Inversion of CO emissions over Beijing and its surrounding areas with ensemble Kalman filter

Inversion of the carbon monoxide (CO) emissions over Beijing and surrounding areas in the summer of 2010 is carried on the Nested Air Quality Prediction Modeling System (NAQPMS) in coupling with an ensemble Kalman filter. CO emission is estimated through integration of observations data obtained fro...

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Bibliographic Details
Published in:Atmospheric environment (1994) 2013-12, Vol.81, p.676-686
Main Authors: Tang, X., Zhu, J., Wang, Z.F., Wang, M., Gbaguidi, A., Li, J., Shao, M., Tang, G.Q., Ji, D.S.
Format: Article
Language:English
Subjects:
Analysis methods
Applied sciences
Atmospheric pollution
Beijing
Carbon monoxide
CO emissions
Emission
Ensemble Kalman filter
Exact sciences and technology
Inventories
Inversion estimation
Inversions
Kalman filters
Mathematical models
Pollution
Regional
Stockpiling
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Summary:Inversion of the carbon monoxide (CO) emissions over Beijing and surrounding areas in the summer of 2010 is carried on the Nested Air Quality Prediction Modeling System (NAQPMS) in coupling with an ensemble Kalman filter. CO emission is estimated through integration of observations data obtained from 25 sites in Beijing and surrounding areas of which 13 sites selected as assimilation sites are used to perform a joint adjustment of both CO concentrations and emissions with hourly surface CO observations, and 12 other sites selected to validate the inversion emission inventory. As a result, estimated CO emissions (Tg year−1) for Beijing, Tianjin, Tangshan and Baoding are 4.11, 3.75, 3.17 and 4.08, respectively; higher than the a priori estimates in the Regional Emission inventory in Asia Version 1.1 (REAS V1.1) by 50%, 80%, 120% and 150% respectively. Obviously, the regional CO emissions are underestimated in REAS1.1, especially over Beijing and surrounding areas. Use of the inverse emission inventory reduces the bias of CO simulation by 64% at assimilation sites and 48% at validation sites. •Inverse emission estimation method based on ensemble Kalman filter is established.•Carbon monoxide (CO) emissions over Beijing and surrounding areas are estimated.•The biases in the a priori bottom-up emission inventory are identified.•The CO simulations are significantly improved using the inversion emission inventory.
ISSN:1352-2310
1873-2844
DOI:10.1016/j.atmosenv.2013.08.051