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Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown
The megacities experience poor air quality frequently due to stronger anthropogenic emissions. India had one of the longest lockdowns in 2020 to curb the spread of COVID-19, leading to reductions in the emissions from anthropogenic activities. In this article, the frequency distributions of differen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529380/ https://www.ncbi.nlm.nih.gov/pubmed/34674132 http://dx.doi.org/10.1007/s11356-021-16874-z |
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author | Mondal, Arnab Sharma, Sudhir Kumar Mandal, Tuhin Kumar Girach, Imran Ojha, Narendra |
author_facet | Mondal, Arnab Sharma, Sudhir Kumar Mandal, Tuhin Kumar Girach, Imran Ojha, Narendra |
author_sort | Mondal, Arnab |
collection | PubMed |
description | The megacities experience poor air quality frequently due to stronger anthropogenic emissions. India had one of the longest lockdowns in 2020 to curb the spread of COVID-19, leading to reductions in the emissions from anthropogenic activities. In this article, the frequency distributions of different pollutants have been analysed over two densely populated megacities: Delhi (28.70° N; 77.10° E) and Kolkata (22.57° N; 88.36° E). In Delhi, the percentage of days with PM(2.5) levels exceeding the National Ambient Air Quality Standards (NAAQS) between 25 March and 17 June dropped from 98% in 2019 to 61% in 2020. The lockdown phase 1 brought down the PM(10) (particulate matter having an aerodynamic diameter ≤ 10 μm) levels below the daily NAAQS limit over Delhi and Kolkata. However, PM(10) exceeded the limit of 100 μgm(−3) during phases 2–5 of lockdown over Delhi due to lower temperature, weaker winds, increased relative humidity and commencement of limited traffic movement. The PM(2.5) levels exhibit a regressive trend in the highest range from the year 2019 to 2020 in Delhi. The daily mean value for PM(2.5) concentrations dropped from 85–90 μgm(−3) to 40–45 μgm(−3) bin, whereas the PM(10) levels witnessed a reduction from 160–180 μgm(−3) to 100–120 μgm(−3) bin due to the lockdown. Kolkata also experienced a shift in the peak of PM(10) distribution from 80–100 μgm(−3) in 2019 to 20–40 μgm(−3) during the lockdown. The PM(2.5) levels in peak frequency distribution were recorded in the 35–40 μgm(−3) bin in 2019 which dropped to 15–20 μgm(−3) in 2020. In line with particulate matter, other primary gaseous pollutants (NO(x), CO, SO(2), NH(3)) also showed decline. However, changes in O(3) showed mixed trends with enhancements in some of the phases and reductions in other phases. In contrast to daily mean O(3), 8-h maximum O(3) showed a reduction over Delhi during lockdown phases except for phase 3. Interestingly, the time of daily maximum was observed to be delayed by ~ 2 h over Delhi (from 1300 to 1500 h) and ~ 1 h over Kolkata (from 1300 to 1400 h) almost coinciding with the time of maximum temperature, highlighting the role of meteorology versus precursors. Emission reductions weakened the chemical sink of O(3) leading to enhancement (120%; 11 ppbv) in night-time O(3) over Delhi during phases 1–3. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-021-16874-z. |
format | Online Article Text |
id | pubmed-8529380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-85293802021-10-21 Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown Mondal, Arnab Sharma, Sudhir Kumar Mandal, Tuhin Kumar Girach, Imran Ojha, Narendra Environ Sci Pollut Res Int Novel Corona Virus (COVID-19) in Environmental Engineering Perspective The megacities experience poor air quality frequently due to stronger anthropogenic emissions. India had one of the longest lockdowns in 2020 to curb the spread of COVID-19, leading to reductions in the emissions from anthropogenic activities. In this article, the frequency distributions of different pollutants have been analysed over two densely populated megacities: Delhi (28.70° N; 77.10° E) and Kolkata (22.57° N; 88.36° E). In Delhi, the percentage of days with PM(2.5) levels exceeding the National Ambient Air Quality Standards (NAAQS) between 25 March and 17 June dropped from 98% in 2019 to 61% in 2020. The lockdown phase 1 brought down the PM(10) (particulate matter having an aerodynamic diameter ≤ 10 μm) levels below the daily NAAQS limit over Delhi and Kolkata. However, PM(10) exceeded the limit of 100 μgm(−3) during phases 2–5 of lockdown over Delhi due to lower temperature, weaker winds, increased relative humidity and commencement of limited traffic movement. The PM(2.5) levels exhibit a regressive trend in the highest range from the year 2019 to 2020 in Delhi. The daily mean value for PM(2.5) concentrations dropped from 85–90 μgm(−3) to 40–45 μgm(−3) bin, whereas the PM(10) levels witnessed a reduction from 160–180 μgm(−3) to 100–120 μgm(−3) bin due to the lockdown. Kolkata also experienced a shift in the peak of PM(10) distribution from 80–100 μgm(−3) in 2019 to 20–40 μgm(−3) during the lockdown. The PM(2.5) levels in peak frequency distribution were recorded in the 35–40 μgm(−3) bin in 2019 which dropped to 15–20 μgm(−3) in 2020. In line with particulate matter, other primary gaseous pollutants (NO(x), CO, SO(2), NH(3)) also showed decline. However, changes in O(3) showed mixed trends with enhancements in some of the phases and reductions in other phases. In contrast to daily mean O(3), 8-h maximum O(3) showed a reduction over Delhi during lockdown phases except for phase 3. Interestingly, the time of daily maximum was observed to be delayed by ~ 2 h over Delhi (from 1300 to 1500 h) and ~ 1 h over Kolkata (from 1300 to 1400 h) almost coinciding with the time of maximum temperature, highlighting the role of meteorology versus precursors. Emission reductions weakened the chemical sink of O(3) leading to enhancement (120%; 11 ppbv) in night-time O(3) over Delhi during phases 1–3. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-021-16874-z. Springer Berlin Heidelberg 2021-10-21 2022 /pmc/articles/PMC8529380/ /pubmed/34674132 http://dx.doi.org/10.1007/s11356-021-16874-z Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Novel Corona Virus (COVID-19) in Environmental Engineering Perspective Mondal, Arnab Sharma, Sudhir Kumar Mandal, Tuhin Kumar Girach, Imran Ojha, Narendra Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title | Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title_full | Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title_fullStr | Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title_full_unstemmed | Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title_short | Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown |
title_sort | frequency distribution of pollutant concentrations over indian megacities impacted by the covid-19 lockdown |
topic | Novel Corona Virus (COVID-19) in Environmental Engineering Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529380/ https://www.ncbi.nlm.nih.gov/pubmed/34674132 http://dx.doi.org/10.1007/s11356-021-16874-z |
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