{"title":"基于GTWR模式的墨西哥极端天气大气污染物与气象因子的相关性研究","authors":"Tianzhen Ju, Lanzhi Wang, Bingnan Li, Zhichao Lv, Zhenrong Gu","doi":"10.1007/s11869-025-01724-5","DOIUrl":null,"url":null,"abstract":"<div><p>In recent years, with the ongoing rise in surface temperatures, heat waves, a frequently occurring extreme weather phenomenon, have manifested within the context of global warming. To investigate the variation of atmospheric pollutants ozone (O<sub>3</sub>), formaldehyde (HCHO), and nitrogen dioxide (NO<sub>2</sub>) and their relationship with meteorological factors during normal weather conditions from March to July 2018–2022, as well as during extreme weather conditions in the Mexican region from March to July 2023. This study utilizes Python, ArcGIS 10.8, and other software to investigate pollutants during two time periods by employing the Geographical Time-Weighted Regression model (GTWR), Random Forest Regression model, Backward Trajectory model, and Ozone Generation Sensitivity Analysis based on daily data from the OMI satellite and meteorological factors. The findings suggest that: (1) O<sub>3</sub> concentrations exhibit an increase, while HCHO concentrations demonstrate a decrease during extreme weather events in the study area; however, NO<sub>2</sub> concentrations do not exhibit significant changes. (2) Extreme weather conditions induce alterations in the correlation between atmospheric pollutants and meteorological factors within the Mexican region. (3) A minor portion of the study area undergoes a shift in Ozone Generation Sensitivity during occurrences of extreme weather.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"18 5","pages":"1489 - 1505"},"PeriodicalIF":2.9000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on correlation between atmospheric pollutants and meteorological factors during extreme weather in Mexico based on GTWR model\",\"authors\":\"Tianzhen Ju, Lanzhi Wang, Bingnan Li, Zhichao Lv, Zhenrong Gu\",\"doi\":\"10.1007/s11869-025-01724-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In recent years, with the ongoing rise in surface temperatures, heat waves, a frequently occurring extreme weather phenomenon, have manifested within the context of global warming. To investigate the variation of atmospheric pollutants ozone (O<sub>3</sub>), formaldehyde (HCHO), and nitrogen dioxide (NO<sub>2</sub>) and their relationship with meteorological factors during normal weather conditions from March to July 2018–2022, as well as during extreme weather conditions in the Mexican region from March to July 2023. This study utilizes Python, ArcGIS 10.8, and other software to investigate pollutants during two time periods by employing the Geographical Time-Weighted Regression model (GTWR), Random Forest Regression model, Backward Trajectory model, and Ozone Generation Sensitivity Analysis based on daily data from the OMI satellite and meteorological factors. The findings suggest that: (1) O<sub>3</sub> concentrations exhibit an increase, while HCHO concentrations demonstrate a decrease during extreme weather events in the study area; however, NO<sub>2</sub> concentrations do not exhibit significant changes. (2) Extreme weather conditions induce alterations in the correlation between atmospheric pollutants and meteorological factors within the Mexican region. (3) A minor portion of the study area undergoes a shift in Ozone Generation Sensitivity during occurrences of extreme weather.</p></div>\",\"PeriodicalId\":49109,\"journal\":{\"name\":\"Air Quality Atmosphere and Health\",\"volume\":\"18 5\",\"pages\":\"1489 - 1505\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Air Quality Atmosphere and Health\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11869-025-01724-5\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air Quality Atmosphere and Health","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s11869-025-01724-5","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Study on correlation between atmospheric pollutants and meteorological factors during extreme weather in Mexico based on GTWR model
In recent years, with the ongoing rise in surface temperatures, heat waves, a frequently occurring extreme weather phenomenon, have manifested within the context of global warming. To investigate the variation of atmospheric pollutants ozone (O3), formaldehyde (HCHO), and nitrogen dioxide (NO2) and their relationship with meteorological factors during normal weather conditions from March to July 2018–2022, as well as during extreme weather conditions in the Mexican region from March to July 2023. This study utilizes Python, ArcGIS 10.8, and other software to investigate pollutants during two time periods by employing the Geographical Time-Weighted Regression model (GTWR), Random Forest Regression model, Backward Trajectory model, and Ozone Generation Sensitivity Analysis based on daily data from the OMI satellite and meteorological factors. The findings suggest that: (1) O3 concentrations exhibit an increase, while HCHO concentrations demonstrate a decrease during extreme weather events in the study area; however, NO2 concentrations do not exhibit significant changes. (2) Extreme weather conditions induce alterations in the correlation between atmospheric pollutants and meteorological factors within the Mexican region. (3) A minor portion of the study area undergoes a shift in Ozone Generation Sensitivity during occurrences of extreme weather.
期刊介绍:
Air Quality, Atmosphere, and Health is a multidisciplinary journal which, by its very name, illustrates the broad range of work it publishes and which focuses on atmospheric consequences of human activities and their implications for human and ecological health.
It offers research papers, critical literature reviews and commentaries, as well as special issues devoted to topical subjects or themes.
International in scope, the journal presents papers that inform and stimulate a global readership, as the topic addressed are global in their import. Consequently, we do not encourage submission of papers involving local data that relate to local problems. Unless they demonstrate wide applicability, these are better submitted to national or regional journals.
Air Quality, Atmosphere & Health addresses such topics as acid precipitation; airborne particulate matter; air quality monitoring and management; exposure assessment; risk assessment; indoor air quality; atmospheric chemistry; atmospheric modeling and prediction; air pollution climatology; climate change and air quality; air pollution measurement; atmospheric impact assessment; forest-fire emissions; atmospheric science; greenhouse gases; health and ecological effects; clean air technology; regional and global change and satellite measurements.
This journal benefits a diverse audience of researchers, public health officials and policy makers addressing problems that call for solutions based in evidence from atmospheric and exposure assessment scientists, epidemiologists, and risk assessors. Publication in the journal affords the opportunity to reach beyond defined disciplinary niches to this broader readership.