Estimating ground-level PM<sub>2.5</sub> in eastern China using aerosol optical depth determined from the GOCI satellite instrument

Abstract

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = −0.52 %) and Beijing (MFB = −8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m−3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

“…These limitations of ground measurements result in insufficient information to conduct studies about pollution sources, distribution, and consequent health impacts. Satellites provide continuous, high-coverage observations of aerosol loadings and various approaches have been developed to estimate ground-level PM concentrations from satellite retrievals (Ma et al, 2014;Xu et al, 2015). Estimates of ground-level PM concentrations from satellite observations have been used in epidemiological studies and benefited policy making (Strickland et al, 2015;Evans et al, 2013).…”

Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea

“…Satellite-based PM monitoring has the potential to provide information on air quality over vast areas at high spatial resolution. Many studies have examined the use of satellitebased products to estimate surface PM concentrations (Liu et al, 2005;Gupta and Christopher, 2009a, b;Van Donkelaar et al, 2010Chudnovsky et al, 2014;Li et al, 2015;Xu et al, 2015a;You et al, 2015;Wu et al, 2016). AOD is the most widely used parameter that can be derived from satellite remote sensing to estimate ground-level PM concentrations.…”

“…AOD produced from geostationary satellite sensor systems may be a better option for estimating ground-level PM concentrations due to it having a higher temporal resolution than polar orbiting sensor systems. The Geostationary Ocean Color Imager (GOCI) is the world's first geostationary ocean color satellite sensor that provides multispectral aerosol data in northeast Asia (included eastern China, the Korea peninsula, and Japan) (Park et al, 2014;Xu et al, 2015a). GOCI provides hourly data at 500 m resolution eight times a day from 09:00 to 16:00 Korean Standard Time (KST).…”

Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

“…There are extensive studies investigating the PM2.5-AOD relationship by the use of either an empirical statistical method (Engel-Cox et al, 2004;Liu et al, 2005Liu et al, , 2009Gupta et al, 2006;Koelemeijer et al, 2006;Gupta and Christopher, 2008;Paciorek et al, 2008;Di Nicolantonio et al, 2009;Schaap et al, 2009;Lee et al, 2012;Sorek-Hamer et al, 2013;Strawa et al, 2013;Chudnovsky et al, 2014;Ma et al, 2014) or a chemical transportation model (Liu et al, 2004;Van Donkelaar et al, 2006Kessner et al, 2013;Xu et al, 2015). In these studies, aerosol vertical distributions are estimated based on model simulation or under an assumption that aerosols are well mixed within the boundary layer and then decrease exponentially with height.…”