An investigation into seasonal and regional aerosol characteristics in East Asia using model-predicted and remotely-sensed aerosol properties
- 1Dept. of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea
- 2Hazardous Substance Research Center, Korea Institute of Science and Technology (KIST), Seoul, Korea
- 3Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, MD 20742, USA
- 4Department of Atmospheric Science, Yonsei University, Seoul, Korea
- 5Department of Environmental Science, Hankuk University of Foreign Studies, Yongin-si, Gyeonggi-do, Korea
- *also at: Advanced Environmental Monitoring Research Center (ADEMRC), Gwangju Institute of Science and Technology (GIST), Gwangju, Korea
Abstract. In this study, the spatio-temporal and seasonal distributions of EOS/Terra Moderate Resolution Imaging Spectroradiometer (MODIS)-derived aerosol optical depth (AOD) over East Asia were analyzed in conjunction with US EPA Models-3/CMAQ v4.3 modeling. In this study, two MODIS AOD products (τMODIS: τM-BAER and τNASA) retrieved through a modified Bremen Aerosol Retrieval (M-BAER) algorithm and NASA collection 5 (C005) algorithm were compared with the AOD (τCMAQ) that was calculated from the US EPA Models-3/CMAQ model simulations. In general, the CMAQ-predicted AOD values captured the spatial and temporal variations of the two MODIS AOD products over East Asia reasonably well. Since τMODIS cannot provide information on the aerosol chemical composition in the atmosphere, different aerosol formation characteristics in different regions and different seasons in East Asia cannot be described or identified by τMODIS itself. Therefore, the seasonally and regionally varying aerosol formation and distribution characteristics were investigated by the US EPA Models-3/CMAQ v4.3 model simulations. The contribution of each particulate chemical species to τMODIS and τCMAQ showed strong spatial, temporal and seasonal variations. For example, during the summer episode, τMODIS and τCMAQ were mainly raised due to high concentrations of (NH4)2SO4 over Chinese urban and industrial centers and secondary organic aerosols (SOAs) over the southern parts of China, whereas during the late fall and winter episodes, τMODIS and τCMAQ were higher due largely to high levels of NH4NO3 formed over the urban and industrial centers, as well as in areas with high NH3 emissions. τCMAQ was in general larger than τMODIS during the year, except for spring. The high biases (τCMAQ>τMODIS) may be due to the excessive formation of both (NH4)2SO4 (summer episode) and NH4NO3 (fall and winter episodes) over China, possibly from the use of overestimated values for NH3 emissions in the CMAQ modeling. According to CMAQ modeling, particulate NH4NO3 made a 14% (summer) to 54% (winter) contribution to σext and τCMAQ. Therefore, the importance of NH4NO3 in estimating τ should not be ignored, particularly in studies of the East Asian air quality. In addition, the accuracy of τM-BAER and τNASA was evaluated by a comparison with the AOD (τAERONET) from the AERONET sites in East Asia. Both τM-BAER and τNASA showed a strong correlation with τAERONET around the 1:1 line (R=0.79), indicating promising potential for the application of both the M-BAER and NASA aerosol retrieval algorithms to satellite-based air quality monitoring studies in East Asia.