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This study used air quality monitoring data, namely, the air pollution index (API) and air quality index (AQI) between 2005 and 2018, together with meteorological data and identified key meteorological factors that affected the spatial and temporal variation of air quality using a random forest algorithm. The spatial and temporal differences in the threshold values of different meteorological factors affecting the concentrations of PM<jats:sub>2.5<\/jats:sub>, PM<jats:sub>10<\/jats:sub>, SO<jats:sub>2<\/jats:sub>, CO, NO<jats:sub>2<\/jats:sub>, and O<jats:sub>3<\/jats:sub> were identified. The AQI has the advantages of facilitating higher index values than the API. The air quality showed an improvement from 2005 to 2018. Wind direction and precipitation were the most important meteorological factors affecting the air quality in northern and southern China, respectively, which to some extent reflected the causes and degradation mechanisms of air pollution in the two regions. There were significant spatial and temporal differences in the effects of meteorological factors on the concentrations of different pollutants. The influence of atmospheric pressure on pollutant concentration differed between the east and west. Precipitation and relative humidity in most cities had significant impacts on PM<jats:sub>2.5<\/jats:sub> and PM<jats:sub>10<\/jats:sub>. The influence of relative humidity was most significant for SO<jats:sub>2<\/jats:sub> and it also had a great influence on O<jats:sub>3<\/jats:sub>, while wind speed had a great influence on NO<jats:sub>2<\/jats:sub>. The results of the study confirm the meteorological sensitivity of air quality and provide support for the implementation of regional air pollution prevention and control initiatives.<\/jats:p>","DOI":"10.1155\/2020\/6829142","type":"journal-article","created":{"date-parts":[[2020,6,14]],"date-time":"2020-06-14T23:30:18Z","timestamp":1592177418000},"page":"1-25","source":"Crossref","is-referenced-by-count":10,"title":["Spatiotemporal Relationships between Air Quality and Multiple Meteorological Parameters in 221 Chinese Cities"],"prefix":"10.1155","volume":"2020","author":[{"given":"Mengyi","family":"Ji","sequence":"first","affiliation":[{"name":"Key Laboratory of Indoor Air Environment Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China"}]},{"given":"Yuying","family":"Jiang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Indoor Air Environment Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China"}]},{"given":"Xiping","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Indoor Air Environment Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China"}]},{"given":"Luo","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangdong Province Key Laboratory for Land Use and Consolidation, South China Agricultural University, Guangzhou 510642, China"}]},{"given":"Xinliang","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8971-4952","authenticated-orcid":true,"given":"Zhi","family":"Qiao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Indoor Air Environment Quality Control, School of 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