临汾市臭氧时空变化特征及影响因素分析

Characteristics of Spatial and Temporal Variations of Ozone in Linfen City and Analysis of Influencing Factors

近年来,我国城市环境空气中PM2.5浓度逐年下降,O3浓度日趋升高,O3污染已成为制约空气质量改善的关键因素。临汾市作为中国重要焦煤基地之一,拥有大量的钢铁、焦化等行业,这些行业排放的污染物,导致O3浓度居高不下,污染治理面临着严峻挑战。本研究基于2020~2022年临汾市监测站点的污染物浓度及气象数据,采用因果性分析、复杂网络及相关性分析方法解析临汾市O3浓度的时空变化特征和影响因素。2020~2022年临汾市O3污染较为严重,从时间上看,O3污染期为5~9月,非污染期为10~2月。从空间上看,临汾市各站O3日最大8小时滑动均值均超过160 μg/m3,O3污染期内的O3浓度传输网络模型连边值均超过0.5,说明各站点间存在显著的O3传输关系,其中市委和城南的O3污染最为明显,传输能力最强。从影响因素上看,O3与NO2负相关关系显著,与PM2.5、CO、PM10、SO2负相关关系较弱。同时,O3与气压、相对湿度呈负相关,而与气温、露点温度、十分钟平均风速和能见度呈正相关。

In recent years, the concentration of PM2.5 in China’s urban ambient air has been decreasing year by year, and the concentration of O3 has been increasing, and O3 pollution has become a key factor restricting the improvement of air quality. Linfen city, as one of the important coking coal bases in China, has a large number of iron and steel and coking industries, which emit pollutants, resulting in high O3 concentrations and facing serious challenges in pollution management. Based on the pollutant concentrations and meteorological data from the monitoring stations in Linfen City from 2020 to 2022, this study uses causality analysis, complex network and correlation analysis to analyse the spatial and temporal characteristics of the O3 concentration and the influencing factors in Linfen City. In 2020~2022, Linfen City is more seriously polluted by O3, and from the time point of view, the O3 polluted period is from May to September, and the non-polluted period is from October to February. From the spatial point of view, the daily maximum 8-hourly sliding mean values of O3 at each station in Linfen City exceeded 160 μg/m3, and the contiguous edge values of the O3 concentration transport network model during the O3 pollution period exceeded 0.5, which indicated that there was a significant O3 transport relationship between stations, with the Municipal Party Committee and the southern part of the city being the most obvious O3 pollutants with the strongest transport capacity. In terms of influencing factors, O3 has a significant negative correlation with NO2, and a weaker negative correlation with PM2.5, CO, PM10, and SO2. Meanwhile, O3 was negatively correlated with barometric pressure and relative humidity, while positively correlated with air temperature, dew point temperature, ten-minute average wind speed and visibility.