{"title":"2018年至2022年期间,德里不同地区PM2.5浓度的季节和日变化以及风型的作用。","authors":"Vaishali, Rupesh M. Das","doi":"10.1007/s10661-025-13761-9","DOIUrl":null,"url":null,"abstract":"<div><p>The present study assesses the seasonal and diurnal variability of PM<sub>2.5</sub> concentrations across different locations in Delhi, emphasizing the role of wind speed and direction. PM<sub>2.5</sub> concentrations were analyzed using descriptive and statistical techniques, including ANOVA, Mann–Kendall trend, and correlation analysis. Data from the CPCB CAAQMS network at five distinct locations—Industrial, Commercial, Residential, Traffic, and Green areas—were examined from 2018–2022. Seasonal variability analysis revealed that PM<sub>2.5</sub> concentrations peaked at 300–350 µg/m<sup>3</sup> during the post-monsoon and winter seasons, while lower levels (< 100 µg/m<sup>3</sup>) were observed during the monsoon. Diurnal patterns exhibited a bimodal distribution, with peaks occurring during the morning (0800–1000 hour) and night (2000 to 2400 hour) time, driven by vehicular emissions, road dust, and wind-blown particles during the day and a stable boundary layer with reduced mixing height at night. Regions with significant industrial and traffic activities experienced 15–25% higher PM<sub>2.5</sub> concentrations than commercial and green areas. The study identified a decreasing trend of approximately 15% in PM<sub>2.5</sub> concentrations from the pre- to post-COVID period. Using correlational and t-test analysis along with the wind rose visualizations, it was revealed that meteorological parameters (wind speed and direction) significantly influence PM<sub>2.5</sub> dispersion. A time lag of 2–4 hour was observed for pollutant transport, depending on the wind speed. Statistical analysis demonstrated a significant inverse correlation between wind speed and PM<sub>2.5</sub> concentrations (p < 0.0001), highlighting the role of meteorological factors in pollutant dispersion. These findings provide actionable insights into air quality management and mitigation strategies for Delhi’s diverse urban environments.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 4","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seasonal and diurnal variability of PM2.5 concentration along with the role of wind patterns over different locations of Delhi during the year 2018 to 2022\",\"authors\":\"Vaishali, Rupesh M. Das\",\"doi\":\"10.1007/s10661-025-13761-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The present study assesses the seasonal and diurnal variability of PM<sub>2.5</sub> concentrations across different locations in Delhi, emphasizing the role of wind speed and direction. PM<sub>2.5</sub> concentrations were analyzed using descriptive and statistical techniques, including ANOVA, Mann–Kendall trend, and correlation analysis. Data from the CPCB CAAQMS network at five distinct locations—Industrial, Commercial, Residential, Traffic, and Green areas—were examined from 2018–2022. Seasonal variability analysis revealed that PM<sub>2.5</sub> concentrations peaked at 300–350 µg/m<sup>3</sup> during the post-monsoon and winter seasons, while lower levels (< 100 µg/m<sup>3</sup>) were observed during the monsoon. Diurnal patterns exhibited a bimodal distribution, with peaks occurring during the morning (0800–1000 hour) and night (2000 to 2400 hour) time, driven by vehicular emissions, road dust, and wind-blown particles during the day and a stable boundary layer with reduced mixing height at night. Regions with significant industrial and traffic activities experienced 15–25% higher PM<sub>2.5</sub> concentrations than commercial and green areas. The study identified a decreasing trend of approximately 15% in PM<sub>2.5</sub> concentrations from the pre- to post-COVID period. Using correlational and t-test analysis along with the wind rose visualizations, it was revealed that meteorological parameters (wind speed and direction) significantly influence PM<sub>2.5</sub> dispersion. A time lag of 2–4 hour was observed for pollutant transport, depending on the wind speed. Statistical analysis demonstrated a significant inverse correlation between wind speed and PM<sub>2.5</sub> concentrations (p < 0.0001), highlighting the role of meteorological factors in pollutant dispersion. These findings provide actionable insights into air quality management and mitigation strategies for Delhi’s diverse urban environments.</p></div>\",\"PeriodicalId\":544,\"journal\":{\"name\":\"Environmental Monitoring and Assessment\",\"volume\":\"197 4\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Monitoring and Assessment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10661-025-13761-9\",\"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":"Environmental Monitoring and Assessment","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10661-025-13761-9","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}
Seasonal and diurnal variability of PM2.5 concentration along with the role of wind patterns over different locations of Delhi during the year 2018 to 2022
The present study assesses the seasonal and diurnal variability of PM2.5 concentrations across different locations in Delhi, emphasizing the role of wind speed and direction. PM2.5 concentrations were analyzed using descriptive and statistical techniques, including ANOVA, Mann–Kendall trend, and correlation analysis. Data from the CPCB CAAQMS network at five distinct locations—Industrial, Commercial, Residential, Traffic, and Green areas—were examined from 2018–2022. Seasonal variability analysis revealed that PM2.5 concentrations peaked at 300–350 µg/m3 during the post-monsoon and winter seasons, while lower levels (< 100 µg/m3) were observed during the monsoon. Diurnal patterns exhibited a bimodal distribution, with peaks occurring during the morning (0800–1000 hour) and night (2000 to 2400 hour) time, driven by vehicular emissions, road dust, and wind-blown particles during the day and a stable boundary layer with reduced mixing height at night. Regions with significant industrial and traffic activities experienced 15–25% higher PM2.5 concentrations than commercial and green areas. The study identified a decreasing trend of approximately 15% in PM2.5 concentrations from the pre- to post-COVID period. Using correlational and t-test analysis along with the wind rose visualizations, it was revealed that meteorological parameters (wind speed and direction) significantly influence PM2.5 dispersion. A time lag of 2–4 hour was observed for pollutant transport, depending on the wind speed. Statistical analysis demonstrated a significant inverse correlation between wind speed and PM2.5 concentrations (p < 0.0001), highlighting the role of meteorological factors in pollutant dispersion. These findings provide actionable insights into air quality management and mitigation strategies for Delhi’s diverse urban environments.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.