Articles | Volume 16, issue 2
Atmos. Chem. Phys., 16, 989–1002, 2016

Special issue: Haze-fog forecasts and near real time (NRT) data application...

Atmos. Chem. Phys., 16, 989–1002, 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 et al.

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Cited articles

Bond, T. C. and Bergstrom, R. W.: Light absorption by carbonaceous particles: An investigative review, Aerosol Sci. Technol., 40, 27–67,, 2006.
Cao, G., Zhang, X., and Zheng, F.: Inventory of black carbon and organic carbon emissions from China, Atmos. Environ., 40, 6516–6527,, 2006.
Evensen, G.: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte-Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10143–10162, 1994.
Fu, T.-M., Cao, J. J., Zhang, X. Y., Lee, S. C., Zhang, Q., Han, Y. M., Qu, W. J., Han, Z., Zhang, R., Wang, Y. X., Chen, D., and Henze, D. K.: Carbonaceous aerosols in China: top-down constraints on primary sources and estimation of secondary contribution, Atmos. Chem. Phys., 12, 2725–2746,, 2012.
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.
Final-revised paper