| 基于随机森林模型的臭氧浓度时空变化特征及关键影响因子识别：以滁州市为例 |
| 摘要点击 2062 全文点击 509 投稿时间：2023-10-16 修订日期：2023-12-04 |
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| 中文关键词 随机森林 臭氧（O3） 时空变化 影响因素 滁州市 |
| 英文关键词 random forest ozone（O3） spatiotemporal variation influencing factor Chuzhou City |
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| 中文摘要 |
| 臭氧污染成因是一个复杂科学问题,在不同时间尺度下对O3时空变化特征进行研究,并分析识别影响O3浓度的关键影响因子,对精细化制定城市空气污染治理措施和切实改善城市空气质量具有重要意义.对滁州市O3浓度的时空变化特征进行分析后,选取多时间尺度的气象和污染物要素的12个影响因子,并应用Spearman相关分析和随机森林模型开展O3浓度关键影响因子的识别研究.结果表明：①滁州市O3污染程度有加重趋势,O3浓度分布呈“东南高-西北低”的空间格局；②2~5月,SO2浓度对O3浓度的升高作用较强；6~9月,PM2.5和PM10与O3显著正相关,影响较大；③相对湿度、 温度和风速对O3的影响较大,气压与小时降雨对O3的影响较弱；④滁州市O3污染机制已由“污染物主控型”变为“气象主控型”；⑤气象和污染物要素中,对O3浓度影响最大的3个影响因子分别为温度、 风速和相对湿度；PM10浓度、 PM2.5浓度和SO2浓度均与O3浓度存在显著的非线性关系. |
| 英文摘要 |
| The cause of ozone pollution is a complex scientific problem. Studying the spatiotemporal variation characteristics of O3 at different time scales and analyzing the key influencing factors of O3 concentration is of great significance for the precise formulation of urban air pollution control measures and the improvement of urban air quality. Based on the analysis of the spatiotemporal variation characteristics of O3 concentration in Chuzhou City, we studied the 12 ozone-influencing factors of meteorology and pollutants at multiple time scales using Spearman correlation analysis and a random forest model. The results showed that： ① The O3 pollution level of Chuzhou City showed an aggravating trend, and the O3 concentration distribution showed a spatial pattern of “high in the southeast and low in the northwest.” ② From February to May, SO2 concentration had a strong impact on the increase in O3 concentration. From June to September, PM2.5 and PM10 were significantly positively correlated with ozone and had a greater impact. ③ Relative humidity, temperature, and wind speed had a significant impact on O3, whereas barometric pressure and hourly rainfall had a weak impact. ④ The O3 pollution mechanism in Chuzhou City changed from “pollutant-controlled” to “meteorology-controlled.” ⑤ Among meteorological and pollutant factors, the three influencing factors that had the greatest influence on O3 concentration were temperature, wind speed, and relative humidity, with PM10 concentration, PM2.5 concentration, and SO2 concentration also contributing. All of the above six influencing factors had a significant nonlinear relationship with the O3 concentration. |
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