Understanding the impact of meteorology on ozone in 334 cities of China

日照时长 环境科学 相对湿度 广义加性模型 风速 大气科学 臭氧 空气污染 降水 气象学 风向 污染 气候学 中国 地理 数学 统计 化学 考古 地质学 生态学 有机化学 生物
作者
Chenfei Hu,Pengde Kang,Daniel A. Jaffe,Chunkai Li,Xiaoling Zhang,Kai Wu,Mingwei Zhou
出处
期刊:Atmospheric Environment [Elsevier BV]
卷期号:248: 118221-118221 被引量:44
标识
DOI:10.1016/j.atmosenv.2021.118221
摘要

The daily variations of near-surface ozone (O3), one of the major air pollutants in China, depend on meteorological conditions. In this study, we analyzed the characteristics of O3 pollution and the complicated interactions among the controlling meteorological factors. In China, O3 pollution is becoming severe and high-concentration areas are expanding greatly. We found that O3 was correlated to numerous meteorological variables including air pressure, temperature, relative humidity, wind speed, wind direction, sunshine duration, evaporation, and precipitation. Using generalized additive models (GAMs), we developed predictive models to forecast the maximum daily 8 h O3 mass concentration for 334 cities in China. Different cities were influenced by different meteorological variables, with temperature (90.77%), relative humidity (68.15%), and sunshine hours (66.96%) being the top three influencing factors. In addition, we found that the influence of these meteorological factors on O3 pollution was nonlinear and impacted by the interaction between variables. Considering individual relationships between each meteorological factor and O3, the average coefficient of determination (R2) of GAMs for the 334 cities was 0.64 ± 0.16. However, considering the interaction between variables, the average R2 for 334 cities of revised GAMs increased to 0.72 ± 0.15. The R2 was significantly improved in 96.72% of the cities after considering the interactions among the meteorological factors based on a ten-fold cross-validation method. Furthermore, we found that the GAM residuals were unbiased. As an example of using and interpreting the GAM results, we focused on a case study in Hangzhou during the G20 summit in 2016. During this period, nitrogen oxides (NOx) and volatile organic compounds were reduced by 51.67% and 49.00%, respectively, because of local emission controls. Despite these changes in precursor emissions, O3 changed slightly during this period, suggesting that O3 in Hangzhou at the time was not controlled by local precursor emissions, but was impacted by meteorological conditions.
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