caa a22 4500 445300892 CHVBK 20180317142557.0 cr unu---uuuuu 170323e20100501xx s 000 0 eng 10.1007/s11430-010-0044-9 doi (NATIONALLICENCE)springer-10.1007/s11430-010-0044-9 An emission source inversion model based on satellite data and its application in air quality forecasts [Elektronische Daten] [XingHong Cheng, XiangDe Xu, GuoAn Ding] This paper aims at constructing an emission source inversion model using a variational processing method and adaptive nudging scheme for the Community Multiscale Air Quality Model (CMAQ) based on satellite data to investigate the applicability of high resolution OMI (Ozone Monitoring Instrument) column concentration data for air quality forecasts over the North China. The results show a reasonable consistency and good correlation between the spatial distributions of NO2 from surface and OMI satellite measurements in both winter and summer. Such OMI products may be used to implement integrated variational analysis based on observation data on the ground. With linear and variational corrections made, the spatial distribution of OMI NO2 clearly revealed more localized distributing characteristics of NO2 concentration. With such information, emission sources in the southwest and southeast of North China are found to have greater impacts on air quality in Beijing. When the retrieved emission source inventory based on high-resolution OMI NO2 data was used, the coupled Weather Research Forecasting CMAQ model (WRF-CMAQ) performed significantly better in forecasting NO2 concentration level and its tendency as reflected by the more consistencies between the NO2 concentrations from surface observation and model result. In conclusion, satellite data are particularly important for simulating NO2 concentrations on urban and street-block scale. High-resolution OMI NO2 data are applicable for inversing NOx emission source inventory, assessing the regional pollution status and pollution control strategy, and improving the model forecasting results on urban scale. Science China Press and Springer-Verlag Berlin Heidelberg, 2010 OMI NO2 product nationallicence variational processing method nationallicence emission source inversion model nationallicence CMAQ nationallicence air quality forecast nationallicence Cheng XingHong Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut Xu XiangDe Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut Ding GuoAn Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut Science China Earth Sciences SP Science China Press 53/5(2010-05-01), 752-762 1674-7313 53:5<752 2010 53 11430 https://doi.org/10.1007/s11430-010-0044-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11430-010-0044-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cheng XingHong Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut NATIONALLICENCE 700 1- Xu XiangDe Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut NATIONALLICENCE 700 1- Ding GuoAn Chinese Academy of Meteorological Sciences, 100081, Beijing, China aut NATIONALLICENCE 773 0- Science China Earth Sciences SP Science China Press 53/5(2010-05-01), 752-762 1674-7313 53:5<752 2010 53 11430 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer