氮氧化物
臭氧
混合比
环境科学
污染
环境化学
空气污染
空气质量指数
挥发性有机化合物
相对湿度
煤燃烧产物
燃烧
大气科学
化学
气象学
有机化学
生态学
物理
生物
地质学
作者
Xiaoxia Ren,Yan-ping Wen,Qiusheng He,Yang Cui,Xueying Gao,Fang Li,Yuhang Wang,Lili Guo,Hongyan Li,Xinming Wang
标识
DOI:10.1016/j.apr.2021.101083
摘要
Regional ozone pollution has become one of the most challenging environmental problems in China. In July 2019, hourly real-time monitoring of ozone (O3) and nitrogen oxides (NOx) and 3-hour off-line measurement of volatile organic compounds (VOCs) during a 10-day intensive campaign were conducted at four sites in Taiyuan, Shanxi Province, China. The average mixing ratio of total VOCs (including alkanes, alkenes, aromatics and acetylene) was 14.8 ± 2.8 ppbv and the dominant VOCs species to O3 formation were alkenes in Taiyuan. According to China Ambient Air Quality Standard Grade II (hourly averaged mixing ratio of 103 ppbv), the studied periods were divided into O3 attainment periods (EP1) and O3 pollution periods (EP2). A continuous O3 pollution event was captured during 12–15 July, with the maximum hourly O3 mixing ratio of 131.7 ppbv. Higher temperature, lower relative humidity, weaker winds and local photochemical reaction were conducive to O3 pollution during EP2. The analysis of VOCs/NOx ratio indicated that the formation of O3 was co-controlled by both VOCs and NOx during the period of 12:00–18:00 LT (high value period of O3), and it was controlled by VOCs during the remaining period. The abundances, compositions of typical VOCs and VOCs/NOx ratio showed clear spatial and temporal variations. Six major sources of VOCs were identified by positive matrix factorization, including coal and biomass combustion (33%), coking sources (28%), vehicular emissions (14%), solvent usage (10%), industrial processes (8%) and biological sources (7%). Backward trajectory analysis found that higher concentration of O3 in air masses from local (70%) and southern areas (22.5%) during EP2. Local (32%) and southern (30%) coking sources were the main contributors of ozone formation potential (OFP) during EP2.
科研通智能强力驱动
Strongly Powered by AbleSci AI