基于WRF-CMAQ模型的四川盆地春季持续臭氧污染过程中PM_(2.5)组分解析  

Analysis of PM_(2.5) Components During Continuous Spring Pollution in Sichuan Basin Based on WRF-CMAQ Model

作　　者：王聪聪 张小玲 雷雨 黄小娟 王婧怡 尹黎昊 王传扬 WANG Congcong;ZHANG Xiaoling;LEI Yu;HUANG Xiaojuan;WANG Jingyi;YIN Lihao;WANG Chuanyang(Plateau Atmosphere and Environment Key Laboratory of Sichuan Province/College of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu 610225,P.R.China;Tai’an Meteorological Bureau,Tai’an 271001,P.R.China;Chengdu Plain Urban Meteorology and Environment Field Scientific Observation and Research Station of Sichuan Province,Chengdu 610225,P.R.China;Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3)/Department of Environmental Science&Engineering/Institute of Atmospheric Sciences,Fudan University,Shanghai 200438,P.R.China.)

机构地区：[1]成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室,四川成都610225 [2]泰安市气象局,山东泰安271001 [3]成都平原城市气象与环境四川省野外科学观测研究站,四川成都610225 [4]复旦大学环境科学与工程系/上海市大气颗粒物污染防治重点实验室,上海200438

出　　处：《生态环境学报》2024年第8期1214-1226,共13页Ecology and Environmental Sciences

基　　金：国家重点研发计划课题(2023YFC3709301);国家自然科学基金项目(42205100);成都信息工程大学引进人才科研启动项目(KYTZ202127);成都信息工大学科技创新能力提升计划重大团队项目(KYTD202202)。

摘　　要：为探究四川盆地典型城市PM_(2.5)组分的污染特征及其与大气氧化性的关系,利用WRF-CMAQ模型对2020年春季一次持续O_(3)污染过程中PM_(2.5)组分进行模拟分析,并将O_(3,max)作为光化学活性指标,划分出轻、低、中3种光化学水平,对不同光化学水平下PM_(2.5)主要组分及贡献的变化特征。结果表明,四川盆地发生O_(3)污染期间,高空为稳定的天气形势或下沉气流,海平面气压场为高压,对应晴好天气,有利于光化学反应及O_(3)和二次气溶胶的生成。污染热点区域主要集中在成都平原和重庆西部,PM_(2.5)和NO_(2)的高浓度区与O_(3)污染发生的区域相吻合。污染前期,OC和NO_(3)^(-)对PM_(2.5)的贡献较大;污染后期,OC和SO_(4)^(2-)对PM_(2.5)的贡献较大。达州的NO_(3)^(-)和NH_(4)^(+)等离子在低光化学水平下浓度最高,光化学水平再升高反而出现下降的趋势。OC和SO_(4)^(2-)与光化学水平呈较好的正相关关系。对于平均日变化情况,O_(3)和PM_(2.5)与光化学水平呈正相关,EC、NO_(2)和NO_(3)^(-)的日变化情况均与PM_(2.5)类似,自贡夜间N O_(3)^(-)浓度相对于其他3个城市较高,OC在中午和午后出现较高值,SO_(4)^(2-)在轻和低光化学水平下变化不明显,浓度与光化学水平成正比。成都和达州,二次有机碳(SOC)随着光化学水平由轻到中的变化,占比不断增加。而对德阳和自贡,SOC随着光化学水平由轻到中占比先增加后减少。4个城市不同光化学水平下的氮氧化率(NOR)和硫氧化率(SOR)基本超过了0.1,说明二次转化较为明显,且SOR的值明显大于NOR,SO_(2)二次转化率更高。该文的研究方法和结论不仅对四川盆地的空气环境综合整治有重要价值,而且可为其它地区空气污染的预防与控制提供参考。To investigate the pollution characteristics of PM_(2.5) components and their relationship with atmospheric oxidation in typical cities in the Sichuan Basin,this study used the WRF-CMAQ model to simulate and analyze the PM_(2.5) components during a sustained O_(3) pollution process in the spring of 2020.O_(3),max was used as an indicator to classify the photochemical activity as light,low,and medium photochemical levels to analyze the characteristics of PM_(2.5) components and their contributions to PM_(2.5 )at different photochemical levels.The results showed that high-level air was dominated by either stable weather conditions or downwelling airflow during the O_(3) pollution period in the Sichuan Basin,and that the sea-level pressure was high,which corresponded to sunny weather.This is beneficial for photochemical reactions,and facilitates the generation of O_(3) and secondary aerosols.Pollution hotspots were mainly concentrated in the Chengdu Plain and western Chongqing.The high concentration areas of PM_(2.5),and NO_(2) coincided with areas of O_(3) pollution.In the early stage of pollution,OC and NO_(3)^(-)contributed the most to PM_(2.5),whereas in the late stage,OC and SO_4^(2-)contributed the most to PM_(2.5).In Dazhou,NO_(3)^(-)and NH_(4)^(+)concentrations reached their highest levels at low photochemical levels,and then decreased with increasing photochemical levels.OC and SO_(4)^(2-)showed strong positive correlations with photochemical levels.For the daily averaged variations,O_(3) and PM_(2.5) were positively correlated with photochemical levels,and the daily changes in EC,NO_2,and NO_(3)^(-)showed similar variations to those of PM_(2.5).The concentration of NO_(3)^(-)at night was higher in Zigong than that in the other three cities.OC had a higher concentration at noon,and later,the concentration of SO_(4)^(2-)did not show significant variation at light and low photochemical levels,but was directly proportional to the photochemical level.In Chengdu and Dazhou,the proportion of Secondary Organic Car

关 键 词：持续臭氧污染 PM_(2.5)组分 大气氧化性 数值模拟 气象条件 四川盆地 

分 类 号：X51[环境科学与工程—环境工程]