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 (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). 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 concentration estimates are taken from the Global Burden of Disease (GBD) 2017 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 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.
The city definition used is the OECD Functional Urban Area (2018, forthcoming).
The accuracy of these exposure estimates varies considerably by location. Inaccuracy is particularly high in areas with few monitoring stations and in areas with very high concentrations. Accuracy is generally good in regions with dense monitoring station networks (such as most advanced economies). See Shaddick et al. (2018) for further details.
References:
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: 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 2017 (corresponding publication is forthcoming).
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-ghs_pop_gpw4_globe_r2015a
OECD Functional Urban Areas (2018, forthcoming update)
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
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
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 (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). 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 concentration estimates are taken from the Global Burden of Disease (GBD) 2017 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 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.
The city definition used is the OECD Functional Urban Area (2018, forthcoming).
The accuracy of these exposure estimates varies considerably by location. Inaccuracy is particularly high in areas with few monitoring stations and in areas with very high concentrations. Accuracy is generally good in regions with dense monitoring station networks (such as most advanced economies). See Shaddick et al. (2018) for further details.
References:
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: 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 2017 (corresponding publication is forthcoming).
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-ghs_pop_gpw4_globe_r2015a
OECD Functional Urban Areas (2018, forthcoming update)
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
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