Development of GRAPES-CUACE adjoint model version 2.0 and its application in sensitivity analysis of ozone pollution in north China

被引:3
|
作者
Wang, Chao [1 ,2 ,3 ]
An, Xingqin [3 ]
Zhao, Defeng [1 ,2 ]
Sun, Zhaobin [4 ]
Jiang, Linsen [5 ]
Li, Jiangtao [3 ]
Hou, Qing [3 ]
机构
[1] Fudan Univ, Dept Atmospher & Ocean Sci, Songhu Rd Ave 2005, Shanghai 200438, Peoples R China
[2] Fudan Univ, Inst Atmospher Sci, Shanghai 200438, Peoples R China
[3] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China
[4] China Meteorol Adm, Inst Urban Meteorol, Beijing 100089, Peoples R China
[5] Chinese Acad Sci, Inst Elect Engn, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Adjoint modeling; Ozone; Sensitivity analysis; Ozone control strategy; Beijing; VARIATIONAL DATA ASSIMILATION; VOLATILE ORGANIC-COMPOUNDS; BEIJING-TIANJIN-HEBEI; NON-LINEAR SYSTEMS; AIR-QUALITY; SURFACE OZONE; METEOROLOGICAL INFLUENCES; ATMOSPHERIC CHEMISTRY; PRECURSOR EMISSIONS; GRID RESOLUTION;
D O I
10.1016/j.scitotenv.2022.153879
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We presented the development of the gaseous chemistry adjoint module of the meteorological-chemical model system GRAPES-CUACE (Global/Regional Assimilation and PrEdiction System coupled with CMA Unified Atmospheric Chemistry Environmental Forecasting System) on the basis of the previously constructed aerosol adjoint module. The latest version of the GRAPES-CUACE adjoint model mainly includes the adjoint of the physical and chemical processes, the adjoint of the transport processes, and the adjoint of interface programs, of both gas and aerosol. The adjoint implementation was validated for the full model, and adjoint results showed good agreement with brute force sensitivities. We also applied the newly developed adjoint model to the sensitivity analysis of an ozone episode occurred in Beijing on July 2, 2017, as well as the design of emission-reduction strategies for this episode. The relationships between the ozone concentration and precursor emissions were well captured by the adjoint model. It is indicated that for a case used here, the Beijing peak ozone concentration was influenced mostly by local emissions (6.2-24.3%), as well as by surrounding emissions, including Hebei (4.4-16.8%), Tianjin (1.8-6.6%), Shandong (1.8-2.6%), and Shanxi (< 1%). In addition, reduction of NOx, VOCs, and CO emissions in these regions would effectively decrease the Beijing peak ozone concentration. This study highlights the capability of GRAPES-CUACE adjoint model in quantifying "emission-concentration " relationship and in providing guidance for environmental control policy.
引用
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页数:15
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