基于WRF–CMAQ的晋城市PM<sub>2.5</sub>与O<sub>3</sub>复合污染协同控制

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摘要利用WRF-CMAQ模式对晋城市一次复合污染事件进行了模拟和源解析.通过设计49组不同比例的VOCs和NO_x减排情景,并结合EKMA曲线评估其前体物的科学减排比例.结果显示工业源和交通源是晋城市VOCs和NO_x的主要来源.O₃污染主要由NO_x控制,而PM_2.5污染则主要由VOCs控制.不考虑极端减排情景,仅针对O₃污染时,最佳的VOCs/NO_x减排比例为1:2;仅针对PM_2.5污染时,最佳减排比例为2:1.综合考虑PM_2.5和O₃的协同治理时,最佳前体物VOCs/NO_x减排比为2:1.

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	李晨
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	陈曦
	叶翠平

关键词 ： PM_2.5, O₃, 协同控制, WRF-CMAQ, EKMA曲线

Abstract：This study used the WRF-CMAQ model to simulate and conduct source apportionment for a case of compound pollution in Jinzhong City. By designing 49 different scenarios of VOCs and NO_x emission reductions and combining them with EKMA curves to evaluate the scientific reduction ratios of their precursors. The results revealed that industrial and traffic sources are the main contributors to VOCs and NO_x in Jincheng City. O₃ pollution is mainly influenced by NO_x levels, whereas PM_2.5 pollution is primarily controlled by VOCs. Considering non-extreme reduction scenarios, for O₃ pollution control alone, the optimal VOCs/NO_x reduction ratio is 1:2; for PM_2.5 pollution control alone, the optimal reduction ratio is 2:1. When considering the coordinated control of both PM_2.5 and O₃ pollution, the best precursor reduction ratio of VOCs to NO_x is 2:1.

Key words： PM_2.5 O₃ collaborative control WRF-CMAQ EKMA curve

收稿日期: 2024-05-26

PACS:

X51

基金资助:山西省基础研究计划项目(202203021212202);太原市生态环境局委托项目(RH2400000292)

通讯作者: 叶翠平,教授,yecuiping@tyut.edu.cn E-mail: yecuiping@tyut.edu.cn

作者简介: 李晨(1998-),男,山西运城人,硕士,主要从事大气污染控制和数值模拟研究.发表论文1篇.lichen1178@163.com.

引用本文:

李晨, 张芝娟, 陈曦, 叶翠平. 基于WRF–CMAQ的晋城市PM_2.5与O₃复合污染协同控制[J]. 中国环境科学, 2024, 44(12): 6569-6577. LI Chen, ZHANG Zhi-juan, CHEN Xi, YE Cui-ping. Coordinated control of PM_2.5 and O₃ compound pollution in Jincheng City based on the WRF-CMAQ model. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(12): 6569-6577.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2024/V44/I12/6569

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