Organisation for Economic Co-operation and Development

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.

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.

This dataset contains bilateral commitment data on aid in support of environment sustainability and aid to biodiversity, climate change mitigation, climate change adaptation and desertification from the Development Assistance Committee (DAC) Creditor Reporting System (CRS) database. In their reporting to the DAC CRS, donors are requested to indicate for each activity whether or not it targets environment and the Rio Conventions (biodiversity, climate change mitigation, climate change adaptation and desertification). A scoring system of three values is used, in which aid activities are "marked" as targeting environment as the "principal objective" or a "significant objective", or as not targeting the objective. The environment marker identifies activities that are "intended to produce an improvement in the physical and/or biological environment of the recipient country, area or target group concerned" or "include specific action to integrate environmental concerns with a range of development objectives through institution building and/or capacity development". A large majority of activities targeting the objectives of the Rio Conventions fall under the DAC definition of "aid to environment". The Rio markers permit their specific identification.

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.

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).

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.

These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.

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.

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).