Analysis of Summer Atmospheric Volatile Organic Compounds in Taiyuan City Based on Random Forest Model
In recent years,volatile organic compounds(VOCs)have received extensive attention as an important precursor of O3,but the understanding of the real emission of VOCs that decouple meteorological factors is limited.In this case,VOCs samples were collected during the O3 pollution period in Taiyuan in summer.The average concentration of VOCs during the study period was 30.6×10-9±9.3×10-9,the average temperature was 26.7℃±3.3℃,and the daily peak of photolysis rate(represented by NO2,JNO2)was 9.2 s-1±1.0×10-3 s-1.In order to clarify the impact of anthropogenic emissions and meteorological factors on VOCs,a random forest model based on machine learning was used to quantify the changes in VOCs concentration before and after de-meteorology.The results showed that the concentration of TVOCs decreased by 0.4%after meteorological normalization,indicating that the unfavorable meteorological conditions in Taiyuan in summer led to the increase of TVOCs concentration.
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