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Evolution of Estimates of Population Exposure to PM2.5
AMBIENT PM2.5 EXPOSURE The GBD studies estimate nationwide population exposure to ambient PM2.5 from a combination of satellite imagery, chemical-transport modeling, and ground-level PM2.5 and PM10 measurements. The evolution in satellite imagery/chemical transport model estimation techniques, the number of ground-level monitoring locations, and the method of calibrating the satellite imagery/chemical transport model estimates with the ground-level measurements has been quite substantial from the GBD 2010 study to the GBD 2019 study (Brauer et al. 2012, 2016; GBD 2019 Risk Factors Collaborators 2020; Shaddick et al. 2018; van Donkelaar et al. 2015, 2016). Ground-level measurements of PM2.5 or PM10 employed by the GBD 2010 study covered fewer than 700 locations (Brauer et al. 2012). This expanded to 4,073 data points from 3,387 unique locations in the GBD 2013 study (Brauer et al. 2016). The GBD 2015 and GBD 2016 studies utilized the WHO Global Ambient Air Quality Database 2016 containing PM measurements from 6,003 ground monitors in about 3,000 human settlements (GBD 2015 Risk Factors Collaborators 2016; GBD 2016 Risk Factors Collaborators 2017; WHO 2016). The GBD 2017 utilized the WHO updated database 2018 with PM10 and PM2.5 from about 9,690 stations in nearly 4,400 locations (defined geographic areas) in 108 countries (GBD 2017 Risk Factors Collaborators 2018). The GBD 2019 also utilized this updated database, along with additional measurement data mainly from Bangladesh, Canada, China, the European Union, the United States, and PM measurement data from US embassies and consulates. Thus, measurement data from 10,408 ground monitors from 116 countries were utilized by the GBD 2019 (GBD 2019 Risk Factors Collaborators 2020). Nevertheless, ground monitoring remains particularly scarce in low-income countries and Sub-Saharan Africa.
PM2.5 HOUSEHOLD AIR POLLUTION EXPOSURE The GBD 2019 study estimates population exposure to PM2.5 household air pollution from a combination of data on the percentage of countries’ population using solid fuels for cooking and a household exposure prediction model. 5