山西省城市地区近年来环境空气臭氧污染特征及来源解析

基于山西省2018—2020年国控点位O₃监测数据分析了全省O₃污染特征，分别以晋城市和太原市为典型城市，分析了温度、相对湿度和风向风速等气象因子以及前体物(NO_x和VOCs)对O₃的影响，并采用CAMx模式开展2020年6—8月山西省O₃区域和行业来源解析. 结果表明:① 山西省O₃超标天数中以O₃轻度污染为主，且中度及以上污染呈增加趋势，O₃污染集中出现在5—9月，且呈现较强的地域性特征，O₃浓度日变化呈单峰型特征. ② ρ(O_{3-1 h})(臭氧1 h平均浓度)与气温、风速均呈正相关，与相对湿度呈负相关，高温、低湿有利于O₃的生成. 风速与ρ(O_{3-1 h})呈分段式线性关系，ρ(O_{3-1 h})随着风速增大而升高，当风速大于某一阈值时，ρ(O_{3-1 h})随风速的增加而下降. 以典型城市晋城市为例，当温度在25 ℃以上、相对湿度在30%~60%之间、风速为4~5 m/s，且风向为南风和东南风时更容易出现ρ(O_{3-1 h})高值. ③ 山西省2020年6—8月O₃区域来源解析表明，各城市O₃本地源贡献较弱而传输贡献影响显著(>80%). ④ 山西省2020年6—8月O₃行业来源解析表明，各市工业源类(电力源、焦化源和其他工业源)的贡献率在50%左右，柴油交通源贡献率在20%~27%之间. 研究显示，山西省O₃污染传输贡献影响显著，联防联控势在必行，电力源、焦化源和柴油交通源对O₃生成贡献较大，亟需优先加强管控. 

Pollution Characteristics and Source Apportionment of Ground-Level Ozone in Shanxi Urban Region in Recent Years

The pollution characteristics of ground-level ozone was studied based on the O₃ concentration data of the national controlled points in Shanxi Province from 2018 to 2020, by analyzing the meteorological factors, including temperature, relative humidity, wind direction, wind speed, and its precursors (NO_x and VOCs) that affect the pollution characteristics of O₃ concentration. Source apportionment of regional and industrial transmission in Shanxi Province from June to August 2020 was performed by the CAMx model. The results showed that the O₃ pollution in Shanxi Province was mainly light pollution, and O₃ pollution became worse in Shanxi Province. The diurnal variation of O₃ showed a ‘single peak’ pattern, and the monthly variation occurred with geographical characteristics from May to September. ρ(O_{3-1 h}) was positively correlated with temperature and wind speed, but negatively correlated with relative humidity. High temperature and low humidity meteorological conditions were more likely to promote atmospheric O₃ formation. A piecewise linear relationship between wind speed and ρ(O_{3-1 h}) was observed. ρ(O_{3-1 h}) increased with the increase in wind speed. However, when the wind speed threshold was exceeded, ρ(O_{3-1 h}) decreased with the increase in wind speed. Taking Jincheng City as an example, high ρ(O_{3-1 h}) was more likely to occur when the temperature was higher than 25 ℃, the humidity was between 30%-60%, the wind speed was between 4-5 m/s and the wind direction was south and southeast. The results of the regional transport matrix of ground-level O₃ from June to August in 2020 showed that transport source had great influence on O₃ pollution, with a contribution rate of more than 80%, and the contribution of local sources was small. Similarly, during the simulation period, industrial sources including electric power, coking and other industrial sources contributed the most to the generation of O₃, accounting for about 50%, followed by diesel transportation sources, accounting for 20%-27%. This research shows that transport sources had great influence on O₃ pollution, and the regional joint prevention and control measures should be taken. It is proposed that controlling the emissions of VOCs from electric power, coking and diesel transportation would be more effective for reducing O₃ pollution.