Spatiotemporal Changes of Pollutant Concentrations in South India during COVID-19 Lockdown Using Ground and Satellite-based data: a Comparative Analysis from the Machine Learning Model

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Water, Air, & Soil Pollution Pub Date : 2025-02-28 DOI:10.1007/s11270-025-07824-3
Pelati Althaf, Nulu S. M. P. Latha Devi, Kanike Raghavendra Kumar
{"title":"Spatiotemporal Changes of Pollutant Concentrations in South India during COVID-19 Lockdown Using Ground and Satellite-based data: a Comparative Analysis from the Machine Learning Model","authors":"Pelati Althaf,&nbsp;Nulu S. M. P. Latha Devi,&nbsp;Kanike Raghavendra Kumar","doi":"10.1007/s11270-025-07824-3","DOIUrl":null,"url":null,"abstract":"<div><p>Under the COVID-19-induced lockdown, there was a sharp decrease in pollution emissions, which led to previously unheard-of trends in India’s most dangerous pollutants. The study is considered for March-June 2020 to investigate the impact of lockdown on the concentrations of air pollutants, at the four stations in Andhra Pradesh, India. The study period was divided into Before Lockdown (BLD), During Lockdown (Phase-I (P-I), Phase-II (P-II), Phase-III (P-III), Phase-IV (P-IV)) and After Lockdown (ALD). The air pollutant concentrations over four stations were retrieved using in-situ measurements under the Central Pollution Control Board (CPCB), India network. The percentage contribution of PM<sub>2.5</sub> in PM<sub>10</sub> was recorded as 60–70% at Tirumala (TML) before lockdown (BLD), Phase-I, Phase-II, and low contribution at Visakhapatnam (VSK) of 10–40%. The maximum reduction in all pollutants recorded at Visakhapatnam (VSK) was up to 30–70%, and the highest reduction in PM<sub>10</sub>, NO<sub>2</sub>, and SO<sub>2</sub> was nearly 35–75% recorded at Tirumala (TML), which shows the effect due to the lack of human activities. In this study, the predominant changes occur in the first phase of the lockdown in all the studied air pollutant’s mean concentrations. Pollutant concentrations decreased across all sites during the lockdown, aligning with National Ambient Air Quality Standards (NAAQS) for the first time. The Spatial analysis showed varying degrees of improvement across four locations, experiencing a significant decrease in concentrations. Pearson’s correlations between pollutants and meteorological factors indicated that wind speed and direction changes influenced pollutant dispersion. Also, the XGBoost model demonstrated high predictive accuracy for PM<sub>2.5</sub> but tended to underpredict at higher concentrations, especially in complex urban environments. This study is for policymakers to develop precise mitigation strategies for air pollution to create a sustainable Environment.</p></div>","PeriodicalId":808,"journal":{"name":"Water, Air, & Soil Pollution","volume":"236 3","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water, Air, & Soil Pollution","FirstCategoryId":"6","ListUrlMain":"https://link.springer.com/article/10.1007/s11270-025-07824-3","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Under the COVID-19-induced lockdown, there was a sharp decrease in pollution emissions, which led to previously unheard-of trends in India’s most dangerous pollutants. The study is considered for March-June 2020 to investigate the impact of lockdown on the concentrations of air pollutants, at the four stations in Andhra Pradesh, India. The study period was divided into Before Lockdown (BLD), During Lockdown (Phase-I (P-I), Phase-II (P-II), Phase-III (P-III), Phase-IV (P-IV)) and After Lockdown (ALD). The air pollutant concentrations over four stations were retrieved using in-situ measurements under the Central Pollution Control Board (CPCB), India network. The percentage contribution of PM2.5 in PM10 was recorded as 60–70% at Tirumala (TML) before lockdown (BLD), Phase-I, Phase-II, and low contribution at Visakhapatnam (VSK) of 10–40%. The maximum reduction in all pollutants recorded at Visakhapatnam (VSK) was up to 30–70%, and the highest reduction in PM10, NO2, and SO2 was nearly 35–75% recorded at Tirumala (TML), which shows the effect due to the lack of human activities. In this study, the predominant changes occur in the first phase of the lockdown in all the studied air pollutant’s mean concentrations. Pollutant concentrations decreased across all sites during the lockdown, aligning with National Ambient Air Quality Standards (NAAQS) for the first time. The Spatial analysis showed varying degrees of improvement across four locations, experiencing a significant decrease in concentrations. Pearson’s correlations between pollutants and meteorological factors indicated that wind speed and direction changes influenced pollutant dispersion. Also, the XGBoost model demonstrated high predictive accuracy for PM2.5 but tended to underpredict at higher concentrations, especially in complex urban environments. This study is for policymakers to develop precise mitigation strategies for air pollution to create a sustainable Environment.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于地面和卫星数据的COVID-19封锁期间印度南部污染物浓度的时空变化:来自机器学习模型的比较分析
在covid -19引发的封锁期间,污染排放急剧减少,导致印度最危险的污染物出现了前所未有的趋势。该研究计划于2020年3月至6月进行,以调查封锁对印度安得拉邦四个站点空气污染物浓度的影响。研究阶段分为封锁前(BLD)、封锁期间(第一阶段(P-I)、第二阶段(P-II)、第三阶段(P-III)、第四阶段(P-IV)和封锁后(ALD)。利用印度中央污染控制委员会(CPCB)网络下的现场测量数据,反演了四个站点的空气污染物浓度。在封锁(BLD),第一阶段,第二阶段之前,蒂鲁马拉(TML)的PM10中PM2.5的百分比贡献为60-70%,而维沙卡帕特南(VSK)的贡献较低,为10-40%。维萨卡帕特南(VSK)记录的所有污染物的最大减少量可达30-70%,而Tirumala (TML)记录的PM10, NO2和SO2的最大减少量接近35-75%,这表明缺乏人类活动的影响。在本研究中,所有研究的空气污染物的平均浓度变化主要发生在封城的第一阶段。在封锁期间,所有地点的污染物浓度都有所下降,首次符合国家环境空气质量标准(NAAQS)。空间分析显示,四个地点的污染程度有所改善,浓度显著下降。污染物与气象因子之间的Pearson相关性表明,风速和风向的变化影响污染物的扩散。此外,XGBoost模型对PM2.5的预测精度较高,但在较高浓度下往往预测不足,特别是在复杂的城市环境中。这项研究是为了政策制定者制定精确的空气污染缓解战略,以创造一个可持续的环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Water, Air, & Soil Pollution
Water, Air, & Soil Pollution 环境科学-环境科学
CiteScore
4.50
自引率
6.90%
发文量
448
审稿时长
2.6 months
期刊介绍: Water, Air, & Soil Pollution is an international, interdisciplinary journal on all aspects of pollution and solutions to pollution in the biosphere. This includes chemical, physical and biological processes affecting flora, fauna, water, air and soil in relation to environmental pollution. Because of its scope, the subject areas are diverse and include all aspects of pollution sources, transport, deposition, accumulation, acid precipitation, atmospheric pollution, metals, aquatic pollution including marine pollution and ground water, waste water, pesticides, soil pollution, sewage, sediment pollution, forestry pollution, effects of pollutants on humans, vegetation, fish, aquatic species, micro-organisms, and animals, environmental and molecular toxicology applied to pollution research, biosensors, global and climate change, ecological implications of pollution and pollution models. Water, Air, & Soil Pollution also publishes manuscripts on novel methods used in the study of environmental pollutants, environmental toxicology, environmental biology, novel environmental engineering related to pollution, biodiversity as influenced by pollution, novel environmental biotechnology as applied to pollution (e.g. bioremediation), environmental modelling and biorestoration of polluted environments. Articles should not be submitted that are of local interest only and do not advance international knowledge in environmental pollution and solutions to pollution. Articles that simply replicate known knowledge or techniques while researching a local pollution problem will normally be rejected without review. Submitted articles must have up-to-date references, employ the correct experimental replication and statistical analysis, where needed and contain a significant contribution to new knowledge. The publishing and editorial team sincerely appreciate your cooperation. Water, Air, & Soil Pollution publishes research papers; review articles; mini-reviews; and book reviews.
期刊最新文献
Enhanced Fluoride Removal by Lanthanum-Based Silica Nanocomposite: Optimization of Preparation Parameters and Adsorption Mechanism Identification of Potential Toxic Element Pollution Sources in Mine Groundwater Based on the PCA-PMF-SOM Model Physiological and Oxidative Dynamics in Mesopotamichthys sharpeyi Under Cadmium Chloride Stress Harnessing Chromium-Resistant Bacteria from Tannery Wastewater: Innovative In Vitro and In Silico Strategies for Bioremediation Pistachio Processing Wastewater treatment by Peroxi-Electrocoagulation Method and Artificial Neural Network Modelling
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1