International Bunkers) and several subsectors. e CAIT data set reports at
the national level, however we extrapolated per capita emissions results by dividing data by 2010 and 2030 popu-
lation data from the World Bank28 (see Supplementary Table S4 online).
We excluded the ten countries (Cook Islands, Federated States of Micronesia, Marshall Islands, Montenegro,
Nauru, Niue, Saint Kitts & Nevis, Serbia, Somalia and Taiwan) with data missing in any dataset, and 179 remained
for analysis. In addition, there were also insucient data available for many of the world’s island and archipe-
lagic countries. Given the negligible GHG emissions and high climate change vulnerability of such countries, the
majority are highly likely to qualify as climate forced riders29,30 and as such, we expect that climate forced rider
Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
countries are likely underrepresented in our results. National GDP (measured in Current US$) was extracted
from the World Bank Group28, who measure GDP as the gross value of all resident producers in an economy plus
We created a Lorenz curve to represent the variation of GHG emissions among countries using the CAIT data-
set, and calculated the Gini index to measure inequity in GHG emissions among countries, and the Robin hood
index to measure how much of the total global emissions would have to be redistributed to achieve equity among
countries (see Supplementary Fig. S2 online).
We compared the CAIT GHG data and the CVM vulnerability data both in 2010 and 2030 to assess whether
the most heavily polluting countries were also those least vulnerable to the negative eects of climate change. We
divided the CAIT GHG emissions into quintiles, matching the CVM data, to enhance comparability between the
datasets and enable visualisation of climate equity in the recent past (2010) and near future (2030). We placed
the emissions quintiles on a scale between the highest (acute emissions) and the lowest (low emissions) emitting
countries. We also tested the correlations between GHG emissions and GDP against vulnerability to climate
change by treating vulnerability categories as ordinal data and undertaking spearman’s rho tests using R statistical
soware31. R has a computational limitation for p-values lower than 2.2e-16, as such, where values this small
were reported we wrote “p = 0”. Additionally, we counted countries in each CVM category and compared them
between each time period.
In common with other studies of inequity in climate change32, we used terminology from the economics lit-
erature to dene ‘free riders’ and ‘forced riders’33, recognising that a strict denition of these terms oen applies
only to situations where one agent’s use of a resource does not directly incur a cost to another agent. We dene
climate free riders as those countries in the ‘acute’ GHG emissions quintile and the ‘low’ vulnerability category,
as they disproportionately receive benets from climate change (via the national wellbeing generated by GHG
emissions) but pay few costs in the sense they are the least vulnerable to negative climate change eects34,35.
Conversely, we dene climate forced riders as those countries that fall within the ‘acute’ vulnerability category and
the ‘low’ GHG emissions quintile, as they are the most susceptible to the negative consequences of climate change
but receive the least benets. ose countries that we dene as equitable, fall in the same emissions quintile and
vulnerability category (for example, low emissions quintile, low vulnerability category), as their emissions benets
are concomitant with their climate change burden.
1. Ipcc. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Woring
Group II to the Fih Assessment eport of the Intergovernmental Panel on Climate Change [Field, C. B., V. . Barros, D. J. Doen, .
J. Mach, M. D. Mastrandrea, T. E. Bilir, M. Chatterjee, . L. Ebi, Y. O.. Estrada, . C. Genova, B. Girma, E. S. issel, A. N. Levy, S.
MacCracen, P. . Mastrandrea, and L. L. White (eds.)]. (Cambridge University Press, 2014).
2. Ipcc. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: egional Aspects. Contribution of Woring Group II to the
Fifth Assessment eport of the Intergovernmental Panel on Climate Change [Barros, V. ., C. B. Field, D. J. Doen, M. D.
Mastrandrea, . J. Mach, T. E. Bilir, M. Chatterjee, . L. Ebi, Y. O. Estrada, . C. Genova, B. Girma, E. S. issel, A. N. Levy, S.
MacCracen, P. . Mastrandrea & L. L. White (eds.)]. (Cambridge University Press, 2014).
3. United Nations Framewor Convention on Climate Change. Text of the Convention. (United Nations Framewor Convention on
Climate Change, 1992).
4. Jorgenson, A. . Economic development and the carbon intensity of human well-being. Nature Clim. Change 4, 186–189 (2014).
5. Sheehan, P., Cheng, E., English, A. & Sun, F. China’s response to the air pollution shoc. Nature Clim. Change 4, 306–309 (2014).
6. Montza, S. A., Dlugoency, E. J. & Butler, J. H. Non-CO2 greenhouse gases and climate change. Nature 476, 43–50 (2011).
7. Betts, . Comparing apples with oranges. Nature eports Climate Change 2, 7–8, doi: 10.1038/climate.2007.74 (2008).
8. Stocer, B. D. et al. Multiple greenhouse-gas feedbacs from the land biosphere under future climate change scenarios. Nature Clim.
Change 3, 666–672 (2013).
9. Cazorla, M. & Toman, M. in Climate Change Economics and Policy: An FF Anthology Ch. 23, 235 (FF Press, 2001).
10. jellstrom, T., ovats, . S., Lloyd, S. J., Holt, T. & Tol, . S. J. e Direct Imp act of Climate Change on egional Labor Productivity.
Arch. Environ. Occup. Health 64, 217–227 (2009).
11. Trenberth, . Changes in precipitation with climate change. Climate esearch 47, 123–138 (2011).
12. Ipcc. Climate Change 2007: Impacts, Adaptation and Vulnerability : Woring Group ii Contribution to the Fourth Assessment eport
of the Ipcc [M. L. Parry, O. F. Canziani, J. P. Palutiof, P. J. Van Der Linden & C. E. Hanson (Eds)]. (Cambridge University Press,
13. Ostrom, E. A polycentric approach for coping with climate change. Ann. Econ. Finance 15, 71–108 (2014).
14. Cole, D. H. Advantages of a polycentric approach to climate change policy. Nature Clim. Change 5, 114–118 (2015).
15. ao, N. D. International and intranational equity in sharing climate change mitigation burdens. Int. Environ. Agreem.-P. 14, 129–146
16. Füssel, H.-M. How inequitable is the global distribution of responsibility, capability, and vulnerability to climate change: A
comprehensive indicator-based assessment. Global Environmental Change 20, 597–611 (2010).
17. World esources Institute, Climate Analysis Indicators Tool: WI’s Climate Data Explorer. (2014) Available at: http://cait.wri.org/
historic. (Date of access: 31/05/2015).
18. DAA. Methodological Documentation for the Climate Vulnerability Monitor. (DAA, 2012).
19. Coulter, P. B. Measuring Inequality: A Methodological Handboo. (Westview Press, 1989).
20. UNFCCC. Conference of the Parties to the United Nations Framewor Convention on Climate Change. (UNFCCC, 2015).
21. UNFCCC, INDCs as communicated by Parties. (2015) Available at: http://www4.unfccc.int/submissions/indc/Submission%20Pages/
submissions.aspx. (Date of access:) 17/12/15).
22. Jacson, . B. et al. eaching pea emissions. Nature Clim. Change. Advance online publication, (2015). Available at: http://www.
nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2892.html. (Date of access: 17/12/2015)
23. Feete, H. et al. Analysis of Current Greenhouse Gas Emission Trends. (Climate Analytics, 2013).
24. Pizer, W. A. & Yates, A. J. Terminating lins between emission trading programs. J Environ Econ Manag 71, 142–159 (2015).
25. Harrison, . A Tale of Two Taxes: e Fate of Environmental Tax eform in Canada. eview of Policy esearch 29, 383–407 (2012).
26. Green Climate Fund, Bacground. (2015) Available at: http://www.gcfund.org/about/the-fund.html. (Date of access: 02/11/2015).
27. Picering, J., Jotzo, F. & Wood, P. J. Splitting the dierence: can limited coordination achieve a fair distribution of the global climate
nancing eort ? Environ Polit 15, 4 (2015).
28. World Ban Group, World DataBan. (2015) Available at: http://databan.worldban.org/data/views/reports/tableview.aspx. (Date
of access: 31/05/2015).
Scientific RepoRts | 6:20281 | DOI: 10.1038/srep20281
29. Nurse, L. A. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: egional Aspects. Contribution of Woring
Group II to the Fih Assessment eport of the Intergovernmental Panel of Climate Change (eds V. . Barros et al..) Ch. 29, 1613–1654
(Cambridge University Press, 2014).
30. Widlansy, M. J. et al. Changes in South Pacic rainfall bands in a warming climate. Nature Clim. Change 3, 417–423 (2013).
31. . Core Team (2013). : A language and environment for statistical computing. Foundation for Statistical Computing, Vienna,
Austria. UL http://www.-project.org/.
32. Otto, F. E. L., Frame, D. J., Otto, A. & Allen, M. . Embracing uncertainty in climate change policy. Nature Clim. Change 5, 917–920
33. Ahnlid, A. Free or Forced iders ? : Small States in the International Political Economy: e Example of Sweden. Cooperation and
Conict 27, 241–276 (1992).
34. eohane, . O. e Global Politics of Climate Change: Challenge for Political Science. PS: Political Science & Politics 48, 19–26
35. ennedy, M. & Basu, B. An analysis of the climate change architecture. enewable and Sustainable Energy eviews 34, 185–193
36. ESI (2011). ArcGIS Destop. Environment al Systems esearch Institute, edlands, CA. UL http://www.arcgis.com/.
G.A., J.E.M.W. and R.A.F. designed the analysis. G.A. performed the analysis and analysed the results. G.A.,
J.E.M.W. and R.A.F. wrote the paper.
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing nancial interests: e authors declare no competing nancial interests.
How to cite this article: Althor, G. et al. Global mismatch between greenhouse gas emissions and the burden of
climate change. Sci. Rep. 6, 20281; doi: 10.1038/srep20281 (2016).
is work is licensed under a Creative Commons Attribution 4.0 International License. e images
or other third party material in this article are included in the article’s Creative Commons license,
unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license,
users will need to obtain permission from the license holder to reproduce the material. To view a copy of this
license, visit http://creativecommons.org/licenses/by/4.0/