Articles | Volume 16, issue 10
https://doi.org/10.5194/acp-16-6395-2016
https://doi.org/10.5194/acp-16-6395-2016
Research article
 | 
25 May 2016
Research article |  | 25 May 2016

Limitations of ozone data assimilation with adjustment of NOx emissions: mixed effects on NO2 forecasts over Beijing and surrounding areas

Xiao Tang, Jiang Zhu, ZiFa Wang, Alex Gbaguidi, CaiYan Lin, JinYuan Xin, Tao Song, and Bo Hu

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Cited articles

Beekmann, M. and Derognat, C.: Monte Carlo uncertainty analysis of a regional-scale transport chemistry model constrained by measurements fromthe Atmospheric Pollution Over the Paris Area (ESQUIF) campaign, J. Geophys. Res., 108, 8559, https://doi.org/10.1029/2003JD003391, 2003.
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Carmichael, G., Chai, T., Sandu, A., Constantinescu, E., and Daescu, D.: Predicting air quality: Improvements through advanced methods to integrate models and measurements, J. Comput. Phys., 227, 3540–3571, 2008.
Constantinescu, E. M., Sandu, A., Chai, T. F., and Carmichael, G. R.: Ensemble-based chemical data assimilation. II: Covariance localization, Q. J. Roy. Meteor. Soc., 133, 1245–1256, 2007.
Eben, K., Jurus, P., Resler, J., Belda, M., Pelikan, E., Kruger, B. C., and Keder, J.: An ensemble Kalman filter for short-term forecasting of tropospheric ozone concentrations, Q. J. Roy. Meteor. Soc., 131, 3313–3322, 2005.
Short summary
Chemical data assimilation through adjusting precursor emissions has brought out notable impacts on improving ozone forecasts in previous studies. This paper, from another point of view, investigated in detail the impacts of adjusting nitrogen oxide emissions on the forecasts of nitrogen dioxide through assimilating ozone observations. Limitations of the existing chemical data assimilation methods in a highly nonlinear system were identified and highlighted.
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