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Australia

  • Governor General:David Hurley
  • Prime Minister:Scott Morrison
  • Capital city:Canberra
  • Languages:English 76.8%, Mandarin 1.6%, Italian 1.4%, Arabic 1.3%, Greek 1.2%, Cantonese 1.2%, Vietnamese 1.1%, other 10.4%, unspecified 5% (2011 est.)
  • Government
  • National statistics office
  • Population, persons:24,992,369 (2018)
  • Area, sq km:7,692,020
  • GDP per capita, US$:57,305 (2018)
  • GDP, billion current US$:1,432.2 (2018)
  • GINI index:No data
  • Ease of Doing Business rank:18
All datasets:  A C D E F G I L M O P R S T U W
  • A
    • November 2018
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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      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
    • July 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 05 July, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 October, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilizers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • March 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 March, 2019
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      Air Emission Accounts are available for European countries and a few non-European countries. The System of Environmental-Economic Accounting (SEEA) Central Framework is an accounting system developed around two objectives: "understanding the interactions between the economy and the environment" and describing "stocks and changes in stocks of environmental assets". The SEEA combines national accounts and environmental statistics in a statistical framework with consistent definitions, classifications and concepts allowing policy makers to evaluate environmental pressures from economic activities at macro- and meso-levels. Data refer to total emissions of CO2 (CO2 emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), N2O (nitrous oxide), HFCs (hydrofluorocarbons), PFCs (perfluorocarbons), (SF6 +NF3) (sulphur hexafluoride and nitrogen trifluoride), SOx (sulphur oxides, NOx (nitrogen oxides), CO (carbon monoxide), NMVOC (non-methane volatile organic compounds), PM2.5 (particulates less that 2.5 µm), PM10 (particulates less that 10 µm) and NH3 (ammonia). The OECD Air Emission Accounts present data based on ISIC rev. 4.
  • C
    • October 2017
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 06 August, 2018
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      Data Citation: CAIT Climate Data Explorer. 2017. Washington, DC: World Resources Institute. Available online at: http://cait.wri.org   CAIT data carries a Creative Commons Attribution-NonCommercial 4.0 International license   CAIT Historic allows for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 186 countries, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2012 and multi-sector greenhouse gas emission for 1990-2012.
    • May 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 May, 2019
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      Indicators in the OECD database on Carbon dioxide (CO2) emissions embodied in international trade are derived by combining the 2015 version of OECD's Inter-Country Input-Output (ICIO) Database with International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. Production-based CO2 emissions are estimated by allocating the IEA CO2 emissions to the 34 target industries in OECD ICIO and, to final demand for fuels, by both residents and non-residents. Consumption-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. The ICIO system includes discrepancies in the trade data (referred to as DISC). Emissions allocated to DISC are made explicit (e.g. in indicator FD_CO2). This ensures that global CO2 production equals global CO2 consumption.
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 October, 2019
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    • July 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 16 October, 2019
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      GHG emissions data from the cultivation of organic soils are those associated with nitrous oxide gas from 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 their aggregation. Implied emission factor for N2O as well activity data (areas) are also provided.
  • D
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 October, 2019
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      The objective of this dataset is to trace net changes in terms of volume in the growing stock of standing wood on forest land. It shows data underlying the indicator on the intensity of use of forest resources. This indicator relates actual fellings to annual productive capacity (i.e. gross increment). Forest depletion and growth describe balances or imbalances in different types of forests. The intensity of use of forest resources reflects various forest management methods and their sustainability. These data should be read in connection with other indicators of the OECD Core Set, in particular with indicators on land use changes and forest quality (species diversity, forest degradation), and be complemented with data on forest management practices and protection measures. In interpreting these data, it should be borne in mind that definitions and estimation methods vary among countries.
  • E
    • July 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 16 October, 2019
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      Greenhouse Gas (GHG) emissions from burning of savanna consist of methane (CH4) and nitrous oxide (N2O) gases produced from the burning of vegetation biomass in the following five land cover types: Savanna, Woody Savanna, Open Shrublands, Closed Shrublands, and Grasslands. 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, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (savanna, woody savanna, closed shrubland, open shrubland, grassland) and by aggregates (all categories, savanna and woody savanna, closed and open shrubland). Implied emission factors for N2O and CH4 as well activity data (burned area and biomass burned) are also provided.
    • September 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 16 October, 2019
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      Agriculture Total contains all the emissions produced in the different agricultural emissions sub-domains (enteric fermentation, manure management, rice cultivation, synthetic fertilizers, manure applied to soils, manure left on pastures, crop residues, cultivation of organic soils, burning of crop residues, burning of savanna, energy use), providing a picture of the contribution to the total amount of GHG emissions from agriculture. GHG emissions from agriculture consist of non-CO2 gases, namely methane (CH4) and nitrous oxide (N2O), produced by crop and livestock production and management activities. 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). 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 Gg CO2 and CO2eq (from CH4 and N2O), by underlying agricultural emission sub-domain and by aggregate (agriculture total, agriculture total plus energy, agricultural soils).
    • June 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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.
    • June 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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
    • June 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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.
    • June 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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.
    • September 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 16 October, 2019
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      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.
    • May 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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.
    • December 2018
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      Greenhouse gas (GHG) emissions data from cropland are currently limited to emissions from cropland organic soils. They are those associated with carbon losses from drained histosols under cropland. 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/vol5.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.
    • December 2018
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      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.
    • December 2018
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      Greenhouse gas (GHG) emissions data from grassland are currently limited to emissions from grassland organic soils. They are those associated with carbon losses from drained histosols under grassland. 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/vol6.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.
    • May 2019
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 26 June, 2019
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      Land Use Total contains all GHG emissions and removals produced in the different Land Use sub-domains, representing the three IPCC Land Use categories: cropland, forest land, and grassland, collectively called emissions/removals from the Forestry and Other Land Use (FOLU) sector. FOLU emissions consist of CO2 (carbon dioxide), CH4 (methane) and N2O (nitrous oxide) associated with land management activities. CO2 emissions/removals are derived from estimated net carbon stock changes in above and below-ground biomass pools of forest land, including forest land converted to other land uses. CH4 and N2O, and additional CO2 emissions are estimated for fires and drainage 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/index.html). GHG emissions are provided as by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CO2eq from CH4 and N2O, net emissions/removals as GG CO2 and Gg CO2eq, by underlying land use emission sub-domain and by aggregate (land use total).
    • September 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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      This dataset provides selected information on national emissions of traditional air pollutants: emission data are based upon the best available engineering estimates for a given period; they concern man-made emissions of sulphur oxides (SOx), nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO) and volatile organic compounds (VOC). Categories presented are based on the NFR 2014 classification. Data exclude non man-made emissions and international aviation and maritime transports emissions. For some countries residential mobile emissions (e.g. mowers) are included into Other combustion instead of Other mobile. The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.  
    • January 2018
      Source: Yale Center for Environmental Law & Policy
      Uploaded by: Knoema
      Accessed On: 02 February, 2018
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      Data cited at: Wendling, Z. A., Emerson, J. W., Esty, D. C., Levy, M. A., de Sherbinin, A., et al. (2018). 2018 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law & Policy. https://epi.yale.edu/   The Environmental Performance Index (EPI) is constructed through the calculation and aggregation of 20 indicators reflecting national-level environmental data. These indicators are combined into nine issue categories, each of which fit under one of two overarching objectives. The two objectives that provide the overarching structure of the EPI are Environmental Health and Ecosystem Vitality. Environmental Health measures the protection of human health from environmental harm. Ecosystem Vitality measures ecosystem protection and resource management. These two objectives are further divided into nine issue categories that span high-priority environmental policy issues, including air quality, forests, fisheries, and climate and energy, among others. The issue categories are extensive but not comprehensive. Underlying the nine issue categories are 20 indicators calculated from country-level data and statistics. After more than 15 years of work on environmental performance measurement and six iterations of the EPI, global data are still lacking on a number of key environmental issues. These include: freshwater quality, toxic chemical exposures, municipal solid waste management, nuclear safety, wetlands loss, agricultural soil quality and degradation, recycling rates, adaptation, vulnerability, and resiliency to climate change, desertification.
    • April 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 April, 2019
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    • April 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 April, 2019
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      Agriculture can have significant impacts on the environment as it uses on average over 40% of water and land resources in OECD countries. The impacts occur on and off farm, including both pollution and degradation of soil, water and air, as well as the provision of ecological goods and services, such as biodiversity and providing a sink for greenhouse gases. Most OECD countries are tracking the environmental performance of agriculture, which is informing policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis (Chapter 4). As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They are also enriching the understanding and analysis of the environmental effects of possible future policy scenarios and agricultural projections. This report provides the latest and most comprehensive data across OECD countries on the environmental performance of agriculture since 1990. A set of agri-environmental indicators (Annex 1, Section II) has been developed through several specific theme-focused workshops involving OECD country analysts and scientific experts, complemented with thorough reviews of the literature. The OECD’s Driving Force-State-Response model (DSR) is the organising framework for developing the indicators.
    • April 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 April, 2019
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      As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They can also help the understanding and analysis of the environmental effects of future policy scenarios and agricultural projections. To help improve measurement of the environmental performance of agriculture, OECD has established a set of agri-environmental indicators, with development of the indicators in cooperation with Eurostat and FAO. These indicators inform policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis.
    • July 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 July, 2019
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      The OECD Environmental Policy Stringency Index (EPS) is a country-specific and internationally-comparable measure of the stringency of environmental policy. Stringency is defined as the degree to which environmental policies put an explicit or implicit price on polluting or environmentally harmful behaviour. The index ranges from 0 (not stringent) to 6 (highest degree of stringency). The index covers 28 OECD and 6 BRIICS countries for the period 1990-2012. The index is based on the degree of stringency of 14 environmental policy instruments, primarily related to climate and air pollution.
    • July 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 July, 2019
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      Unit of measure used Environmental protection (EP) includes all purposeful activities directly aimed at the prevention, reduction and elimination of pollution or any other degradation of the environment resulting from production or consumption processes. The scope of Environmental Protection is defined according to the Classification of Environmental Protection Activities (CEPA), which distinguishes nine different environmental domains. Activities such as energy and material saving are only included to the extent that they mainly aim at environmental protection. An important example is recycling which is included only to the extent that it constitutes a substitute for waste management. Excluded are: (i) activities that, while beneficial to the environment, primarily satisfy technical needs or health and safety requirements for the protection of the workplace. (ii) expenditure linked to mobilisation of natural resources (e.g., water supply). (iii) calculated cost items such as depreciation (consumption of fixed capital) or the cost of capital as this questionnaire only records actual outlays. (iv) payments of interest, fines and penalties for non-compliance with environmental regulations or compensations to third parties etc., as they are not directly linked with an environmental protection activity. Environmental Protection Expenditure can be evaluated both according to the abater principle and the financing principle. This distinction makes it possible to aggregate different sectors and industries without double counting. Expenditure according to the abater principle (EXP I), includes all expenditure that the sector has for measures they themselves execute. Any economic benefits directly linked with the environmental protection activities (Receipts from by-products) are deducted in order to calculate the net amount of money spent by the sector for their own activities. The financing principle (EXP II) measures how much money a particular sector (directly) contributes to overall environmental protection activities, wherever they are executed. This means that the part of EXP I that was directly financed by others (through subsidies or revenues received) should be deducted, while the part of EXP I in other sectors that this sector finances directly (through subsidies or fees paid) should be added. The framework is based on double entry bookkeeping, where each activity and expenditure item has an abater (producer) and a financing side. This means that much expenditure by specialised producers is financed by the users of their services, mainly business sector and households. This will be recorded as Revenues for the Specialised producers (Table 4), and fees/purchases in Business and Households (Tables 2 and 3). Specialised producers include the production of environmental protection services by public and private corporations or quasi-corporations for the use of other units, mainly financed by the users of these services. These are mainly activities within ISIC Rev. 4/NACE Rev. 2 division and classes 37, 38.1, 38.2 and 39 such as: 37 Sewerage, 38.1 Waste collection, 38.2 Waste treatment and disposal, 39  Remediation activities and other waste management services. This sector is the sum of two components: a) Public specialised producers: All corporations and quasi-corporations that are subject to control by government units. Control is defined as the ability to determine general corporate policy by choosing appropriate directors, if necessary (Table 4A). b) Private specialised producers: All corporations and quasi-corporations that are not subject to control by government units (Table 4B). Specialised producers could also include for example the activities of e.g. volunteer environmental organisations or secondary environmental activities. These should be entered along with a footnote describing the coverage. CEPA domains: a column "pollution abatement and control" (PAC) has been kept in the questionnaire to ensure continuity with earlier data series.
    • August 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 August, 2019
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      EAMFP growth measures the residual growth in the joint production of both the desirable and the undesirable outputs that cannot be explained by changes in the consumption of factor inputs (including labour, produced capital and natural capital). Therefore, for a given growth of input use, EAMFP increases when GDP increases or when pollution decreases. As part of the growth accounting framework underlying the EAMFP indicator, the growth contribution of natural capital and growth adjustment for pollution abatement indicators are derived: Growth contribution of natural capital - measures to what extent a country's growth in output is attributable to natural resource use; Growth adjustment for pollution abatement - measures to what extent a country's GDP growth should be corrected for pollution abatement efforts - adding what has been undervalued due to resources being diverted to pollution abatement, or deducing the ‘excess' growth which is generated at the expense of environmental quality.
    • November 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 August, 2019
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      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.
    • May 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 May, 2019
      Select Dataset
      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 visualization.
    • October 2019
      Source: Maximiliano Herrera's Human Rights Site
      Uploaded by: Knoema
      Accessed On: 25 October, 2019
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      Data cited at: Maximiliano Herrera's Human Rights Site    Fahrenheit values calculated using formula. Fahrenheit  T(°F) = T(°C) × 9/5 + 32 for Country data calculated average for each country locations.
  • F
    • July 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 August, 2017
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      The OECD food waste dataset is a compilation of available data related to food loss and food waste for 32 countries. The period covered may vary across different countries depending on data availability (globally ranging from 1993 to 2013). Several types of sources have been used: international organisations, government and national statistic institutes, OECD delegations, academic studies and private sector or>>/governmental analytical reports. When available, detailed information on sources is provided in the "variable def. and sources" (eg. references to an academic article or a government website).
    • December 2016
      Source: Carbon Dioxide Information Analysis Center
      Uploaded by: Sandeep Reddy
      Accessed On: 17 May, 2017
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      World and National CO2 Emissions from Fossil-Fuel Burning, Cement Manufacture, and Gas Flaring. Source: Tom Boden, Gregg Marland and Bob Andres (Oak Ridge National Laboratory)
  • G
    • September 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 September, 2019
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      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat), and to Eurostat through the Waste Statistics Regulation. They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences.
    • April 2018
      Source: United Nations Statistics Division
      Uploaded by: Knoema
      Accessed On: 21 November, 2018
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      Environmental Indicators disseminate global environment statistics on ten indicator themes compiled from a wide range of data sources. The themes and indicator tables were selected based on the current demands for international environmental statistics and the availability of internationally comparable data. Indicator tables, charts and maps with relatively good quality and coverage across countries, as well as links to other international sources, are provided under each theme. Statistics on Water and Waste are based on official statistics supplied by national statistical offices and/or ministries of environment (or equivalent institutions) in response to the biennial UNSD/UNEP Questionnaire on Environment Statistics, complemented with comparable statistics from OECD and Eurostat, and water resources data from FAO Aqua stat. Statistics on other themes were compiled by UNSD from other international sources. In a few cases, UNSD has made some calculations in order to derive the indicators. However, generally no adjustments have been made to the values received from the source. UNSD is not responsible for the quality, completeness/availability, and validity of the data. Environment statistics is still in an early stage of development in many countries, and data are often sparse. The indicators selected here are those of relatively good quality and geographic coverage. Information on data quality and comparability is given at the end of each table together with other important metadata.
    • November 2018
      Source: Emission Database for Global Atmospheric Research
      Uploaded by: Knoema
      Accessed On: 14 February, 2019
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      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.
    • September 2018
      Source: Dual Citizen LLC
      Uploaded by: Knoema
      Accessed On: 21 September, 2018
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      The performance index of the 2018 GGEI is defined by 20 underlying indicators, each contained within one of the four main dimensions of leadership & climate change, efficiency sectors, markets & investment and the environment.   For more detail on our approach to aggregating these diverse data sources to define the composite indicators in the GGEI and its four main dimensions, as well as our approach to data selection, weighting and other issues associated with creating an index, please visit the Methodology section.
    • October 2017
      Source: Emission Database for Global Atmospheric Research
      Uploaded by: Knoema
      Accessed On: 10 January, 2018
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      Emissions are calculated for the following substances: 1) 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); 2) Ozone precursor gases: Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non-Methane Volatile Organic Compounds (NMVOC) and Methane (CH4). 3) Acidifying gases: Ammonia (NH3), Nitrogen oxides (NOx) and Sulfur Dioxide (SO2). 4) Primary particulates: Fine Particulate Matter (PM10) - Carbonaceous speciation (BC , OC) is under progress. 5) Stratospheric Ozone Depleting Substances: Chlorofluorocarbons (CFC-11, 12, 113, 114, 115), Halons (1211, 1301, 2402), Hydrochlorofluorocarbons (HCFC-22, 124, 141b, 142b), Carbon Tetrachloride (CCl4), Methyl Bromide (CH3Br) and Methyl Chloroform (CH3CCl2). Emissions (EM) for a country C are calculated for each compound x on an annual basis (y) and sector wise (for i sectors, multiplying on the one hand the country-specific activity data (AD), quantifying the human activity for each of the i sectors, with the mix of j technologies (TECH) for each sector i, and with their abatement percentage by one of the k end-of-pipe (EOP) measures for each technology j, and on the other hand the country-specific emission factor (EF) for each sector i and technology j with relative reduction (RED) of the uncontrolled emission by installed abatement measure k. Emissions in 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.
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 October, 2019
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      This dataset contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The indicator bring together the OECD's statistics, indicators and measures of progress. The dataset covers OECD countries as well as BRIICS economies (Brazil, Russian Federation, India, Indonesia, China and South Africa), and selected countries when possible. The indicators are selected according to well specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: Environmental and resource productivity, to indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; The natural asset base, to indicate the risks to growth from a declining natural asset base; Environmental quality of life, to indicate how environmental conditions affect the quality of life and wellbeing of people; Economic opportunities and policy responses, to indicate the effectiveness ofpolicies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.
    • December 2018
      Source: United Nations Framework Convention on Climate Change
      Uploaded by: Knoema
      Accessed On: 13 March, 2019
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      In accordance with Articles 4 and 12 of the Climate Change Convention, and the relevant decisions of the Conference of the Parties, countries that are Parties to the Convention submit national greenhouse gas (GHG) inventories to the Climate Change secretariat. These submissions are made in accordance with the reporting requirements adopted under the Convention, such as The UNFCCC Reporting Guidelines on Annex I Inventories (document FCCC/SBSTA/2004/8) for Annex I Parties and Guidelines for the preparation of national communications for non-Annex I Parites (decision 17/CP.8). The inventory data are provided in the annual GHG inventory submissions by Annex I Parties and in the national communications under the Convention by non-Annex I Parties. The GHG data reported by Parties contain estimates for direct greenhouse gases, such as: CO2 - Carbon dioxide CH4 - Methane N2O - Nitrous oxide PFCs - Perfluorocarbons HFCs - Hydrofluorocarbons SF6 - Sulphur hexafluoride as well as for the indirect greenhouse gases such as SO2, NOx, CO and NMVOC.
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 October, 2019
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      This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas.   Data refer to total emissions of CO2 (emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Data exclude indirect CO2.   Intensities (per unit of GDP and per capita) as well as index are calculated on gross direct emissions excluding emissions or removals from land-use, land-use change and forestry (LULUCF).   The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.
    • June 2019
      Source: United Nations Framework Convention on Climate Change
      Uploaded by: Knoema
      Accessed On: 02 July, 2019
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  • I
    • May 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 May, 2019
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      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • January 2010
      Source: International Transport Forum
      Uploaded by: Knoema
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      These tables contain detailed data on Greenhouse Gas (GHG) emissions and carbon dioxide (CO2) emissions from fossil fuel combustion in member countries of the International Transport Forum and member countries of OECD. Data on greenhouse gas emissions (and CO2 emissions in particular) come from national reports to the United Nations Framework Convention on Climate Change (UNFCCC) and from the International Energy Agency (IEA). UNFCCC and IEA emissions data are based on the default methods and emissions factors from the Revised 1996 IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories. CO2 emissions from international aviation and international maritime transport are included in national totals allocated on the basis of fuel sales. There is, however, no internationally agreed allocation methodology for these sectors as of yet.
  • L
    • September 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 September, 2019
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      Land resources are one of the four components of the natural environment: water, air, land and living resources. In this context land is both: a physical "milieu" necessary for the development of natural vegetation as well as cultivated vegetation; a resource for human activities. The data presented here give information concerning land use state and changes (e.g. agricultural land, forest land). Land area excludes area under inland water bodies (i.e. major rivers and lakes). Arable refers to all lan generally under rotation, whether for temporary crops (double-cropped areas are counted only once) or meadows, or left fallow (less than five years). These data are not meant to indicate the amount of land that is potentially cultivable. Permanent crops are those that occupy land for a long period and do not have to be planted for several years after each harvest (e.g. cocoa, coffee, rubber). Land under vines and trees and shrubs producing fruits, nuts and flowers, such as roses and jasmine, is so classified, as are nurseries (except those for forest trees, which should be classified under "forests and other wooded land"). Arable and permanent crop land is defined as the sum of arable area and land under permanent crops. Permanent meadows and pastures refer to land used for five years or more to grow herbaceous forage crops, either cultivated or growing wild (wild prairie or grazing land). Forest refers to land spanning more than 0.5 hectare (0.005 km2) and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. This includes land from which forests have been cleared but that will be reforested in the foreseeable future. This excludes woodland or forest predominantly under agricultural or urban land use and used only for recreation purposes. Other areas include built-up and related land, wet open land, and dry open land, with or without vegetation cover. Areas under inland water bodies (rivers and lakes) are excluded. The definitions used in different countries may show variations.
    • February 2018
      Source: Global CCS Institute
      Uploaded by: Shakthi Krishnan
      Accessed On: 15 February, 2018
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      Data cited at: The Global CCS Institute https://www.globalccsinstitute.com Publication URL: http://www.globalccsinstitute.com/projects/large-scale-ccs-projects#map License: https://creativecommons.org/licenses/by-nc/4.0/   Globally, there are 15 large-scale CCS projects in operation, with a further seven under construction. The 22 projects in operation or under construction represents a doubling since the start of this decade. The total CO2 capture capacity of these 22 projects is around 40 million tonnes per annum (Mtpa). There are another 10 large-scale CCS projects at the most advanced stage of development planning, the Concept Definition (or Define) stage, with a total CO2 capture capacity of around 14 Mtpa. A further 12 large-scale CCS projects are in earlier stages of development planning (the Evaluate and Identify stages) and have a total CO2 capture capacity of around 25 Mtpa. Two large-scale CCS projects became operational in 2015:The Quest project, located in Alberta, Canada (CO2 capture capacity of approximately 1 Mtpa) was launched in November 2015. The project, involving the manufacture of hydrogen for upgrading bitumen into synthetic crude oil, is North America’s first large-scale CCS project to store CO2 exclusively in a deep saline formation.The Uthmaniyah CO2-EOR Demonstration Project, located in the Kingdom of Saudi Arabia was launched in July 2015. The project is capable of capturing around 0.8 Mtpa of CO2 from the Hayiwah NGL (natural gas liquids) Recovery Plant. Two more industrial CCS projects are expected to become operational in early 2016:The Illinois Industrial CCS Project (CO2 capture capacity of 1 Mtpa) is located at the Archer Daniel Midlands corn-to-ethanol production facility in Decatur, Illinois (United States). The project, the world’s first bio-CCS project at large scale, will be the first integrated CCS project in the United States to inject CO2 into a deep saline formation at a scale of 1 Mtpa.The Abu Dhabi CCS Project (CO2 capture capacity of 0.8 Mtpa), the world’s first iron and steel project to apply CCS at large scale, will involve CO2capture from the direct reduced iron process used at the Emirates Steel plant in Abu Dhabi. Large-scale CCS projects in the power sector are now a reality, demonstrated by:The world’s first large-scale power sector CCS project – the Boundary Dam Carbon Capture and Storage Project in Canada (CO2 capture capacity of 1 Mtpa) – becoming operational in October 2014.Commissioning activities on a new-build 582 megawatt (MW) power plant beginning at the Kemper County Energy Facility in Mississippi (United States, CO2 capture capacity of 3 Mtpa) with CO2 capture expected to commence around the middle of 2016.The Petra Nova Carbon Capture Project at the W.A. Parish power plant near Houston, Texas (US, CO2 capture capacity of 1.4 Mtpa) entering construction in July 2014, with CO2 capture anticipated by the end of 2016.
    • June 2012
      Source: Wikipedia
      Uploaded by: Carpe Facto
      Select Dataset
      Extremes in elevation across countries.
  • M
    • March 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 20 March, 2019
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Millennium Development Goals Publication: https://datacatalog.worldbank.org/dataset/millennium-development-goals License: http://creativecommons.org/licenses/by/4.0/   Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Millennium Development Goals (MDGs). The MDGs focus the efforts of the world community on achieving significant, measurable improvements in people's lives by the year 2015: they establish targets and yardsticks for measuring development results. Gender Parity Index (GPI)= Value of indicator for Girls/ Value of indicator for Boys. For e.g GPI=School enrolment for Girls/School enrolment for Boys. A value of less than one indicates differences in favor of boys, whereas a value near one (1) indicates that parity has been more or less achieved. The greater the deviation from 1 greater the disparity is.
    • December 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 December, 2018
      Select Dataset
      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) and ground-level ozone (O3) have 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. Exposure to ground-level ozone (O3) has serious consequences for human health, contributing to, or triggering, respiratory diseases. These include breathing problems, asthma and reduced lung function (WHO, 2016; Brauer et al., 2016). Ozone exposure is highest in emission-dense countries with warm and sunny summers. The most important determinants are background atmospheric chemistry, climate, anthropogenic and biogenic emissions of ozone precursors such as volatile organic compounds, and the ratios between different emitted chemicals.
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 October, 2019
      Select Dataset
      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat). They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences. This dataset presents trends in amounts of municipal (including household waste), and the treatment and disposal method used. The amount of waste generated in each country is related to the rate of urbanisation, the types and pattern of consumption, household revenue and lifestyles.
  • O
    • November 2018
      Source: Ocean Health Index
      Uploaded by: Shakthi Krishnan
      Accessed On: 23 November, 2018
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      Ocean Health Index
    • February 2012
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Select Dataset
      The data presented here refer to the latest year available, which corresponds to the late 2000s for most countries. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. The data presented here show numbers of known species and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians and vascular plants.
    • February 2012
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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      This dataset covers the uses of wildlife resources and related pressures from human activities: fish production; catches of fish and other aquatic animals and products and the management of wildlife resources: biosphere reserves and wetlands of international importance; major protected areas.
    • November 2008
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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      Dataset provides information on selected economic aspects of environmental management. It includes tables on expenditure, which help to identify the financial consequences of environmental policies: public and private pollution abatement and control expenditure; public research and development financing for environmental protection; official development assistance, including aid in support of environment. Dataset also includes data concerning revenues from environmentally-related taxes.
    • August 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 August, 2014
      Select Dataset
      As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They can also help the understanding and analysis of the environmental effects of future policy scenarios and agricultural projections. To help improve measurement of the environmental performance of agriculture, OECD has established a set of agri-environmental indicators, with development of the indicators in cooperation with Eurostat and FAO. These indicators inform policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis.
  • P
  • R
    • September 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 September, 2019
      Select Dataset
      The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).
  • S
    • April 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 April, 2019
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    • June 2019
      Source: Sustainable Development Solutions Network
      Uploaded by: Knoema
      Accessed On: 09 July, 2019
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      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 2019 SDG Index and Dashboards report presents a revised and updated assessment of countries’ distance to achieving the Sustainable Development Goals (SDGs). It includes detailed SDG Dashboards to help identify implementation priorities for the SDGs. The report also provides a ranking of countries by the aggregate SDG Index of overall performance.
  • T
    • March 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 May, 2019
      Select Dataset
      The data presented here refer to the latest year available. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. Species assessed as Critically Endangered (CR), Endangered (EN), or Vulnerable (VU) are referred to as "threatened" species. Reporting the proportion of threatened species on The IUCN Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the % threatened species would likely be an overestimate). The data presented here show numbers of known species (or assessed) and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians, vascular plants, mosses, lichens and invertebrates.
    • December 2018
      Source: PBL Netherlands Environmental Assessment Agency
      Uploaded by: Knoema
      Accessed On: 21 December, 2018
      Select Dataset
      Data Cited at: PBL Netherlands Environmental Assessment Agency   Trends in Global CO2 and Greenhouse Gas Emissions: 2018 Report   Notes: CO2 equivalent berekend met Global Warming Potentials (GWP-100) van het Vierde IPCC Fourth Assessment report (2017). CO2 equivalent calculated with Global Warming Potentials (GWP-100) of the Fourth IPCC Assessment report (2017).
  • U
    • June 2015
      Source: United Nations Environment Programme
      Uploaded by: Knoema
      Accessed On: 30 June, 2016
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      The GEO Data Portal is the authoritative source for data sets used by UNEP and its partners in the Global Environment Outlook (GEO) report and other integrated environment assessments. The GEO Data Portal gives access to a broad socio-economic data sets from authoritative sources at global, regional, sub-regional and national levels. The contents of the Data Portal cover environmental themes such as climate, forests and freshwater and many others, as well as socioeconomic categories, including education, health, economy, population and environmental policies.
  • W
    • October 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 08 October, 2019
      Select Dataset
      This dataset provides information on the level of public equipment installed by countries to managed and abate water pollution. It shows the percentage of national population connected to "public" sewerage networks and related treatment facilities, and the percentage of national population connected to "public" wastewater treatment plants, and the degree of treatment. Connected here means actually connected to a wastewater plants through a public sewage network. Individual private treatment facilities such as septic tanks are not covered here. When analysing these data, it should be kept in mind that the optimal connection rate is not necessarily 100 per cent; it may vary among countries and depends on geographical features and on the spatial distribution of habitats. The interpretation of those data should take into account some variations in countries' definitions, as reflected in metadata.
    • August 2018
      Source: EarthEcho Water Challenge
      Uploaded by: Knoema
      Accessed On: 22 August, 2018
      Select Dataset
      The pH of pure water is 7. In general, water with a pH lower than 7 is considered acidic, and with a pH greater than 7 is considered basic. The normal range for pH in surface water systems is 6.5 to 8.5, and the pH range for groundwater systems is between 6 to 8.5.
    • July 2019
      Source: World Bank
      Uploaded by: Sandeep Reddy
      Accessed On: 22 August, 2019
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      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.
    • November 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 06 November, 2019
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      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

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