Articles | Volume 16, issue 2
https://doi.org/10.5194/acp-16-989-2016
https://doi.org/10.5194/acp-16-989-2016
Research article
 | 
27 Jan 2016
Research article |  | 27 Jan 2016

Inverse modeling of black carbon emissions over China using ensemble data assimilation

P. Wang, H. Wang, Y. Q. Wang, X. Y. Zhang, S. L. Gong, M. Xue, C. H. Zhou, H. L. Liu, X. Q. An, T. Niu, and Y. L. Cheng

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AR by Ping Wang on behalf of the Authors (23 Dec 2015)  Author's response   Manuscript 
ED: Publish as is (06 Jan 2016) by Jørgen Brandt
AR by Ping Wang on behalf of the Authors (12 Jan 2016)  Manuscript 
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Short summary
An ensemble optimal interpolation (EnOI) data assimilation technique is used to investigate the possibility of optimally recovering the spatially resolved emissions bias of BC. The inversed emission over China in January is 240.1 Gg, and annual emission is about 2539 Gg. Even though only monthly mean BC measurements are employed to inverse the emissions, the accuracy of the daily model simulation improves. We finds that EnOI is a useful and computation-free method to make top-down estimation.
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