基于WRF–CMAQ的晋城市PM_(2.5)与O_(3)复合污染协同控制  

Coordinated control of PM_(2.5) and O_(3) compound pollution in Jincheng City based on the WRF-CMAQ model

作　　者：李晨[1] 张芝娟 陈曦[1,2] 叶翠平[1] LI Chen;ZHANG Zhi-juan;CHEN Xi;YE Cui-ping(College of Environment and Ecology,Taiyuan University of Technology,Jinzhong 030600,China;Shanxi Key Laboratory of Compound Air Pollutions Identification and Control,Jinzhong 030600,China)

机构地区：[1]太原理工大学环境与生态学院,山西晋中030600 [2]太原理工大学大气复合污染识别与控制山西省重点实验室,山西晋中030600

出　　处：《中国环境科学》2024年第12期6569-6577,共9页China Environmental Science

基　　金：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)。

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.O_(3)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O_(3)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O_(3)的协同治理时,最佳前体物VOCs/NO_(x)减排比为2:1.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.O_(3) pollution is mainly influenced by NO_(x) levels,whereas PM_(2.5) pollution is primarily controlled by VOCs.Considering non-extreme reduction scenarios,for O_(3) 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 O_(3) pollution,the best precursor reduction ratio of VOCs to NO_(x) is 2:1.

关 键 词：PM_(2.5) O_(3) 协同控制 WRF-CMAQ EKMA曲线 

分 类 号：X51[环境科学与工程—环境工程]