TY - JOUR
T1 - Estimating long-term PM2.5 concentrations in China using satellite-based aerosol optical depth and a chemical transport model
AU - Geng, Guannan
AU - Zhang, Qiang
AU - Martin, Randall V.
AU - van Donkelaar, Aaron
AU - Huo, Hong
AU - Che, Huizheng
AU - Lin, Jintai
AU - He, Kebin
N1 - Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Epidemiological and health impact studies of fine particulate matter (PM2.5) have been limited in China because of the lack of spatially and temporally continuous PM2.5 monitoring data. Satellite remote sensing of aerosol optical depth (AOD) is widely used in estimating ground-level PM2.5 concentrations. We improved the method for estimating long-term surface PM2.5 concentrations using satellite remote sensing and a chemical transport model, and derived PM2.5 concentrations over China for 2006-2012. We generated a map of surface PM2.5 concentrations at 0.1°×0.1° over China using the nested-grid GEOS-Chem model, most recent bottom-up emission inventory, and satellite observations from the MODIS and MISR instruments. Aerosol vertical profiles from the space-based CALIOP lidar were used to adjust the climatological drivers of the bias in the simulated results, and corrections were made for incomplete sampling. We found significant spatial agreement between the satellite-derived PM2.5 concentrations and the ground-level PM2.5 measurements collected from literatures (r=0.74, slope=0.77, intercept=11.21μg/m3). The population-weighted mean of PM2.5 concentrations in China is 71μg/m3 and more than one billion people live in locations where PM2.5 concentrations exceed the World Health Organization Air Quality Interim Target-1 of 35μg/m3. The results from our work are substantially higher than previous work, especially in heavily polluted regions. The overall population-weighted mean uncertainty over China is 17.2μg/m3, as estimated using ground-level AOD measurements and vertical profiles observed from CALIOP.
AB - Epidemiological and health impact studies of fine particulate matter (PM2.5) have been limited in China because of the lack of spatially and temporally continuous PM2.5 monitoring data. Satellite remote sensing of aerosol optical depth (AOD) is widely used in estimating ground-level PM2.5 concentrations. We improved the method for estimating long-term surface PM2.5 concentrations using satellite remote sensing and a chemical transport model, and derived PM2.5 concentrations over China for 2006-2012. We generated a map of surface PM2.5 concentrations at 0.1°×0.1° over China using the nested-grid GEOS-Chem model, most recent bottom-up emission inventory, and satellite observations from the MODIS and MISR instruments. Aerosol vertical profiles from the space-based CALIOP lidar were used to adjust the climatological drivers of the bias in the simulated results, and corrections were made for incomplete sampling. We found significant spatial agreement between the satellite-derived PM2.5 concentrations and the ground-level PM2.5 measurements collected from literatures (r=0.74, slope=0.77, intercept=11.21μg/m3). The population-weighted mean of PM2.5 concentrations in China is 71μg/m3 and more than one billion people live in locations where PM2.5 concentrations exceed the World Health Organization Air Quality Interim Target-1 of 35μg/m3. The results from our work are substantially higher than previous work, especially in heavily polluted regions. The overall population-weighted mean uncertainty over China is 17.2μg/m3, as estimated using ground-level AOD measurements and vertical profiles observed from CALIOP.
KW - Aerosol optical depth
KW - Particulate matter
KW - Satellite remote sensing
UR - https://www.scopus.com/pages/publications/84937969138
U2 - 10.1016/j.rse.2015.05.016
DO - 10.1016/j.rse.2015.05.016
M3 - Article
AN - SCOPUS:84937969138
SN - 0034-4257
VL - 166
SP - 262
EP - 270
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
ER -