Machine Learning Explains Long-Term Trend and Health Risk of Air Pollution during 2015–2022 in a Coastal City in Eastern China

作者：Zihe Qian, Qingxiao Meng, Kehong Chen, Zihang Zhang, Hongwei Liang, Han Yang, Xiaolei Huang, Weibin Zhong, Yichen Zhang, Yichen Zhang, Ziqian Wei, Binqian Zhang, Kexin Zhang, Meijuan Chen, Yunjiang Zhang, Yunjiang Zhang, Xinlei Ge · 发表于：Toxics · 年份：2023 · DOI：10.3390/toxics11060481 · 被引用次数：9 · 研究领域：Air Quality and Health Impacts、Atmospheric chemistry and aerosols、Air Quality Monitoring and Forecasting

Exposure to air pollution is one of the greatest environmental risks for human health. Air pollution level is significantly driven by anthropogenic emissions and meteorological conditions. To protect people from air pollutants, China has implemented clean air actions to reduce anthropogenic emissions, which has led to rapid improvement in air quality over China. Here, we evaluated the impact of anthropogenic emissions and meteorological conditions on trends in air pollutants in a coastal city (Lianyungang) in eastern China from 2015 to 2022 based on a random forest model. The annual mean concentration of observed air pollutants, including fine particles, inhalable particles, sulfur dioxide, nitrogen dioxide, and carbon monoxide, presented significant decreasing trends during 2015-2022, with dominant contributions (55-75%) by anthropogenic emission reduction. An increasing trend in ozone was observed with an important contribution (28%) by anthropogenic emissions. The impact of meteorological conditions on air pollution showed significant seasonality. For instance, the negative impact on aerosol pollution occurred during cold months, while the positive impact was in warm months. Health-risk-based air quality decreased by approximately 40% in 8 years, for which anthropogenic emission made a major contribution (93%).