Weiwei Pu, Yingruo Li, Xiaowan Zhu, Xiangxue Liu, Di He, Fan Dong, Heng Guo, Guijie Zhao, Liyan Zhou, Shuangshuang Ge and Zhiqiang Ma
{"title":"基于区域本底站的测量结果,评估排放和气象对中国北方空气质量趋势的影响†。","authors":"Weiwei Pu, Yingruo Li, Xiaowan Zhu, Xiangxue Liu, Di He, Fan Dong, Heng Guo, Guijie Zhao, Liyan Zhou, Shuangshuang Ge and Zhiqiang Ma","doi":"10.1039/D4EA00070F","DOIUrl":null,"url":null,"abstract":"<p >The contributions of meteorology and emissions to air pollutant trends are critical for air quality management, but they have not been fully analyzed, especially in the background area of northern China. Here, we used a machine learning technique to quantify the impacts of meteorological conditions and emissions on PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO pollution during 2013–2021 and evaluated their contributions to Clean Air Action policies. The annual effect of the meteorology on PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, and CO levels was dominated by the meteorological conditions during the cold season, while that of the O<small><sub>3</sub></small> level largely depended on the meteorological conditions during the warm season. Meteorology-driven anomalies contributed −14.8 to 10.3%, −8.5 to 7.3%, −11 to 7.1%, −7.9 to 6.0%, and −7.4 to 7.3% to the annual mean concentrations of PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO during the study period, respectively. The Clean Air Actions have led to a major improvement in the air quality at regional scale, with the reduction of 1.7 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 0.2 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 1.5 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 0.7 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, and 0.03 mg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small> for PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO at background area, respectively, after meteorological correction. Although emissions dominated the long-term variations in pollutants, the meteorological conditions obviously played a positive role during the action periods for pollutants except for O<small><sub>3</sub></small>. Considering the notable effects of the meteorological conditions on air pollution and the interreaction between pollutants, a more comprehensive control strategy should be considered on a broader regional scale.</p>","PeriodicalId":72942,"journal":{"name":"Environmental science: atmospheres","volume":" 11","pages":" 1283-1293"},"PeriodicalIF":2.8000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/ea/d4ea00070f?page=search","citationCount":"0","resultStr":"{\"title\":\"Evaluating emissions and meteorological contributions to air quality trends in northern China based on measurements at a regional background station†\",\"authors\":\"Weiwei Pu, Yingruo Li, Xiaowan Zhu, Xiangxue Liu, Di He, Fan Dong, Heng Guo, Guijie Zhao, Liyan Zhou, Shuangshuang Ge and Zhiqiang Ma\",\"doi\":\"10.1039/D4EA00070F\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The contributions of meteorology and emissions to air pollutant trends are critical for air quality management, but they have not been fully analyzed, especially in the background area of northern China. Here, we used a machine learning technique to quantify the impacts of meteorological conditions and emissions on PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO pollution during 2013–2021 and evaluated their contributions to Clean Air Action policies. The annual effect of the meteorology on PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, and CO levels was dominated by the meteorological conditions during the cold season, while that of the O<small><sub>3</sub></small> level largely depended on the meteorological conditions during the warm season. Meteorology-driven anomalies contributed −14.8 to 10.3%, −8.5 to 7.3%, −11 to 7.1%, −7.9 to 6.0%, and −7.4 to 7.3% to the annual mean concentrations of PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO during the study period, respectively. The Clean Air Actions have led to a major improvement in the air quality at regional scale, with the reduction of 1.7 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 0.2 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 1.5 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, 0.7 μg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small>, and 0.03 mg m<small><sup>−3</sup></small> year<small><sup>−1</sup></small> for PM<small><sub>2.5</sub></small>, NO<small><sub>2</sub></small>, SO<small><sub>2</sub></small>, O<small><sub>3</sub></small>, and CO at background area, respectively, after meteorological correction. Although emissions dominated the long-term variations in pollutants, the meteorological conditions obviously played a positive role during the action periods for pollutants except for O<small><sub>3</sub></small>. Considering the notable effects of the meteorological conditions on air pollution and the interreaction between pollutants, a more comprehensive control strategy should be considered on a broader regional scale.</p>\",\"PeriodicalId\":72942,\"journal\":{\"name\":\"Environmental science: atmospheres\",\"volume\":\" 11\",\"pages\":\" 1283-1293\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.rsc.org/en/content/articlepdf/2024/ea/d4ea00070f?page=search\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental science: atmospheres\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2024/ea/d4ea00070f\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental science: atmospheres","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/ea/d4ea00070f","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Evaluating emissions and meteorological contributions to air quality trends in northern China based on measurements at a regional background station†
The contributions of meteorology and emissions to air pollutant trends are critical for air quality management, but they have not been fully analyzed, especially in the background area of northern China. Here, we used a machine learning technique to quantify the impacts of meteorological conditions and emissions on PM2.5, NO2, SO2, O3, and CO pollution during 2013–2021 and evaluated their contributions to Clean Air Action policies. The annual effect of the meteorology on PM2.5, NO2, SO2, and CO levels was dominated by the meteorological conditions during the cold season, while that of the O3 level largely depended on the meteorological conditions during the warm season. Meteorology-driven anomalies contributed −14.8 to 10.3%, −8.5 to 7.3%, −11 to 7.1%, −7.9 to 6.0%, and −7.4 to 7.3% to the annual mean concentrations of PM2.5, NO2, SO2, O3, and CO during the study period, respectively. The Clean Air Actions have led to a major improvement in the air quality at regional scale, with the reduction of 1.7 μg m−3 year−1, 0.2 μg m−3 year−1, 1.5 μg m−3 year−1, 0.7 μg m−3 year−1, and 0.03 mg m−3 year−1 for PM2.5, NO2, SO2, O3, and CO at background area, respectively, after meteorological correction. Although emissions dominated the long-term variations in pollutants, the meteorological conditions obviously played a positive role during the action periods for pollutants except for O3. Considering the notable effects of the meteorological conditions on air pollution and the interreaction between pollutants, a more comprehensive control strategy should be considered on a broader regional scale.