globalchange  > 气候变化与战略
DOI: 10.1016/j.atmosenv.2020.117631
论文题名:
High-spatiotemporal-resolution inverse estimation of CO and NOx emission reductions during emission control periods with a modified ensemble Kalman filter
作者: Wu H.; Tang X.; Wang Z.; Wu L.; Li J.; Wang W.; Yang W.; Zhu J.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 236
语种: 英语
英文关键词: Air quality ; Carbon monoxide ; Emission control ; Inverse problems ; Nitrogen oxides ; Quality control ; Uncertainty analysis ; Control strategies ; Decoupling analysis ; Emission estimation ; Emission inventories ; Ensemble Kalman Filter ; Ensemble simulation ; Observing system simulation experiments ; Spatio-temporal resolution ; Kalman filters ; air quality ; carbon monoxide ; emission control ; emission inventory ; estimation method ; Kalman filter ; nitrous oxide ; simulation ; spatiotemporal analysis ; uncertainty analysis ; China
学科: Beijing-Tianjin-Hebei ; Emission control ; Ensemble Kalman filter ; Inverse estimation
中文摘要: Emission control strategies are among the most effective ways to improve air quality, but the emissions reduced were usually estimated with high uncertainty. Here we present a modified ensemble Kalman filter (EnKF) to reduce the uncertainties of carbon monoxide (CO) and nitrogen oxides (NOx) emissions at one week and 5 km resolution by assimilating surface CO and nitrogen dioxide (NO2) observations. By decoupling analysis steps from ensemble simulations, the modified EnKF avoids filter divergence and enables reuse of costly ensemble simulations, making high-spatiotemporal-resolution inversion affordable. This method is tested by a set of observing system simulation experiments. By assimilating synthetic observations from 400 sites, the errors of CO and NOx emissions over Beijing-Tianjin-Hebei (BTH) in the a priori emission inventory are reduced by 78% and 76%, respectively. Further application of this method estimates the emission reductions during China's Victory day parade using real surface observations. The changes of the emissions in each city are identified by this method, which suggests that the CO and NOx emissions over BTH region during the parade are reduced by 36% and 44%, respectively. Using the inversed emission inventory, the biases of CO and NO2 simulations during the parade are reduced by 95% and 91%, respectively. This highlights the potentials of this method for improving high-spatiotemporal-resolution emission estimation. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160251
Appears in Collections:气候变化与战略

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作者单位: State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Science, Beijing, 100049, China; Guanghua School of Management, Peking University, Beijing, 100029, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; China National Environmental Monitoring Center, Beijing, 100012, China; International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

Recommended Citation:
Wu H.,Tang X.,Wang Z.,et al. High-spatiotemporal-resolution inverse estimation of CO and NOx emission reductions during emission control periods with a modified ensemble Kalman filter[J]. Atmospheric Environment,2020-01-01,236
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