郑州市高新区夏季臭氧及前体物污染特征和关键前体物溯源研究  

Research on the characteristics of summer ozone and its precursor pollution and key precursor traceability in Zhengzhou High-tech Development Zone

作　　者：胡娜 李源清 张晓东 张亮 臧金亮[1,2] HU Na;LI Yuanqing;ZHANG Xiaodong;ZHANG Liang;ZANG Jiniang(Zhengzhou Institute of Metrology,Zhengzhou 450001;National Institute of Metrology,Beijing 100029)

机构地区：[1]郑州计量先进技术研究院,郑州450001 [2]中国计量科学研究院,北京100029

出　　处：《环境科学学报》2024年第9期32-41,共10页Acta Scientiae Circumstantiae

基　　金：国家市场监督管理总局科技计划项目(No.2022MK076)。

摘　　要：基于2023年6—8月郑州市高新区国控站点和监测车监测数据,利用正交矩阵因子分析法受体模型(Positive Matrix Factorization,PMF)和零维框架模拟模型(The Framework for 0-D Atmospheric Modeling,F0AM)结合的方法,全面分析了臭氧(O_(3))和其前体物的污染特征以及O_(3)关键前体物的精准溯源.结果表明,监测期间郑州市高新区O_(3)污染较严重,O_(3)污染天数为46 d(占比55%),其中轻度污染40 d,中度污染6 d.污染日呈现高温低湿的特点,MDA8-O_(3)、O_(3)、TVOCs、NO_(2)和NO_(x)分别是非污染日的1.52倍、1.41倍、1.2倍、1.6倍和1.4倍,导致O_(3)污染具有更强的本地生成能力.研究发现监测期间VOCs主要来自工业过程源(21.3%)、二次生成源(11.9%)、机动车尾气排放源(13.4%)、溶剂使用源(18.9%)、老化气团源(14.4%)、天然气/液化石油气挥发源(9.6%)和植物排放源(10.4%).敏感性分析(RIR)结果表明,郑州市高新区处于VOCs-NO_(x)协同控制区,因此协同减排VOCs与NO_(x)是控制O_(3)生成的有效途径.另外,PMF源解析和敏感性分析结果表明,污染期间敏感性高的VOC物种主要来自植物排放(41.1%)、工业过程(32.6%)、溶剂使用(14.3%)、二次生成(6.2%)和机动车尾气(5.8%),尤其应对来自植物排放的异戊二烯、工业过程的苯系物和二次生成的乙醛及其来源进行重点监测管控.Based on the monitoring data from national control stations and monitoring vehicles in Zhengzhou High-tech Development Zone from June to August 2023,the pollution characteristics of ozone(O_(3))and its precursors,as well as accurate traceability of key ozone precursors were comprehensively analyzed,using Positive Matrix Factorization(PMF)and The Framework for 0-D Atmospheric Modeling(F0AM).The results showed that O_(3)pollution in Zhengzhou High-tech Development Zone was relatively severe during the monitoring period,with 46 days(55%)of O_(3)pollution,including 40 days of mild pollution and 6 days of moderate pollution.Pollution days were characterized by high temperature and low humidity,and MDA8-O_(3),O_(3),TVOCs,NO_(2),and NO_(x)were 1.52 times,1.41 times,1.2 times,1.6 times,and 1.4 times than that of non-pollution days respectively,resulting in a more robust localization generation capacity of O_(3)pollution.Studying the O_(3)pollution process found that VOCs mainly came from industrial process(21.3%),secondary generation(11.9%),motor vehicle exhaust(13.4%),organic solvents(18.9%),regional aged air mass(14.4%),NG/LPG(9.6%)and plant emissions(10.4%).Sensitivity analysis(RIR)results indicated that O_(3)formation was sensitive to VOCs and NO_(x)in Zhengzhou High-tech Development Zone.Therefore,it is a productive way to decrease O_(3)formation by controlling VOCs and NO_(x)in coordination.In addition,PMF and sensitivity analysis(RIR)results indicated that high-sensitivity VOCs mainly came from plant emissions(41.1%),industrial processs(32.6%),organic solvents(14.3%),secondary generation(6.2%)and motor vehicle exhaust(5.8%),and it is significantly better to focus on controlling isoprene from plant emissions,BTEX from industrial process,acetaldehyde from secondary generation and their main source.

关 键 词：臭氧污染 正交矩阵因子分析法受体模型(PMF) 零维框架模拟模型(F0AM) 敏感性分析 精准溯源 

分 类 号：X51[环境科学与工程—环境工程]