Estimating Long-term PM2.5 Concentrations in China using Satellite-Based Aerosol Optical Depth and a Chemical Transport Model

stimating long-term PM2.5 concentrations in China using satellite-based aerosol optical depth and a chemical transport model Guannan Geng a,b,c, Qiang Zhang a,⁎, Randall V. Martin b,d, Aaron van Donkelaar b,H o n gH u oe, Huizheng Che f, Jintai Lin g, Kebin He c a Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China b Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada c State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China d Harvard–Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA e Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084, China f Key Laboratory of Atmospheric Chemistry (LAC), Institute of Atmospheric Composition, Chinese Academy of Meteorological Science, Beijing 100081,China g Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China abstractarticle info Article history: Received 17 September 2014 Received in revised form 16 April 2015 Accepted 20 May 2015 Available online 9 June 2015 Keywords: Particulate matter Aerosol optical depth Satellite remote sensing Epidemiological and health impact studies offine 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 PM 2.5 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 PM 2.5 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 pro files 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 signi ficant spatial agreement between the satellite-derived PM 2.5 concentrations and the ground-level PM 2.5 measurements collected from literatures (r = 0.74, slope = 0.77, intercept = 11.21 μg/m3). The population-weighted mean of PM 2.5 concentrations in China is 71 μg/m3 and more than one billion people live in locations where PM 2.5 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 17.2 μg/m3, as estimated using ground-level AOD measurements and vertical profiles observed from CALIOP.