比较南亚各城市环境细颗粒物污染事件的特点

Q2 Environmental Science
Narayan Babu Dhital
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引用次数: 0

摘要

近年来,南亚地区反复出现严重的空气污染事件。尽管以前的许多研究都是针对单个城市和特定事件对此类污染事件进行调查,但有关该地区多个城市的污染事件特征的信息却十分有限。本研究对 2019-2023 年期间南亚五国 12 个城市的环境 PM2.5 污染事件特征进行了比较分析。PM2.5的日均质量浓度被分解为趋势、季节和残差成分,并通过残差的异常来识别污染事件。此外,还利用污染程度、频率、持续时间和相对严重性指数来描述污染事件。这些城市的 PM2.5 质量浓度年平均值从 20.6 ± 2.5 μg m-3(科伦坡)到 116.6 ± 9.3 μg m-3(拉合尔)不等,12 个城市中有 6 个城市的 PM2.5 质量浓度年平均值为 50 μg m-3。此外,达卡、钦奈、海得拉巴、加尔各答、伊斯兰堡和拉合尔的 PM2.5 水平呈明显上升趋势(p < 0.05)(森氏斜率:1.00-4.33 μg m-3 y-1),而孟买(-0.74 μg m-3 y-1)和新德里(-2.00 μg m-3 y-1)则呈下降趋势(p < 0.05)。各城市的 PM2.5 平均浓度从 49.9 ± 6.1 μg m-3(科伦坡)到 367.1 ± 17.9 μg m-3(拉合尔)不等。同样,平均发病频率从 1.6 年-1 次(加德满都)到 5.2 年-1 次(达卡)不等,而每次发病持续时间从 1.2 天(孟买)到 2.6 天(加德满都)不等。根据发作严重程度的相对指数,拉合尔、达卡和新德里的发作严重程度较高,PM2.5的基线水平也较高。相比之下,卡拉奇、伊斯兰堡、海得拉巴和加德满都显示出中等严重程度和中等基线PM2.5水平,而科伦坡和孟买显示出低严重程度和低至中等基线PM2.5水平。此外,2019-2023年期间,各城市的年度PM2.5事件严重程度排名发生了巨大变化。本研究中提出的基线和偶发污染水平的相对严重性可帮助决策者确定针对污染偶发事件、长期趋势或两者的控制策略的优先次序,并通过减缓、准备和预测来保护人类健康。研究结果还将为制定旨在开展跨境合作和协作的区域政策提供见解,以应对整个南亚地区的空气污染挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing the characteristics of ambient fine particle pollution episodes across South Asian cities

South Asia has been experiencing recurring severe air pollution episodes in recent years. While many previous studies investigated such episodes focusing on individual cities and specific events, limited information exists on episode characteristics across multiple cities in this region. This study presents a comparative analysis of the characteristics of ambient PM2.5 pollution episodes in 12 South Asian cities across five countries during 2019−2023. Daily mean PM2.5 mass concentrations were decomposed into trend, seasonal, and residual components, and episodes were identified through anomalies in residuals. Furthermore, pollution episodes were characterized using magnitude, frequency, duration, and a relative severity index. The cities exhibited annual mean PM2.5 mass concentrations ranging from 20.6 ± 2.5 μg m−3 (Colombo) to 116.6 ± 9.3 μg m−3 (Lahore), with six out of 12 cities having annual mean PM2.5 mass concentrations > 50 μg m−3. Additionally, significant increasing trends (p < 0.05) in PM2.5 levels were observed for Dhaka, Chennai, Hyderabad, Kolkata, Islamabad, and Lahore (Sen's slope: 1.00−4.33 μg m−3 y−1), whereas decreasing trends (p < 0.05) were observed for Mumbai (−0.74 μg m−3 y−1) and New Delhi (−2.00 μg m−3 y−1). Mean PM2.5 episode magnitudes varied in a wide range from 49.9 ± 6.1 μg m−3 (Colombo) to 367.1 ± 17.9 μg m−3 (Lahore) across the cities. Likewise, the mean episode frequency ranged from 1.6 y−1 (Kathmandu) to 5.2 y−1 (Dhaka), whereas duration ranged from 1.2 (Mumbai) to 2.6 (Kathmandu) days per episode. Based on the relative index of episode severity, Lahore, Dhaka, and New Delhi exhibited high episode severity, as well as high baseline PM2.5 levels. In contrast, Karachi, Islamabad, Hyderabad, and Kathmandu showed moderate episode severity and moderate baseline PM2.5 levels, whereas Colombo and Mumbai showed low episode severity with low to moderate baseline PM2.5 levels. Moreover, annual PM2.5 episode severity ranks among the cities changed dramatically during 2019−2023. The relative severity of baseline and episodic pollution levels presented in this study may help policymakers prioritize the control strategies targeting pollution episodes, long-term trends, or both, as well as protecting human health through mitigation, preparedness, and forecasting. The findings will also provide insights for formulating regional policies aimed at transboundary cooperation and collaboration to deal with air pollution challenges across South Asia.

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来源期刊
Environmental Challenges
Environmental Challenges Environmental Science-Environmental Engineering
CiteScore
8.00
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249
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8 weeks
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