Jump: Map | Indicators | User Guide
Many indicators have been considered during the process of conceptualizing and developing the Atlas. These indicators have been identified by the different stakeholders through multiple discussions entertained during the course of the project (more on the protocol in later sections). We selected a short list of 6 indicators that cover all key elements and at the same time allow us to keep the tool tractable and readable for users.
The number of future coal power plants (including those under construction and planned capacity) is an indicator of potential stranded assets. The presence of committed emissions has been long recognized as a key impediment to the enactment of stringent climate policy (Davis & Socolow, 2014). Stranded assets are defined as "those investments which are made but which, at some time prior to the end of their economic life (as assumed at the investment decision point), are no longer able to earn an economic return, as a result of changes in the market and regulatory environment." according to the definition by IEA World Energy Outlook 2019 (IEA, 2019). Coal power plants are the most problematic asset as they represent huge investments with large commitments in terms of resource exploitation, energy jobs and low energy price. For visibility and performance, only countries with more than 150 MW of future capacities are kept
Definition: Capacity of coal power generation currently under construction or in planning [MW]. Only units of 30MW or larger are considered
Source: CoalSwarm Global Coal Plant Tracker, January 2019 (Units 30 MW and larger). google doc
URL: CoalSwarm Global Coal Plant Tracker
Spatial resolution: Country
Filter: > 150 MW
Fossil fuel subsidies are increasing fossil fuel consumption, leading to higher global carbon emissions and, as a consequence raise the required level of climate change mitigation (Jewel et al., 2018) and represent a critical measure of the political strength of the fossil fuel sector in a given region (IISD, 2009). Moreover, the removal of fossil fuel subsidies would be beneficial in many aspects (reducing budget deficit, increasing economic growth) that would improve the feasibility of the implementation of climate policies (Hayer, 2017)
Definition: Fossil fuel subsidies in 2010 [USD2005/GJ]
Source: Jewell, Jessica, David McCollum, Johannes Emmerling, Christoph Bertram, David E. H. J. Gernaat, Volker Krey, Leonidas Paroussos, et al. “Limited Emission Reductions from Fuel Subsidy Removal except in Energy-Exporting Regions.” Nature 554, no. 7691 (February 2018): 229–33
URL: https://doi.org/10.1038/nature25467
Spatial resolution: Country
Filter: > 2 USD/G
The magnitude of low carbon investments is an indicator of how strong the commitments of the countries to reduce their carbon footprint in the energy supply sector should be. As mobilizing large sums of money can be challenging, this indicator represents a measure of the potential barriers within the financial domain. G20 countries have ‘reemphasized’ the previously agreed commitment of wealthy countries to jointly mobilize 100 billion dollars per year (during the period 2020-2025) for mitigation actions in developing countries. Considerably more capital would have to be mobilized in order to close the investment gap for a 2° C- or 1.5° C-consistent future (McCollum et al., 2018). High values of the indicator highlight regions where required investments are highest
Definition: Average investment in low-carbon technologies for the period 2020-2050 [Billions USD 2015/yr]
Source: David McCollum, et al. (2018) “Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals" Nature Energy volume 3, pages589–599 (2018)
URL: https://doi.org/10.1038/nature25467
Spatial resolution: 5 Global regions. The region definition follows the regional aggregation used in the SSP database (https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about#regiondefs)
Filter: no
Embedded emissions represent the carbon intensity in traded goods and they reflect a discrepancy in countries between consumption based and production based measures of emissions. The higher the dependence of a country on goods that are produced with large amount on emissions and then imported, the higher would be the implications on trade of climate change policies, indicating a potential impediment to their implementation
Definition: Residual emissions from import goods (GCB) in 2016 [MtCO2]
Source: Update from Peters, GP, Minx, JC, Weber, CL and Edenhofer, O 2011. Growth in emission transfers via international trade from 1990 to 2008. Proceedings of the National Academy of Sciences 108, 8903-8908. http://www.pnas.org/content/108/21/8903
URL: https://www.icos-cp.eu/GCP/2018
Spatial resolution: Country
Filter: no
Economic Restriction is the opposite of the “Economic freedom indicator” which is calculated by the Heritage Foundation. The latter is a composite indicator measuring the level of control citizenz exert on their own labour and property. Positive relationship has been found between civil freedoms (including business freedom) and a clean environment (Bernauer & Koubi, 2009). Additionally, Etsy and Porter (2005) found a positive correlation between competitiveness and environmental performance. In the Atlas, we report the indicator of Economic Restriction only countries for countries with a value of the index greater than 50
Definition: Indicator of Economic Restriction converted from the 2018 index of Economic Freedom (Indicator of Economic Restriction =100 – Economic Freedom) [0-100]
Source: The Heritage Foundation
URL: https://www.heritage.org/index/explore
Spatial resolution: Country
Filter: >50
School non-attendance is a key indicator of education. Education is a determinant of good governance and good governance, in turn, increases environmental performance (Epstein, 2006; Inglehart & Welzel, 2009). Education equality is also an indicator of governance performance (Andrijevic,2020). Finally, education is highly correlated to the propensity to support climate change policies. It has been found that globally education level tends to be the single strongest predictor of public awareness of climate change (Lee et al., 2015)
Although many indicators of education exist, we have chosen one of the most widely adopted, i.e. the school enrolment of girls at secondary school
Definition: Secondary school non-participation (secondary, female), Net absenteeism ratio, mean (2010-2017). Opposite of the school enrolment, expressed as a percentage [0-100]
Source: World Development Indicators. World Bank
URL: https://databank.worldbank.org/data/
Spatial resolution: Country
Filter: >33
Jump: Map | Indicators | User Guide
The following subsections provide a quick overview of the functionalities of the Atlas. The Atlas can be browsed using any modern browser that can understand JavaScript, but in order to enjoy all the features of the interface, we recommend the use of google chrome, or equivalent. The map is working with Firefox but some visual features are not available on this platform.
The main page is composed of different parts:
The exploration mode is activated from the beginning or when the user clicks on the menu item ‘Explore’. The following actions are possible:
About the bubbles: The bubble size is proportional to the value of the indicator for the given country or region. Values are normalized so that they are comparable across indicators. When an indicator is selected, a scaling legend is displayed at the bottom of the map along with the reference of the data source. Each indicator has a unique color. On the map, the bubbles are located at the centroid of the given region. More information can be seen if the user hovers the bubbles.
The user activates the mode Combination by clicking on the menu item ‘Combine’. In this mode, the user can select more than one indicator to be displayed on the map. The bubbles will aggregate while keeping their colour to highlight hotspot on the map for all the selected indicators.
We recommend not to use more than 3 indicators at the same time as it becomes difficult to interpret the indicators’ combination (however combining more than 3 indicators is possible in the interface). The size of the bubbles is automatically adjusted when the number of selected indicators is increasing.
Jump: Map | Indicators | User Guide
Andrijevic, Marina, Jesus Crespo Cuaresma, Raya Muttarak, and Carl-Friedrich Schleussner. “Governance in Socioeconomic Pathways and Its Role for Future Adaptive Capacity.” Nature Sustainability 3, no. 1 (January 2020): 35–41. https://doi.org/10.1038/s41893-019-0405-0.
Bernauer, Thomas, and Vally Koubi. “Effects of Political Institutions on Air Quality.” Ecological Economics 68, no. 5 (March 2009): 1355–65. https://doi.org/10.1016/j.ecolecon.2008.09.003
Davis, Steven J., and Robert H. Socolow. “Commitment Accounting of CO2emissions.” Environmental Research Letters 9, no. 8 (August 2014): 084018. https://doi.org/10.1088/1748-9326/9/8/084018
Epstein, D. L., Bates, R., Goldstone, J., Kristensen, I. & O’Halloran, S. Democratic transitions. Am. J. Pol. Sci. 50, 551–569 (2006)
Esty, Daniel C., and Michael E. Porter. “National Environmental Performance: An Empirical Analysis of Policy Results and Determinants.” Environment and Development Economics 10, no. 4 (August 2005): 391–434. https://doi.org/10.1017/S1355770X05002275
Hayer, Sarabjeet. “Fossil Fuel Subsidies”, European Parliament's Committee on Environment, Public Health and Food Safety European Union, 2017
Inglehart, R. & Welzel, C. How development leads to democracy: what we know about modernization today. Foreign Aff. 88, 33–48 (2009)
IISD, “The Politics of Fossil-Fuel Subsidies.” IISD, 2009. https://www.iisd.org/gsi/sites/default/files/politics_ffs.pdf
Jewell, Jessica, David McCollum, Johannes Emmerling, Christoph Bertram, David E. H. J. Gernaat, Volker Krey, Leonidas Paroussos, et al. “Limited Emission Reductions from Fuel Subsidy Removal except in Energy-Exporting Regions.” Nature 554, no. 7691 (February 2018): 229–33. https://doi.org/10.1038/nature25467
Lee, Tien Ming, Ezra M. Markowitz, Peter D. Howe, Chia-Ying Ko, and Anthony A. Leiserowitz. “Predictors of Public Climate Change Awareness and Risk Perception around the World.” Nature Climate Change 5, no. 11 (November 2015): 1014–20. https://doi.org/10.1038/nclimate2728
McCollum, David L., Wenji Zhou, Christoph Bertram, Harmen-Sytze de Boer, Valentina Bosetti, Sebastian Busch, Jacques Després, et al. “Energy Investment Needs for Fulfilling the Paris Agreement and Achieving the Sustainable Development Goals.” Nature Energy 3, no. 7 (July 2018): 589–99. https://doi.org/10.1038/s41560-018-0179-z
IEA (2019), "World Energy Outlook 2019", IEA, Paris https://www.iea.org/reports/world-energy-outlook-2019
Wong-Parodi, Gabrielle, and Benjamin H. Strauss. “Team Science for Science Communication.” Proceedings of the National Academy of Sciences 111, no. Supplement 4 (September 16, 2014): 13658–63.