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The Energy Institute Statistical Review of World Energy™ analyses data on world energy markets from the prior year. Previously produced by bp, the Review has been providing timely, comprehensive and objective data to the energy community since 1952.

The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2014The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2015

OECD Indicators on Carbon dioxide (CO2) emissions embodied in international trade (TeCO2) are derived by combining the 2021 editions of OECD Inter-Country Input-Output (ICIO) Database and of International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. In this release of TeCO2, emissions from fuels used for international aviation and maritime transport (i.e. aviation and marine bunkers) are also considered.Production-based CO2 emissions are estimated by allocating the CO2 emissions to the 45 target industries in OECD ICIO and, to household final consumption of fuels, by both residents and non-residents.Demand-based CO2 emissions are calculated by multiplying the intensities of the production-based emissions (c) with the global Leontief inverse (I-A)(-1) and global final demand matrix (Y) from OECD ICIO, taking the column sums of the resulting matrix and adding residential and private road emissions (FNLC), i.e. direct emissions from final demand: colsum [ diag(c) (I-A)(-1) Y ] + FNLC.For more information, see TeCO2 web page: http://oe.cd/io-co2.

Data cited at: The World Bank  https://datacatalog.worldbank.org/ Topic:Climate Investment Funds – Clean Technology Fund (CTF) Results Data Publication: https://finances.worldbank.org/Projects/2019-Climate-Investment-Funds-Clean-Technology-Fun/kjmm-jfbk License: http://creativecommons.org/licenses/by/4.0/ 

GHG emissions data from cultivation of organic soils are those associated with nitrous oxide gas from cultivated organic soils under cropland (item: cropland organic soils) and grassland (item: grassland organic soils). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg N2O and Gg CO2eq, by cropland, grassland and by the two aggregated. Implied emission factor for N2O as well activity data (areas) are also provided.

Greenhouse Gas (GHG) emissions from burning crop residues consist of methane (CH4) and nitrous oxide (N2O) gases produced by the combustion of a percentage of crop residues burnt on-site. The mass of fuel available for burning should be estimated taking into account the fractions removed before burning due to animal consumption, decay in the field, and use in other sectors (e.g., biofuel, domestic livestock feed, building materials, etc.). FAOSTAT emission estimates are computed at Tier 1 following the IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, reguions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4, Gg N2O, Gg CO2eq and CO2eq from CH4 and N2O, by crop (maize, rice, sugarcane and wheat) and by aggregates. Implied emission factors for N2O and CH4 as well activity data (biomass burned) are also provided.

Greenhouse gas (GHG) emissions from enteric fermentation consist of methane gas produced in digestive systems of ruminants and to a lesser extent of non-ruminants. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4 and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), goats, horses, llamas, mules, sheep, swine (breeding and market)) and by species aggregates (all animals, camels and llamas, cattle, mules and asses, sheep and goats, swine). Implied emission factor for CH4 and activity data are also provided

GHG emissions from manure applied to soils consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) added to agricultural soils by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the application site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding and market) and turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and activity data (N content in manure) are also provided.

GHG emissions from manure left on pastures consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) left on pastures by grazing livestock. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as direct, indirect and total Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding, market), turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and N content in manure are also provided.

Greenhouse gas (GHG) emissions from synthetic fertilizers consist of nitrous oxide gas from synthetic nitrogen additions to managed soils. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the addition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq. Implied emission factor for N2O and activity data (consumption) are also provided.

Greenhouse Gas (GHG) emissions from burning of biomass consist of methane and nitrous oxide gases from biomass combustion of forest land cover classes ‘Humid and Tropical Forest’ and ‘Other Forests’, and of methane, nitrous oxide, and carbon dioxide gases from combustion of organic soils. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (humid tropical forest, other forest, organic soils) and by aggregate (burning - all categories). Implied emission factors for N2O, CH4 and CO2 as well activity data (burned area and biomass burned) are also provided.

Annual net CO2 emission/removal from Forest Land consist of net carbon stock gain/loss in the living biomass pool (aboveground and belowground biomass) associated with Forest and Net Forest Conversion. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html) and using area and carbon stocks data compiled by countries in the FAO Global Forest Resource Assessments (http://www.fao.org/forestry/fra/en/). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net stock change Gg C, net emissions/removals Gg CO2 and CO2eq, by forest or net forest conversion and by aggregate (forest land). Implied emission factor for CO2 as well as activity data (area, net area difference, total forest area and carbon stock in living biomass) are also given.

The FAOSTAT domain Organic soils consist of nitrous oxide (N2O) and carbon dioxide (CO2) emissions associated with the drainage of organic soils ? using histosols as proxy ? for agriculture. Data are computed geospatially, using the Tier 1 method of the 2006 IPCC Guidelines for National greenhouse gas Inventories (IPCC, 2006). Estimates are available by country and with global coverage, in complete time series for the period 1990?2019. The database is updated annually. The FAOSTAT domain Organic soils disseminates information by country on: activity data (in hectares of organic soils drained for agriculture); and greenhouse gas (GHG) emissions (in kilotonnes of N2O and CO2). Drainage and associated emissions are assessed separately for IPCC land use categories cropland and grassland, corresponding to FAO land use categories ??cropland?? and ??permanent meadows and pastures.?? Data are available for all countries and territories, for standard FAOSTAT regional aggregations, and for Annex I and non-Annex I country groups. This FAOSTAT domain also disseminates the activity data and emissions data reported by countries to the United Nations Framework Convention on Climate Change (UNFCCC), under ?Cultivation of organic soils? for the N2O component and categories ?Cropland drained organic soils? and ?Grassland drained organic soils? for the CO2. Activity data are sourced from the most recently available GHG National Inventories (NGHGI) or from National Communications. Emission data are sourced directly from the UNFCCC data portal or from Biennial Update Reports (BURs). UNFCCC data are disseminated in FAOSTAT with permission, formalized via a FAO-UNFCCC Memorandum of Understanding.

As of Jun 2021, estimates of greenhouse gas (GHG) emissions from agriculture and land use are disseminated under the FAOSTAT heading Climate Change/Emissions. This heading consolidates and replaces two previous distinct headings: Emissions-Agriculture and Emissions-Land Use, which no longer exist. Several other domains were consolidated to facilitate data access. https://fenixservices.fao.org/faostat/static/documents/GT/README_Changes_in_2021.pdf   The domain Emissions Totals consolidatesin one single dataset the information previously presented in two separate datasets: Agriculture total (previously: http://www.fao.org/faostat/en/#data/GT; containing data on non-CO2 emissions from agriculture); and Land Use total (previously: http://www.fao.org/faostat/en/#data/GL; containing CO2 and non-CO2 emissions from land use, land use change and forestry. This link no longer works).

Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.

NOTICE (March 2018): This website provides access to the CDIAC archive data temporarily. It will be gradually transitioned into data packages in the new ESS-DIVE archive. This site will continue to operate in parallel during and after the transition, and will be retired at a future date. If you have any questions regarding the data or the transition, please contact [email protected]. The carbon-cycle model simulates vegetation, litter, and soil carbonin 12 ecosystem and land-use classifications aggregated to 14 world regions. Land-use transitions are calculated annually on a 0.5 degree grid before aggregation to the regional level. Secondary forest re-growth is simulated in 50-year age classes for non-boreal forest (labeled as 1500_OtherForest, for forest that started regrowing in the period 1500-1549). Carbon stocks as land-use changes (e.g. conversion to cropland or reversion to native ecosystems) are explicitly tracked over time. Regional cropland areas, productivity, and harvest index change over time as estimated from historical data.

The Global Carbon Project facilitates access to data to encourage its use and promote a good understanding of the carbon cycle. Respecting original data sources is key to help secure the support of data providers to enhance, maintain and update valuable data. 

Global Footprint Network National Footprint Accounts, 2019 Edition Downloaded on 2 October 2020 from http://data.footprintnetwork.org.

Direct greenhouse gases: Carbon Dioxide (CO2), Methane (CH4), Nitrous Oxide (N2O), Hydrofluorocarbons (HFC-23, 32, 125, 134a, 143a, 152a, 227ea, 236fa, 245fa, 365mfc, 43-10-mee), Perfluorocarbons (PFCs: CF4, C2F6, C3F8, c-C4F8, C4F10, C5F12, C6F14, C7F16), Sulfur Hexafluoride (SF6), Nitrogen Trifluoride (NF3) and Sulfuryl Fluoride (SO2F2). Emissions are calculated by individual countries using country-specific information. The countries are organized in different world regions for illustration purposes. Emissions of some small countries are presented together with other countries depending on country definition and availability of activity statistics. Source: European Commission, Joint Research Centre (JRC)/PBL Netherlands Environmental Assessment Agency.

FAO - GLEAM Global greenhouse gas emissions from livestock summary data (2017)

The OECD Green Growth database contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The database synthesises data and indicators across a wide range of domains including a range of OECD databases as well as external data sources. The database covers OECD member and accession countries, key partners (including Brazil, China, India, Indonesia and South Africa) and other selected non-OECD countries.

Citation: Global Footprint Network, National Footprint and Biocapacity Accounts, 2022  Edition Downloaded 2022 -04 -19 from  https://data.footprintnetwork.org .   NFA 2022 National Footprint and Biocapacity Accounts data set (1961-2018) This data includes total and per capita national biocapacity, the ecological footprint of consumption, the ecological footprint of production, and total area in hectares. This dataset, however, does not include any of our yield factors (national or world) nor any equivalence factors.    

Ocean Health Index

Data cited at: Numbeo-https://www.numbeo.com/pollution/rankings_by_country.jsp?title=2020 Pollution Index is an estimation of the overall pollution in the city. The biggest weight is given to air pollution, than to water pollution/accessibility, two main pollution factors. Small weight is given to other pollution types. Pollution Exp Scale is using an exponential scale to show very high numbers for very polluted cities, and very low numbers for unpolluted cities. Therefore to calculate formula it uses the exponential function to calculate the index.

Data Cited at - Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., Fuller, G. (2019): Sustainable Development Report 2019. New York: Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN). The Sustainable Development Report 2020 presents the SDG Index and Dashboards for all UN member states and frames the implementation of the Sustainable Development Goals (SDGs) in terms of six broad transformations. It was prepared by teams of independent experts at the Sustainable Development Solutions Network (SDSN) and the Bertelsmann Stiftung.

The OECD Sustainable Ocean Economy Database synthesizes available ocean-related datasets and indicators from across the Organisation to improve their discoverability and comparability. The database brings together relevant indicators from the Environment Directorate (ENV), the Trade and Agriculture Directorate (TAD), the Centre for Entrepreneurship, SMEs, Regions and Cities (CFE), the International Transport Forum (ITF), the International Energy Agency (IEA), and others.

Latest data available here by topic: Emission - https://knoema.com/FAOEMLULUT2015/, https://knoema.com/FAOEMLUBM2017/ Environment- https://knoema.com/FAOAGLND2017/agri-environmental-indicators-land Forest - https://knoema.com/FAOEMLUFL2015/ Energy: https://knoema.com/WBMDG2017/millennium-development-goals?accesskey=dsyjnoe  

Data cited at: The World Bank https://www.worldbank.org/en/about/annual-report#anchor-annual- Topic: The World Bank Annual Report 2022- Publication:  https://www.worldbank.org/en/about/annual-report#anchor-annual- License:  https://creativecommons.org/licenses/by/3.0/igo/ Notes: The Annual Report is prepared by the Executive Directors of the International Bank for Reconstruction and Development (IBRD) and the International Development Association (IDA) - collectively known as the World Bank - in accordance with the by-laws of the two institutions. The President of the IBRD and IDA and the Chairman of the Board of Executive Directors submits the Report, together with the accompanying administrative budgets and audited financial statements, to the Board of Governors.

Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development.

Note: The data is no longer available to the Public. It requires an account with WCCD to access data. 

The primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates