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。

IF 3 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Vaishali, Rupesh M. Das
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引用次数: 0

摘要

本研究评估了德里不同地点PM2.5浓度的季节和日变化,强调了风速和风向的作用。使用描述性和统计技术对PM2.5浓度进行分析,包括方差分析、Mann-Kendall趋势和相关分析。CPCB CAAQMS网络中五个不同地点(工业、商业、住宅、交通和绿色区域)的数据从2018年到2022年进行了检查。季节变异分析显示,PM2.5浓度在季风后和冬季达到300-350µg/m3的峰值,而在季风期间观察到较低的水平(3)。日模式表现为双峰分布,峰值出现在早晨(0800 ~ 1000 h)和夜间(2000 ~ 2400 h),白天受车辆排放、道路扬尘和风吹颗粒物的驱动,夜间边界层稳定,混合高度降低。工业和交通活动严重的地区PM2.5浓度比商业区和绿地高15-25%。该研究发现,从疫情前到后,PM2.5浓度呈下降趋势,下降幅度约为15%。通过相关检验和t检验分析,结合风升图,发现气象参数(风速和风向)对PM2.5弥散有显著影响。根据风速的不同,污染物的输送有2 ~ 4小时的时滞。统计分析表明,风速与PM2.5浓度之间存在显著的负相关关系
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Environmental Monitoring and Assessment
Environmental Monitoring and Assessment 环境科学-环境科学
CiteScore
4.70
自引率
6.70%
发文量
1000
审稿时长
7.3 months
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.
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