Data Characteristics
Data Characteristics Date last updated Date last updated Concepts & Classifications Concepts & Classifications Key statistical concept Key statistical conceptPopulation exposure to fine particles
Air pollution is one of the most pressing environmental and health issues across OECD countries and beyond.
Fine particulate matter (PM2.5) is the air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant. Chronic exposure considerably increases the risk of respiratory and cardiovascular diseases (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been selected as an OECD Green Growth headline indicator.
The underlying PM2.5 concentration estimates are taken from the Global Burden of Disease (GBD) 2019 project. They are derived by integrating satellite observations, chemical transport models and measurements from ground monitoring station networks.
The concentration estimates are population-weighted using gridded population datasets from the Joint Research Center Global Human Settlement project. These are produced by distributing census-derived population estimates from the Gridded Population of the World, version 4 from the NASA Socioeconomic Data and Applications Center according to the density and distribution of built-up areas.
For political and administrative boundaries, OECD (2020) territorial grid units are used where available, for the remaining countries, the FAO (2015) Global Administrative Unit Layers (GAUL 2014) are used (see below for details). The OECD (2020) Functional Urban Area definition is used for cities.
The share of exposure attributable to mineral dust and sea salt (Y2015 only) field should be regarded as approximate. It is calculated using the difference in exposure between the dust/no dust estimates from van Donkelaar et al. (2016).
The accuracy of these exposure estimates varies considerably by location. Accuracy is poorer in areas with few monitoring stations and in areas with very high concentrations such as Africa, the Middle-East and South Asia. Accuracy is generally good in regions with dense monitoring station networks (such as most advanced economies). See Shaddick et al. (2018) for further details.
Guideline values:
WHO provides air quality guidelines based on scientific evidence and expert advice. Such guidelines were first produced in 1987 and later updated in 1997, 2005 and 2021. The 2005 interim targets are retained in the updated air quality guidelines and a new interim target (i.e. interim target 4) is added since the AQG level is lowered:
Interim target-1 - 35 µg/m3: These levels are associated with about a 15% higher long-term mortality risk relative to the AQG level.
Interim target-2 - 25 µg/m3: In addition to other health benefits, these levels lower the risk of premature mortality by approximately 6% [2–11%] relative to the IT-1 level.
Interim target-3 - 15 µg/m3: In addition to other health benefits, these levels reduce the mortality risk by approximately 6% [2-11%] relative to the IT-2 level.
Interim target-4 - 10 µg/m3
Air quality guideline (AQG) - 5 µg/m3: These are the lowest levels at which total, cardiopulmonary and lung cancer mortality have been shown to increase with more than 95% confidence in response to long-term exposure to PM2.5.
Source: WHO (2021) WHO Air quality guidelines. Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. Available at: https://www.who.int/publications/i/item/9789240034228
References:
Wang, H. et al. (2020). Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), pp.1160-1203. https://doi.org/10.1016/S0140-6736(20)30977-6
Shaddick, G., Thomas, M., Amini, H., Broday, D.M., Cohen, A., Frostad, J., Green, A., Gumy, S., Liu, Y., Martin, R.V., Prüss-Üstün, A., Simpson, D., van Donkelaar, A., Brauer, M. (2018) Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. doi: http://doi.org/10.1021/acs.est.8b02864 - Note: This paper details the methodology for GBD 2015 and GBD 2016 exposure estimates, there have been minor changes for GBD 2019.
European Commission, Joint Research Centre (JRC); Columbia University, Center for International Earth Science Information Network - CIESIN (2015): GHS population grid, derived from GPW4, multitemporal (1990, 2000, 2015). European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/jrc-ghsl-ghspopgpw4glober2015a
FAO (2015), The Global Administrative Unit Layers (GAUL) 2014 dataset, implemented by FAO within the CountrySTAT and Agricultural Market Information System (AMIS) projects. Available at http://www.fao.org/geonetwork/srv/en/main.home.
WHO (2018) Factsheet on ambient air quality and health. Available at http://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health
Van Donkelaar, A., Martin, R. V., Brauer, M., Hsu, N. C., Kahn, R. A., Levy, R. C., ... & Winker, D. M. (2016). Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors. Environmental science & technology, 50(7), 3762-3772. http://dx.doi.org/10.1021/acs.est.5b05833 https://fizz.phys.dal.ca/~atmos/martin/?page_id=140
Mackie, A., I. Hašcic and M. Cárdenas Rodríguez (2016), "Population Exposure to Fine Particles: Methodology and Results for OECD and G20 Countries", OECD Green Growth Papers, No. 2016/02, OECD Publishing, Paris. http://dx.doi.org/10.1787/5jlsqs8g1t9r-en
Other notes
- Aggregate values are population-weighted
- OECD aggregate includes AUS, AUT, BEL, CAN, CHE, CHL, COL, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, GRC, HUN, IRL, ISL, ISR, ITA, JPN, KOR, LTU, LUX, LVA, MEX, NLD, NOR, NZL, POL, PRT, SVK, SVN, SWE, TUR, USA
- Large regions correspond to OECD territorial level 2 (TL2) or GAUL level 1 (GAUL 1). Small regions correspond to OECD territorial level 3 (TL3) or GAUL level 2 (GAUL 2).
- The boundary unit codes indicate the source and year of the definition used. OECDXXXX2020 means that boundary comes from the OECD's reference areas as of 2020, and the unique ID in the source dataset is XXXX. Similarly, GAUL1XXXX2015 means the boundaries come from GAUL 1 (2015) and the source GAUL id is XXXX. FUAs all come from the same dataset and simply use the unique ID from the source.
- PM2.5 exposure estimates from other sources but drawing on the same underlying concentration estimates may differ modestly due to differences in boundaries used and the population weighting performed.
- Aggregate values and large regions that correspond to GAUL level 1 (GAUL 1) have not been updated for the year 2020. Aggregate values will be updated mid-2023 when an update for 2021 and 2022 air pollution will be possible. Currently, large regions that correspond to GAUL level 1 will not be updated until further notice.
Population exposure to fine particles
Air pollution is one of the most pressing environmental and health issues across OECD countries and beyond.
Fine particulate matter (PM2.5) is the air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant. Chronic exposure considerably increases the risk of respiratory and cardiovascular diseases (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been selected as an OECD Green Growth headline indicator.
The underlying PM2.5 concentration estimates are taken from the Global Burden of Disease (GBD) 2019 project. They are derived by integrating satellite observations, chemical transport models and measurements from ground monitoring station networks.
The concentration estimates are population-weighted using gridded population datasets from the Joint Research Center Global Human Settlement project. These are produced by distributing census-derived population estimates from the Gridded Population of the World, version 4 from the NASA Socioeconomic Data and Applications Center according to the density and distribution of built-up areas.
For political and administrative boundaries, OECD (2020) territorial grid units are used where available, for the remaining countries, the FAO (2015) Global Administrative Unit Layers (GAUL 2014) are used (see below for details). The OECD (2020) Functional Urban Area definition is used for cities.
The share of exposure attributable to mineral dust and sea salt (Y2015 only) field should be regarded as approximate. It is calculated using the difference in exposure between the dust/no dust estimates from van Donkelaar et al. (2016).
The accuracy of these exposure estimates varies considerably by location. Accuracy is poorer in areas with few monitoring stations and in areas with very high concentrations such as Africa, the Middle-East and South Asia. Accuracy is generally good in regions with dense monitoring station networks (such as most advanced economies). See Shaddick et al. (2018) for further details.
Guideline values:
WHO provides air quality guidelines based on scientific evidence and expert advice. Such guidelines were first produced in 1987 and later updated in 1997, 2005 and 2021. The 2005 interim targets are retained in the updated air quality guidelines and a new interim target (i.e. interim target 4) is added since the AQG level is lowered:
Interim target-1 - 35 µg/m3: These levels are associated with about a 15% higher long-term mortality risk relative to the AQG level.
Interim target-2 - 25 µg/m3: In addition to other health benefits, these levels lower the risk of premature mortality by approximately 6% [2–11%] relative to the IT-1 level.
Interim target-3 - 15 µg/m3: In addition to other health benefits, these levels reduce the mortality risk by approximately 6% [2-11%] relative to the IT-2 level.
Interim target-4 - 10 µg/m3
Air quality guideline (AQG) - 5 µg/m3: These are the lowest levels at which total, cardiopulmonary and lung cancer mortality have been shown to increase with more than 95% confidence in response to long-term exposure to PM2.5.
Source: WHO (2021) WHO Air quality guidelines. Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. Available at: https://www.who.int/publications/i/item/9789240034228
References:
Wang, H. et al. (2020). Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), pp.1160-1203. https://doi.org/10.1016/S0140-6736(20)30977-6
Shaddick, G., Thomas, M., Amini, H., Broday, D.M., Cohen, A., Frostad, J., Green, A., Gumy, S., Liu, Y., Martin, R.V., Prüss-Üstün, A., Simpson, D., van Donkelaar, A., Brauer, M. (2018) Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. doi: http://doi.org/10.1021/acs.est.8b02864 - Note: This paper details the methodology for GBD 2015 and GBD 2016 exposure estimates, there have been minor changes for GBD 2019.
European Commission, Joint Research Centre (JRC); Columbia University, Center for International Earth Science Information Network - CIESIN (2015): GHS population grid, derived from GPW4, multitemporal (1990, 2000, 2015). European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/jrc-ghsl-ghspopgpw4glober2015a
FAO (2015), The Global Administrative Unit Layers (GAUL) 2014 dataset, implemented by FAO within the CountrySTAT and Agricultural Market Information System (AMIS) projects. Available at http://www.fao.org/geonetwork/srv/en/main.home.
WHO (2018) Factsheet on ambient air quality and health. Available at http://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health
Van Donkelaar, A., Martin, R. V., Brauer, M., Hsu, N. C., Kahn, R. A., Levy, R. C., ... & Winker, D. M. (2016). Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors. Environmental science & technology, 50(7), 3762-3772. http://dx.doi.org/10.1021/acs.est.5b05833 https://fizz.phys.dal.ca/~atmos/martin/?page_id=140
Mackie, A., I. Hašcic and M. Cárdenas Rodríguez (2016), "Population Exposure to Fine Particles: Methodology and Results for OECD and G20 Countries", OECD Green Growth Papers, No. 2016/02, OECD Publishing, Paris. http://dx.doi.org/10.1787/5jlsqs8g1t9r-en
Other notes
- Aggregate values are population-weighted
- OECD aggregate includes AUS, AUT, BEL, CAN, CHE, CHL, COL, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, GRC, HUN, IRL, ISL, ISR, ITA, JPN, KOR, LTU, LUX, LVA, MEX, NLD, NOR, NZL, POL, PRT, SVK, SVN, SWE, TUR, USA
- Large regions correspond to OECD territorial level 2 (TL2) or GAUL level 1 (GAUL 1). Small regions correspond to OECD territorial level 3 (TL3) or GAUL level 2 (GAUL 2).
- The boundary unit codes indicate the source and year of the definition used. OECDXXXX2020 means that boundary comes from the OECD's reference areas as of 2020, and the unique ID in the source dataset is XXXX. Similarly, GAUL1XXXX2015 means the boundaries come from GAUL 1 (2015) and the source GAUL id is XXXX. FUAs all come from the same dataset and simply use the unique ID from the source.
- PM2.5 exposure estimates from other sources but drawing on the same underlying concentration estimates may differ modestly due to differences in boundaries used and the population weighting performed.
- Aggregate values and large regions that correspond to GAUL level 1 (GAUL 1) have not been updated for the year 2020. Aggregate values will be updated mid-2023 when an update for 2021 and 2022 air pollution will be possible. Currently, large regions that correspond to GAUL level 1 will not be updated until further notice.