[Urban Ozone Driving Factors Based on Explainable Machine Learning].

Q2 Environmental Science
Chao-Long Wang, Lian Xue, Yi-Sheng Zhang, Xiao-Fei Qin, Yuan Fang, Wen-Xin Tao, Jin-Hua Du, Su-Fan Zhang, Guan Wang, Da-Sa Gu, Shan-Shan Cui
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引用次数: 0

Abstract

Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provincial control sites, and one background site, were selected. By coupling the extreme gradient boosting (XGBoost) model with the interpretability SHapley Additive exPlanations (SHAP) module, the impact of meteorological elements and atmospheric pollutant emissions on ozone (O3) pollution was investigated. The results indicated that from 2019 to 2023, meteorological factors contributed 67.7% to O3 formation, whereas emissions from atmospheric pollutants accounted for 32.3%. Surface solar radiation significantly affected O3 formation from 10:00 to 17:00. A positive correlation existed between temperature and O3 concentration, peaking at 14:00. A relative humidity below 70% was conducive to O3 formation and a relative humidity above 70% had a 94% probability of negatively contributing to O3 production. Particularly between 12:00 and 16:00, relative humidity significantly and positively contributed to O3 formation. When the boundary layer height was below 500 meters, it positively affected O3 concentration, whereas above this height, its impact weakened. In the morning and late afternoon, boundary layer height promoted the formation of O3 concentration. Easterly (E) to southwesterly (SW) winds had a positive effect on O3 concentrations in Qingdao. NO2 showed a negative response in the morning (06:00-11:00) and a positive response in the afternoon (12:00-15:00). PM2.5 had a nonlinear positive correlation with O3, positively affecting O3 concentration from 07:00 to 14:00 PM and suppressing it from 15:00 to 18:00. Significant differences existed in the dominant factors of O3 concentration across different areas and seasons. In the western Laoshan District, Yangkou, the western site of the Shinan District, and eastern and western parts of the West Coast New Area, surface solar radiation had a noticeably lower impact on O3 than in other locations. The effect of NO2 was most significant in the eastern parts of the West Coast New Area, western Laoshan District, and Yangkou. PM2.5 affected O3 formation more in these sites than in others of Qingdao. In spring, the impact of NO2 was more significant in the western Laoshan and Shinan Districts. In summer, surface solar radiation was more influential in Yangkou, the eastern and western parts of the West Coast New Area, the western Laoshan District, and the Shibei District, whereas, relative humidity was the key factor in other locations. In autumn, temperature and surface solar radiation were the main factors affecting O3. In winter, the contribution of NO2 was higher than that in different seasons, with anthropogenic emissions playing a more important role in O3 formation. The analysis of days exceeding O3 standards showed that surface solar radiation and NO2 were the main drivers of exceeding O3 concentrations. For all sites, the total SHAP values of PM2.5 and PM10 on days exceeding O3 standards ranged between 6.1 μg·m-3 and 12.4 μg·m-3.

[基于可解释机器学习的城市臭氧驱动因素]。
选取青岛沿海城市16个站点,包括8个国家级控制站点、7个省级控制站点和1个背景站点。通过将极端梯度增强(XGBoost)模型与可解释性SHapley加性解释(SHAP)模型耦合,研究了气象要素和大气污染物排放对臭氧污染的影响。结果表明:2019 - 2023年,气象因子对O3形成的贡献率为67.7%,大气污染物排放对O3形成的贡献率为32.3%;10 ~ 17时,地表太阳辐射显著影响O3的形成。温度与O3浓度呈正相关,在14:00达到峰值。相对湿度低于70%有利于O3的形成,而相对湿度高于70%则有94%的可能性不利于O3的产生。特别是在12:00 ~ 16:00之间,相对湿度对O3的形成有显著的正向贡献。边界层高度在500 m以下时对O3浓度有正向影响,在500 m以上对O3浓度的影响减弱。在上午和下午晚些时候,边界层高度促进了O3浓度的形成。东风至西南风对青岛市O3浓度有正向影响。NO2在上午(06:00-11:00)呈负响应,下午(12:00-15:00)呈正响应。PM2.5与O3呈非线性正相关,在07:00 - 14:00 PM对O3浓度有正向影响,在15:00 - 18:00 PM对O3浓度有抑制作用。不同地区、不同季节O3浓度的主导因子存在显著差异。在崂山西部、阳口、市南区西部旧址、西海岸新区东西部,地表太阳辐射对O3的影响明显低于其他地区。其中,西海岸新区东部、崂山西部和阳口地区NO2的影响最为显著。PM2.5对这些站点O3形成的影响大于其他站点。在春季,NO2的影响在崂山西部和市南区更为显著。夏季,地面太阳辐射对阳口、西海岸新区东西部、崂山西部和市北区的影响较大,而相对湿度是其他地区的主要影响因素。在秋季,温度和地表太阳辐射是影响O3的主要因素。在冬季,NO2的贡献高于其他季节,人为排放对O3的形成起着更重要的作用。O3超标日数分析表明,地表太阳辐射和NO2是O3超标的主要驱动因素。PM2.5和PM10在O3超标日的总SHAP值在6.1 ~ 12.4 μg·m-3之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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