基于EnKF排放清单反演方法的关键影响参数评估与优化

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Abstract The ensemble Kalman filter (EnKF) emission inversion is one of the most widely used methods to evaluate air pollutant emission inventory, but its performance is influenced by various parameters. How to identify and optimize the important parameters is the key to ensure the reliability and efficiency of emission inventory inversion. In this study, we use the sensitivity technique to investigate the effects of the number of ensembles, localization radius, inflation factor, observed station density, and temporal resolution of observations on emission inversion for Chinese carbon monoxide (CO) emissions. The results show that the observed station density is the most important parameter affecting emission inversions. The difference in total inversed (CO) emissions in China with varying station densities approaches 34%. Simultaneously, the observed station density also influences the sensitivity of emission inversions to other parameters. As the station density drops, the sensitivity of emission inversion to the localization radius, the number of ensembles and inflation factor increases, while the sensitivity to the temporal resolution of observations diminishes; Therefore, in areas with sparse observations, the localization radius is the most influential inversion parameter, followed by the number of ensembles and the inflation factor; however, in areas with many observed stations, the localization radius and the temporal resolution of observations are the main influential parameters, while the inflation factor and the number of ensembles have relatively less influence. This study can be used to optimize parameters for emission at different scales. The following parameters are proposed for Chinese CO emission inversion (station density is 1.55/10⁴km²): the number of ensembles is 50, the localization radius is 100km, the maximum likelihood estimation (MLE) inflation method, and the daily average or hourly observational data.

Key words： Ensemble Kalman Filter (EnKF) emission inversion parameter evaluation the station density localization radius

Received: 24 January 2022

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X511

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	Articles by authors
	ZHENG Chuan-zeng
	JIA Guang-lin
	YU Yu-fan
	LU Meng-hua
	WANG Zi-fa
	TANG Xiao
	WU Huang-jian
	HUANG Zhi-jiong
	ZHENG Jun-yu

Cite this article:

ZHENG Chuan-zeng,JIA Guang-lin,YU Yu-fan等. A study on evaluation and optimization about key effect parameters of emission inventory inversion method based on EnKF[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(9): 4043-4051.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I9/4043

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