IndicatorName: Employment by sector and gender (% of total) - Services - Male

Longdefinition: Employment of Males within Services is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


IndicatorName: Employment by sector and gender (% of total) - Transport & Communication - Female

License_Type: CC BY-4.0

Longdefinition: Employment of Females within Transport & Communication is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.

Source: Global Jobs Indicators Database, The World Bank. Available at: https://databank.worldbank.org/source/global-jobs-indicators-database-(join)

Topic: Country profile

Unitofmeasure: % of total


IndicatorName: Employment by sector and gender (% of total) - Transport & Communication - Male

Longdefinition: Employment of Males within Transport & Communication is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


IndicatorName: Food GHG emissions by system stage (Share of total) - Consumption

Longdefinition: Food GHG emissions disaggregated by system stage are generated from EDGAR-FOOD, a global emission inventory of GHGs from the food systems. EDGAR-FOOD has been developed to aid the understanding of the activities underlying the energy demand and use, agriculture and land use change emissions associated with the production, distribution, consumption and disposal of food through the various stages and sectors of the composite global food system. These data were complemented with data from the FAOSTAT database on GHG emissions from land use related to agriculture (FAO, 2020). EDGAR-FOOD represents the first database consistently covering each stage of the food chain for all countries with yearly frequency for the period 1990-2015. Details regarding the methodology applied are available in Crippa et al. (2021).

Source: Crippa, M., Solazzo, E., Guizzardi, D., Monforti-Ferrario, F., Tubiello, F.N. and Leip, A. EDGAR-FOOD data. Figshare, doi:10.6084/m9.figshare.13476666 (2021).

Topic: Mitigation


IndicatorName: Food GHG emissions by system stage (Share of total) - End_of_Life


IndicatorName: Food GHG emissions by system stage (Share of total) - LULUC (Production)


IndicatorName: Food GHG emissions by system stage (Share of total) - Packaging


IndicatorName: Food GHG emissions by system stage (Share of total) - Production


IndicatorName: Food GHG emissions by system stage (Share of total) - Processing


IndicatorName: Food GHG emissions by system stage (Share of total) - Retail


IndicatorName: Food GHG emissions by system stage (Share of total) - Transport


IndicatorName: Population exposed to floods (share of population below 5.5$)

Longdefinition: Share of population that falls into the defined poverty threshold of $5.50 (consumption per day) that is exposed to floods within a country

Source: Rentschler, Jun; Salhab, Melda. 2020. People in Harm's Way : Flood Exposure and Poverty in 189 Countries. Policy Research Working Paper;No. 9447. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/34655 License: CC BY 3.0 IGO.

Topic: Adaptation

Unitofmeasure: % of population


IndicatorName: Population exposed to floods (share of total population)

Longdefinition: Share of total population that is exposed to floods within a country


IndicatorName: Share of animal products in food supply (kcal/capita/day)

Longdefinition: Animal products supply is taken from New Food Balances (domain), Food Supply (element) of the Food Balance Sheet (FAOSTAT). FAOSTAT Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

Source: FAOSTAT. Available at: http://www.fao.org/faostat/en/#data

Unitofmeasure: kcal/capita/day


IndicatorName: Share of vegetal products in food supply (kcal/capita/day)

Longdefinition: Vegetal supply is taken from New Food Balances (domain), Food Supply (element) of the Food Balance Sheet (FAOSTAT). FAOSTAT Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


IndicatorName: Freight volume by mode (billion tons-km) - Air transport

Longdefinition: This indicator presents the volume of freight attributable to air transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)

Source: UN Open Data Hub. Available at: https://unstats-undesa.opendata.arcgis.com/

Unitofmeasure: billion tons-km


IndicatorName: Freight volume by mode (billion tons-km) - Inland waterway transport

Longdefinition: This indicator presents the volume of freight attributable to inland waterway transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


IndicatorName: Freight volume by mode (billion tons-km) - Rail transport

Longdefinition: This indicator presents the volume of freight attributable to rail transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


IndicatorName: Freight volume by mode (billion tons-km) - Road transport

Longdefinition: This indicator presents the volume of freight attributable to road transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


IndicatorName: Per capita food supply (kcal/cap/day)

Longdefinition: Per capita food supply is taken from New Food Balances (domain), Food Supply (element) of the Food Balance Sheet (FAOSTAT). FAOSTAT Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Cancelled

Longdefinition: Gas pipeline capacity (barrels of oil equivalent per day), by capacity, is generated from the Global Fossil Infrastructure Tracker (GFIT). The GFIT is an information resource on fossil fuel infrastructure projects and their development. Currently, the GFIT includes all global LNG import terminals and export terminals, and all global oil and gas transmission pipelines over a pre-determined size threshold. The Tracker organizes information in both map and table format. The interactive map format allows users to geographically visualize pipeline routes and terminal locations, while the table format allows users to access additional data points on each project. Both the map and table provide menu-based data filtering options as well as links to further information in project-specific wiki pages housed on GEM.wiki. GFIT was accessed in July 2021 to generate this data.

Source: Global Fossil Infrastructure Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-fossil-infrastructure-tracker/

Unitofmeasure: barrels of oil equivalent per day


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Construction


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - In Development (Proposed + Construction)


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Mothballed


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Operating


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Proposed


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Retired


IndicatorName: Gas pipeline capacity by project status (barrels of oil equivalent per day) - Shelved


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Agriculture

Longdefinition: Agriculture sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.

Source: Climate Watch. 2020. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org.

Unitofmeasure: Mt CO2 eq


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Bunker Fuels

Longdefinition: Bunker fuels sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Building

Longdefinition: Building sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Electricity/Heat

Longdefinition: Electricity and heat sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Total excluding LUCF

Longdefinition: Total greenhouse gas emissions (excluding LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Energy

Longdefinition: Energy sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Fugitive Emissions

Longdefinition: Fugitive sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Total including LUCF

Longdefinition: Total greenhouse gas emissions (including LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Industrial Processes

Longdefinition: Industrial Processes sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Land-Use Change and Forestry

Longdefinition: Land-Use Change and Forestry sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Manufacturing/Construction

Longdefinition: Manufacturing and construction sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Other Fuel Combustion

Longdefinition: Other fuel combustion sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Transportation

Longdefinition: Transportation sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total GHG emissions by sector (Mt CO2 eq) - Waste

Longdefinition: Waste sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: GHG emissions from food systems, by gas (Mt CO2 eq) - Methane

Longdefinition: GHG emissions from food systems disaggregated by gas are generated from EDGAR-FOOD, a global emission inventory of GHGs from the food systems. EDGAR-FOOD has been developed to aid the understanding of the activities underlying the energy demand and use, agriculture and land use change emissions associated with the production, distribution, consumption and disposal of food through the various stages and sectors of the composite global food system. These data were complemented with data from the FAOSTAT database on GHG emissions from land use related to agriculture (FAO, 2020). EDGAR-FOOD represents the first database consistently covering each stage of the food chain for all countries with yearly frequency for the period 1990-2015. Details regarding the methodology applied are available in Crippa et al. (2021).


IndicatorName: GHG emissions from food systems, by gas (Mt CO2 eq) - CO2


IndicatorName: GHG emissions from food systems, by gas (Mt CO2 eq) - F-gases


IndicatorName: GHG emissions from food systems, by gas (Mt CO2 eq) - N2O


IndicatorName: GHG growth (annual %)

Longdefinition: Greenhouse gas emissions growth is generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.

Unitofmeasure: annual %


IndicatorName: Macro drivers of GHG emissions growth in the period 2012-2018 - Emission Intensity of GDP (contribution to total growth, %)

Longdefinition: Data reflects the impact of the emissions intensity of GDP (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.

Unitofmeasure: Percent


IndicatorName: Macro drivers of GHG emissions growth in the period 2012-2018 - GDP per capita (contribution to total growth, %)

Longdefinition: Data reflects the impact of GDP-per capita (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Macro drivers of GHG emissions growth in the period 2012-2018 - Population (contribution to total growth, %)

Longdefinition: Data reflects the impact of population (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Per capita GHG emissions (tons/capita)

Longdefinition: Per capita greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.

Unitofmeasure: tons/capita


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Agriculture (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Agriculture sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Building (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Building sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Electricity/Heat (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Electricity and Heat sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Fugitive Emissions (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Fugitive Emissions sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Industrial Processes (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Industrial Processes sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Land-Use Change and Forestry (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Land-Use Change and Forestry sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Manufacturing/Construction (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Manufacturing and Construction sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Other Fuel Combustion (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Other Fuel Combustion sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Transportation (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Transportation sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Sectoral drivers of GHG emissions growth in the period 2012-2018 - Waste (contribution to total growth, %)

Longdefinition: Data reflects the aggregate contribution of the Waste sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Total sovereign green bonds issuance (billion US$)

Longdefinition: Sovereign green bond issuance is disaggregated from Green Bond Issuances by Type of Issuer data. Green Bonds are created to fund projects that have positive environmental and/or climate benefits. Note: While green finance indicators may cover more than climate finance (i.e. to include environmental issues at large) they do provide a good proxy for the greening of the finance system in the country. Countries that rank well on these indicators are more likely to mobilize green finance to facilitate their climate transition.

Source: IMF Climate Change Dashboard. Sources:  Refinitiv; Country authorities; IMF staff calculations.

Topic: Managing the transition

Unitofmeasure: billion US$


IndicatorName: Emission Totals - Indirect emissions (N2O) - AFOLU

License_Type: CC BY-3.0

Longdefinition:
The FAOSTAT domain Emissions Totals summarizes the greenhouse gas (GHG) emissions generated from agriculture and forest land. They consist of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) emissions from crop and livestock activities, forest management and include land use and land use change processes. Data are computed at Tier 1 of the IPCC Guidelines for National greenhouse gas (GHG) Inventories (IPCC, 1996; 1997; 2000; 2002; 2006; 2014). Estimates are available by country, with global coverage for the period 1961–2019 with projections for 2030 and 2050 for some categories of emissions or 1990–2019 for others. The database is updated annually.

The FAOSTAT domain Emissions Totals disseminates information estimates of CH4, N2O and CO2 emissions/removals and their aggregates in CO2eq in units of kilotonnes (kt, or 106 kg). The latter are computed by using the IPCC Fifth Assessment report global warming potentials, AR5 (IPCC, 2014).

Source: FAO, FAOSTAT Climate Change, Emissions Totals, http://www.fao.org/faostat/en/#data/GT.

Unitofmeasure: kilotonnes


IndicatorName: Emission Totals - Indirect emissions (N2O) - Agricultural Soils


IndicatorName: Emission Totals - Indirect emissions (N2O) - Crop Residues


IndicatorName: Emission Totals - Indirect emissions (N2O) - Emissions on agricultural land


IndicatorName: Emission Totals - Indirect emissions (N2O) - Farm-gate emissions


IndicatorName: Emission Totals - Indirect emissions (N2O) - IPCC Agriculture


IndicatorName: Emission Totals - Indirect emissions (N2O) - Manure left on Pasture


IndicatorName: Emission Totals - Indirect emissions (N2O) - Manure applied to Soils


IndicatorName: Emission Totals - Indirect emissions (N2O) - Synthetic Fertilizers


IndicatorName: Annual investment needs for coastal protection, by risk strategy (% of GDP) - low risk tolerance

Longdefinition: Data reflects the cost of a risk taking strategy that adopts an ambititious low-risk strategy. This is discussed in Policy Note 5 of the Beyond the Gap report.

Source: Rozenberg, Julie; Fay, Marianne. 2019. Beyond the Gap : How Countries Can Afford the Infrastructure They Need while Protecting the Planet. Sustainable Infrastructure;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/31291 License: CC BY 3.0 IGO

Unitofmeasure: % of GDP


IndicatorName: Annual investment needs for coastal protection, by risk strategy (% of GDP) - constant relative flood risk

Longdefinition: Data reflects the cost of a risk taking strategy that keeps the risk relative to GDP constant. This is discussed in Policy Note 5 of the Beyond the Gap report.


IndicatorName: Annual investment needs for coastal protection, by risk strategy (% of GDP) - optimal protection

Longdefinition: Data reflects the level of spending in protection that minimizes the cost of floods, including the prevention of expenditure and damages. This is discussed in Policy Note 5 of the Beyond the Gap report.


IndicatorName: Informal employment by sector and gender (% of total) - Agriculture, forestry and fishing - Female

Longdefinition: This indicator presents the share of agriculture (female) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Informal employment by sector and gender (% of total) - Agriculture, forestry and fishing - Male

Longdefinition: This indicator presents the share of agriculture (male) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Informal employment by sector and gender (% of total) - Non-agriculture - Female

Longdefinition: This indicator presents the share of non-agriculture (female) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Informal employment by sector and gender (% of total) - Non-agriculture - Male

Longdefinition: This indicator presents the share of non-agriculture (male) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Informal employment by sector and gender (% of total) - No breakdown - Female

Longdefinition: This indicator presents the share of employment that had no-breakdown as either non-agricultural or agricultural (female), which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Informal employment by sector and gender (% of total) - No breakdown - Male

Longdefinition: This indicator presents the share of employment that had no-breakdown as either non-agricultural or agricultural (male), which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


IndicatorName: Proportion of freshwater key biodiversity areas (KBAs) covered by protected areas (%)

Longdefinition: This indicator presents the proportion of freshwater key biodiversity areas (KBAs) covered by protected areas. Data is taken from the United Nations Sustainable Goals, representing Indicator 15.1.2: Average proportion of Freshwater Key Biodiversity Areas (KBAs) covered by protected areas (percent).


IndicatorName: Proportion of terrestrial key biodiversity areas (KBAs) covered by protected areas (%)

Longdefinition: This indicator presents the proportion of terrestrial key biodiversity areas (KBAs) covered by protected areas. Data is taken from the United Nations Sustainable Goals, representing Indicator 15.1.2: Average proportion of Terrestrial Key Biodiversity Areas (KBAs) covered by protected areas (percent).


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Agriculture

Longdefinition: Agriculture sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Total excluding LUCF

Longdefinition: Total non-CO2 emissions (excluding LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Energy

Longdefinition: Energy sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Fugitive Emissions

Longdefinition: Fugitive sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Total including LUCF

Longdefinition: Total non-CO2 emissions (including LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Industrial Processes

Longdefinition: Industrial Processes sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Land-Use Change and Forestry

Longdefinition: Land-Use Change and Forestry sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Other Fuel Combustion

Longdefinition: Other fuel combustion sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Non-CO2 GHG emissions by sector (Mt CO2 eq) - Waste

Longdefinition: Waste sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


IndicatorName: Net food imports by crop - Barley

Longdefinition: Net food imports are generated from FAOSTAT, taking Export level (tonnes) from the Import level (tonnes) [both under Trade: Crops and Livestock Products]. Net food imports are a proxy for the country's vulnerability to global food prices.

Unitofmeasure: Tonnes


IndicatorName: Net food imports by crop - Rice, paddy


IndicatorName: Net food imports by crop - Maize


IndicatorName: Net food imports by crop - Rice, broken


IndicatorName: Net food imports by crop - Rice, paddy (rice milled equivalent)


IndicatorName: Net food imports by crop - Rice, husked


IndicatorName: Net food imports by crop - Rice, milled/husked


IndicatorName: Net food imports by crop - Rice, milled


IndicatorName: Net food imports by crop - Soybeans


IndicatorName: Net food imports by crop - Wheat


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Cancelled

Longdefinition: Oil pipeline capacity (barrels of oil equivalent per day), by capacity, is generated from the Global Fossil Infrastructure Tracker (GFIT). The GFIT is an information resource on fossil fuel infrastructure projects and their development. Currently, the GFIT includes all global LNG import terminals and export terminals, and all global oil and gas transmission pipelines over a pre-determined size threshold. The Tracker organizes information in both map and table format. The interactive map format allows users to geographically visualize pipeline routes and terminal locations, while the table format allows users to access additional data points on each project. Both the map and table provide menu-based data filtering options as well as links to further information in project-specific wiki pages housed on GEM.wiki. GFIT was accessed in July 2021 to generate this data.


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Construction


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - In Development (Proposed + Construction)


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Operating


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Proposed


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Retired


IndicatorName: Oil pipeline capacity by project status (barrels of oil equivalent per day) - Shelved


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (0-9 years)

Longdefinition: Operating coal power capacity, by plant age, is generated from the Global Coal Plant Tracker (GCPT). The GCPT provides information on coal-fired power units from around the world generating 30 megawatts and above. The GCPT catalogues every operating coal-fired generating unit, every new unit proposed since 2010, and every unit retired since 2000. Units often consist of a boiler and turbine, and several units may make up one coal-fired power station. The map and underlying data is updated bi-annually, in January and July. Each plant included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCPT was accessed in July 2021 to generate this data.

Source: Global Coal Plant Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-coal-plant-tracker/

Unitofmeasure: MW


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (10-19 years)


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (20-29 years)


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (30-39 years)


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (40-49 years)


IndicatorName: Operating coal power capacity by plant age (MW) - Coal plant age (50-plus years)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (Subcritical/CCS)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (CFB)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (IGCC)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (Supercritical)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (Subcritical)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (Unknown)


IndicatorName: Operating coal power capacity by plant type (MW) - Plant Type (Ultra-super)


IndicatorName: Percentage of people who believe it is somewhat very likely that they could use the right to use their property of part of it against their will in the next 5 years

Longdefinition: Indicator reflects percentage of people who believe it is somewhat very likely that they could lose the right to use their property of part of it against their will in the next 5 years

Source: Prindex. Available at: https://www.prindex.net/data/

Unitofmeasure: % of total population


IndicatorName: Percentage of people who believe it is very unlikely or unlikely that they could use the right to use their property of part of it against their will in the next 5 years

Longdefinition: Indicator reflects percentage of people who believe it is very unlikely or unlikely that they could lose the right to use their property of part of it against their will in the next 5 years


IndicatorName: Percentage of people who say they have formal documents, legally-binding documents that demonstrate their right to live in or use any of their properties

Longdefinition: Indicator reflects percentage of people who say they have formal documents, legally-binding documents that demonstrate their right to live in or use any of their properties


IndicatorName: Percentage of people who say they have informal documents that demonstrate their right to live in or use any of their properties

Longdefinition: Indicator reflects percentage of people who say they have informal documents that demonstrate their right to live in or use any of their properties


IndicatorName: Percentage of people who say they have no documents or informal documents that demonstrate their right to live in or use any of their properties

Longdefinition: Indicator reflects percentage of people who say they have no documents or informal documents that demonstrate their right to live in or use any of their properties


IndicatorName: Average supply of protein of animal origin (g/cap/day)

Longdefinition: Average supply of protein of animal origin reflects a 3-year average from the Suite of Food Security Indicators on FAOSTAT. Suite of Food Security Indicators presents the core set of food security indicators. Following the recommendation of experts gathered in the Committee on World Food Security (CFS) Round Table on hunger measurement, hosted at FAO headquarters in September 2011, an initial set of indicators aiming to capture various aspects of food insecurity is presented on FAOSTAT. The choice of the indicators has been informed by expert judgment and the availability of data with sufficient coverage to enable comparisons across regions and over time. Many of these indicators are produced and published elsewhere by FAO and other international organizations. They are reported on FAOSTAT in a single database with the aim of building a wide food security information system. More indicators will be added to this set as more data will become available. Indicators are classified along the four dimensions of food security -- availability, access, utilization and stability. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

Unitofmeasure: g/cap/day


IndicatorName: Passenger volume by mode (billion tons-km) - Air transport

Longdefinition: This indicator presents the passenger volume attributable to air transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Passenger volume (passenger kilometres) by mode of transport.


IndicatorName: Passenger volume by mode (billion tons-km) - Rail transport

Longdefinition: This indicator presents the passenger volume attributable to rail transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Passenger volume (passenger kilometres) by mode of transport.


IndicatorName: Passenger volume by mode (billion tons-km) - Road transport

Longdefinition: This indicator presents the passenger volume attributable to road transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Passenger volume (passenger kilometres) by mode of transport.


IndicatorName: Prevalence of undernourishment (3-year average) (% of total)

Longdefinition: Prevalence of undernourishment relfects a 3-year average from the Suite of Food Security Indicators on FAOSTAT. Suite of Food Security Indicators presents the core set of food security indicators. Following the recommendation of experts gathered in the Committee on World Food Security (CFS) Round Table on hunger measurement, hosted at FAO headquarters in September 2011, an initial set of indicators aiming to capture various aspects of food insecurity is presented on FAOSTAT. The choice of the indicators has been informed by expert judgment and the availability of data with sufficient coverage to enable comparisons across regions and over time. Many of these indicators are produced and published elsewhere by FAO and other international organizations. They are reported on FAOSTAT in a single database with the aim of building a wide food security information system. More indicators will be added to this set as more data will become available. Indicators are classified along the four dimensions of food security -- availability, access, utilization and stability. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


IndicatorName: Rice supply quantity (g/capita/day)

Longdefinition: Rice supply is taken from crops processed (domain), food supply quantity (element), rice milled (item) of the Crop statistics (FAOSTAT). FAOSTAT Crop statistics are recorded for 173 products, covering the following categories: Crops Primary, Fibre Crops Primary, Cereals, Coarse Grain, Citrus Fruit, Fruit, Jute Jute-like Fibres, Oilcakes Equivalent, Oil crops Primary, Pulses, Roots and Tubers, Treenuts and Vegetables and Melons. Data are expressed in terms of area harvested, production quantity and yield. The objective is to comprehensively cover production of all primary crops for all countries and regions in the world.Cereals: Area and production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed or silage or used for grazing are therefore excluded. Area data relate to harvested area. Some countries report sown or cultivated area only. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


IndicatorName: Risk to asset (average annual losses as % of GDP)

Longdefinition: Risk to asset indicator is intended to be viewed with risk to wellbeing indicator (both reported as average annual losses as % of GDP). The Unbreakable report which the indicators are taken from moves beyond asset and production losses and shifts its attention to how natural disasters affect people’s well-being. Disasters are far greater threats to well-being than traditional estimates suggest. This approach provides a more nuanced view of natural disasters than usual reporting, and a perspective that takes fuller account of poor people’s vulnerabilities.

Source: Hallegatte, Stephane; Vogt-Schilb, Adrien; Bangalore, Mook; Rozenberg, Julie. 2017. Unbreakable : Building the Resilience of the Poor in the Face of Natural Disasters. Climate Change and Development;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/25335 License: CC BY 3.0 IGO.


IndicatorName: Risk to wellbeing (average annual losses as % of GDP)

Longdefinition: Risk to wellbeing indicator is intended to be viewed with risk to asset indicator (both reported as average annual losses as % of GDP). The Unbreakable report which the indicators are taken from moves beyond asset and production losses and shifts its attention to how natural disasters affect people’s well-being. Disasters are far greater threats to well-being than traditional estimates suggest. This approach provides a more nuanced view of natural disasters than usual reporting, and a perspective that takes fuller account of poor people’s vulnerabilities.


IndicatorName: Percentage of population with No Education

Longdefinition: Education status as a percentage of the total population is disaggregated from the Global Jobs Indicatos Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


IndicatorName: Percentage of population with Primary Education


IndicatorName: Percentage of population with Secondary Education


IndicatorName: Percentage of population with Post Secondary Education


IndicatorName: Mean number of years of education completed, aged 17 and older

Longdefinition: Mean number of years of education completed (aged 17+) is disaggregated from the Global Jobs Indicatos Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.

Unitofmeasure: Number of years


IndicatorName: Mortality rate attributable to household air pollution (deaths per 100 000 population)

Longdefinition: This indicator presents the mortality rate attributable to household air pollution as a factor of deaths per 100 000 population. Data is taken from the United Nations Sustainable Goals, representing Indicator 3.9.1: Crude death rate attributed to ambient air pollution (deaths per 100 000 population).

Unitofmeasure: Deaths per 100 000 population


IndicatorName: Mortality rate attributable to ambient air pollution (deaths per 100 000 population)

Longdefinition: This indicator presents the mortality rate attributable to ambient air pollution as a factor of deaths per 100 000 population. Data is taken from the United Nations Sustainable Goals, representing Indicator 3.9.1: Crude death rate attributed to household air pollution (deaths per 100 000 population).


IndicatorName: Share of population covered by at least one social protection benefit

Longdefinition: This indicator conveys the share of the population effectively covered by a social protection system, including social protection floors. It also provides the coverage rates of the main components of social protection: child and maternity benefits, support for persons without a job, persons with disabilities, victims of work injuries and older persons. For more information, refer to the concepts and definitions page. Alternate source for this information is UN open data hub, SDG Indicator 1.3.1: Proportion of population covered by social protection floors/systems (%) | Annual

Source: International Labour Organization - ILOSTAT database, https://ilostat.ilo.org/data

Unitofmeasure: % of population


IndicatorName: Public social protection expenditure (%of GDP)

Source: The Atlas of Social Protection: Indicators of Resilience and Equity, World Bank Group. Available at: https://datacatalog.worldbank.org/int/search/dataset/0037942


IndicatorName: Number of companies that are TCFD compliant by sector - Central Bank

Longdefinition: TCFD compliant company data is sourced from the Task Force on Climate-Related Financial Disclosures and aggregated into sector brackets. The Task Force on Climate-related Financial Disclosures (TCFD) provides a framework for companies and other organizations to develop more effective climate related financial disclosures through their existing reporting processes.

Source: Task Force on Climate-Related Financial Disclosures. Available at: https://www.fsb-tcfd.org/supporters/

Unitofmeasure: Number


IndicatorName: Number of companies that are TCFD compliant by sector - Consumer Discretionary


IndicatorName: Number of companies that are TCFD compliant by sector - Communication Services


IndicatorName: Number of companies that are TCFD compliant by sector - Consumer Staples


IndicatorName: Number of companies that are TCFD compliant by sector - Energy


IndicatorName: Number of companies that are TCFD compliant by sector - Financials


IndicatorName: Number of companies that are TCFD compliant by sector - Government


IndicatorName: Number of companies that are TCFD compliant by sector - Health Care


IndicatorName: Number of companies that are TCFD compliant by sector - Industrials


IndicatorName: Number of companies that are TCFD compliant by sector - Information Technology


IndicatorName: Number of companies that are TCFD compliant by sector - Materials


IndicatorName: Number of companies that are TCFD compliant by sector - Other


IndicatorName: Number of companies that are TCFD compliant by sector - Real Estate


IndicatorName: Number of companies that are TCFD compliant by sector - Transportation


IndicatorName: Number of companies that are TCFD compliant by sector - Utilities


IndicatorName: Natural hazard levels - Coastal flood

Longdefinition: Natural Hazard levels from Coastal Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.

Source: ThinkHazard! data [https://thinkhazard.org/en/] taken from the Climate Change Knowledge Portal [available at: https://climateknowledgeportal.worldbank.org/]

Unitofmeasure: Hazard level


IndicatorName: Natural hazard levels - Cyclone

Longdefinition: Natural Hazard levels from Cyclones are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Extreme heat

Longdefinition: Natural Hazard levels from Extreme Heat are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Earthquake

Longdefinition: Natural Hazard levels from Earthquakes are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Landslide

Longdefinition: Natural Hazard levels from Landslides are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - River flood

Longdefinition: Natural Hazard levels from River Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Tsunami

Longdefinition: Natural Hazard levels from Tsunamis are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Urban flood

Longdefinition: Natural Hazard levels from Urban Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Natural hazard levels - Wildfire

Longdefinition: Natural Hazard levels from Wildfire are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


IndicatorName: Share of transport network exposed to cyclones (%)

Longdefinition: Share of transport network that is exposed to cyclones, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense cyclone (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).

Source: Hallegatte, Stephane; Rentschler, Jun; Rozenberg, Julie. 2019. Lifelines : The Resilient Infrastructure Opportunity. Sustainable Infrastructure;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/31805 License: CC BY 3.0 IGO.


IndicatorName: Share of transport network exposed to earthquakes (%)

Longdefinition: Share of transport network that is exposed to earthquakes, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense earthquake (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).


IndicatorName: Share of transport network exposed to floods (%)

Longdefinition: Share of transport network that is exposed to floods, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense flood (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).


IndicatorName: Annual investments needed to make transport infrastructure more resilient by 2030 (% of GDP)

Longdefinition: The annual investments, shown as a percentage of a country's GDP, that are needed to make transport infrastructure more resilient by the year 2030. The Lifelines report, Appendix A, lists 70 interventions to make infrastructure systems, including transport networks, more resilient. These interventions have been used to estimate the investment needs for this metric.


IndicatorName: Share of transport network exposed to natural disasters (%)

Longdefinition: Share of transport network that is exposed to natural disasters, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense natural disaster (the threshold is country dependent, based on the expected resistance of the infrastructure in the country). In this instance natural disaster total reflects the results of earthquakes, floods, and cyclones.


IndicatorName: Resilient infrastructure would reduce annual repair cost by a factor

Longdefinition: The Lifelines report, Appendix A, lists 70 interventions to make infrastructure systems, including transport networks, more resilient. These interventions have been used to estimate the annual investments needed to make transport infrastructure more resilient by 2030 (% of GDP). This result was used to derive the factor reduction in annual repair costs.

Unitofmeasure: Value factor


IndicatorName: Total GHG emissions growth in the period 2012-2018 (%)


IndicatorName: Total coal capacity by plant status (MW) - Announced

Longdefinition: Total coal capacity by plant status is generated from the Global Coal Plant Tracker (GCPT). The GCPT provides information on coal-fired power units from around the world generating 30 megawatts and above. The GCPT catalogues every operating coal-fired generating unit, every new unit proposed since 2010, and every unit retired since 2000. Units often consist of a boiler and turbine, and several units may make up one coal-fired power station. The map and underlying data is updated bi-annually, in January and July. Each plant included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCPT was accessed in July 2021 to generate this data.


IndicatorName: Total coal capacity by plant status (MW) - Cancelled


IndicatorName: Total coal capacity by plant status (MW) - Construction


IndicatorName: Total coal capacity by plant status (MW) - Mothballed


IndicatorName: Total coal capacity by plant status (MW) - Operating


IndicatorName: Total coal capacity by plant status (MW) - Permitted


IndicatorName: Total coal capacity by plant status (MW) - Pre-permit


IndicatorName: Total coal capacity by plant status (MW) - Retired


IndicatorName: Total coal capacity by plant status (MW) - Shelved


Aggregationmethod: Weighted Average

Developmentrelevance:
Maintaining reliable and secure electricity services while seeking to rapidly decarbonize power systems is a key challenge for countries throughout the world. More and more countries are becoming increasing dependent on reliable and secure electricity supplies to underpin economic growth and community prosperity. This reliance is set to grow as more efficient and less carbon intensive forms of power are developed and deployed to help decarbonize economies.

Energy is necessary for creating the conditions for economic growth. It is impossible to operate a factory, run a shop, grow crops or deliver goods to consumers without using some form of energy. Access to electricity is particularly crucial to human development as electricity is, in practice, indispensable for certain basic activities, such as lighting, refrigeration and the running of household appliances, and cannot easily be replaced by other forms of energy. Individuals' access to electricity is one of the most clear and un-distorted indication of a country's energy poverty status.

Electricity access is increasingly at the forefront of governments' preoccupations, especially in the developing countries. As a consequence, a lot of rural electrification programs and national electrification agencies have been created in these countries to monitor more accurately the needs and the status of rural development and electrification.

Use of energy is important in improving people's standard of living. But electricity generation also can damage the environment. Whether such damage occurs depends largely on how electricity is generated. For example, burning coal releases twice as much carbon dioxide - a major contributor to global warming - as does burning an equivalent amount of natural gas.

IndicatorName: Access to electricity (% of population)

Longdefinition: Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.

Periodicity: Annual

Source: World Bank Global Electrification Database from "Tracking SDG 7: The Energy Progress Report" led jointly by the custodian agencies: the International Energy Agency (IEA), the International Renewable Energy Agency (IRENA), the United Nations Statistics Division (UNSD), the World Bank and the World Health Organization (WHO).

Statisticalconceptandmethodology: Data for access to electricity are collected among different sources: mostly data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Given the low frequency and the regional distribution of some surveys, a number of countries have gaps in available data. To develop the historical evolution and starting point of electrification rates, a simple modeling approach was adopted to fill in the missing data points - around 1990, around 2000, and around 2010. Therefore, a country can have a continuum of zero to three data points. There are 42 countries with zero data point and the weighted regional average was used as an estimate for electrification in each of the data periods. 170 countries have between one and three data points and missing data are estimated by using a model with region, country, and time variables. The model keeps the original observation if data is available for any of the time periods. This modeling approach allowed the estimation of electrification rates for 212 countries over these three time periods (Indicated as "Estimate"). Notation "Assumption" refers to the assumption of universal access in countries classified as developed by the United Nations. Data begins from the year in which the first survey data is available for each country.


IndicatorName: Population living in slums (% of urban population)

Longdefinition: Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.

Source: United Nations Human Settlements Programme (UN-HABITAT)

Topic: Country Profile

Unitofmeasure: % of urban population