Verification of anthropogenic emissions of China by satellite and ground observations

CMAQ 臭氧监测仪 环境科学 中分辨率成像光谱仪 大气科学 对流层 排放清单 北京 空气质量指数 卫星 化学输运模型 气溶胶 光谱辐射计 中国 气象学 气候学 地理 地质学 航空航天工程 考古 工程类 物理 光学 反射率
作者
Shuxiao Wang,Jia Xing,Satoru Chatani,Jiming Hao,Zbigniew Klimont,J. Cofała,Markus Amann
出处
期刊:Atmospheric Environment [Elsevier]
卷期号:45 (35): 6347-6358 被引量:137
标识
DOI:10.1016/j.atmosenv.2011.08.054
摘要

An integrated emission inventory of China was validated through comparing the Community Multi-scale Air Quality (CMAQ) simulations with the NO2 and SO2 column retrieved from Ozone Monitoring Instrument (OMI), Aerosol Optical Depth (AOD) retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS), and ground observations of SO2, NO2, PM10, PM2.5 and its components. The model simulations were performed for year 2005. The model generally reproduces both spatial distribution and seasonal variation of tropospheric NO2, SO2 column densities and AOD in China that have been observed by OMI and MODIS. The correlation coefficients between model simulated and satellite observed NO2 column densities, SO2 column densities and AOD over east China are 0.90, 0.85 and 0.79, and the normalized mean bias (NMBs) are −8%, 1%, and −8% respectively, which are comparable with the errors from satellite retrievals. The surface concentrations of NO2, SO2, and PM10 given by CMAQ model are also comparable with those observed in Beijing, Shanghai, and Guangzhou, with the NMBs ranging from 1% to 18%, −3% to −25%, and −12% to 18%, respectively. The results suggest that the anthropogenic emissions of SO2, NOx, and PM10 used in this study are in line with both the satellite and ground observations therefore are of acceptable accuracy. There is overestimation for SO2 and underestimation for PM10 in some industry-intensive areas because of the inaccuracy of spatial and temporal allocations. The CMAQ model also significantly underestimates the PM2.5 concentration in Beijhjing, mainly due to the limitation of secondary organic aerosol (SOA) formation mechanism used in the model and the underestimation of primary OC and EC emissions. Therefore more efforts shall be made to improve the primary emission estimates of OC and EC, as well as the temporal allocation factor of SO2 and PM10 emissions.

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