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Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India
The present paper designed to understand the variations in the atmospheric pollutants viz. PM(10), PM(2.5), SO(2), NO(2), and CO during the COVID-19 pandemic over eight most polluted Indian cities (Mumbai, Delhi, Bangalore, Hyderabad, Lucknow, Chandigarh, Kolkata, and Ahmedabad). A significant reduc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Meteorological Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849226/ https://www.ncbi.nlm.nih.gov/pubmed/33552402 http://dx.doi.org/10.1007/s13143-021-00232-7 |
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author | Gautam, Alok Sagar Kumar, Sanjeev Gautam, Sneha Anand, Aryan Kumar, Ranjit Joshi, Abhishek Bauddh, Kuldeep Singh, Karan |
author_facet | Gautam, Alok Sagar Kumar, Sanjeev Gautam, Sneha Anand, Aryan Kumar, Ranjit Joshi, Abhishek Bauddh, Kuldeep Singh, Karan |
author_sort | Gautam, Alok Sagar |
collection | PubMed |
description | The present paper designed to understand the variations in the atmospheric pollutants viz. PM(10), PM(2.5), SO(2), NO(2), and CO during the COVID-19 pandemic over eight most polluted Indian cities (Mumbai, Delhi, Bangalore, Hyderabad, Lucknow, Chandigarh, Kolkata, and Ahmedabad). A significant reduction in the PM(2.5) (63%), PM(10) (56%), NO(2) (50%), SO(2) (9%), and CO (59%) were observed over Major Dhyan Chand Stadium. At Chhatrapati Shivaji International Airport, a decline of 44% in PM(2.5) and 50% in PM(10) was seen just a week during the initial phase of the lockdown. Gaseous pollutants (NO(2), SO(2) & CO) dropped up-to 36, 16, and 41%, respectively. The Air Quality Index (AQI) shows a dramatic change from 7% to 67% during observation at Chandigarh and Ballygunge during the inspection. Whereas, Ahmedabad, Worli, Income Tax Office, Talkatora, Lalbagh, and Ballygaunge have showed a significant change in AQI from 25.76% to 68.55%. However, Zoo Park, CST, Central School, and Victoria show relatively low variation in AQI in the range of 3.0% to 14.50% as compare to 2019 after lockdown. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analysis suggested that long range transportation of pollutants were also a part and parcel contributing to changes in AQI which were majorly coming from the regions of Iran, Afghanistan, Saudi Arabia, as well as a regional grant from Indian Gangatic plains and Delhi Non-capital region. |
format | Online Article Text |
id | pubmed-7849226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Meteorological Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-78492262021-02-02 Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India Gautam, Alok Sagar Kumar, Sanjeev Gautam, Sneha Anand, Aryan Kumar, Ranjit Joshi, Abhishek Bauddh, Kuldeep Singh, Karan Asia Pac J Atmos Sci Original Article The present paper designed to understand the variations in the atmospheric pollutants viz. PM(10), PM(2.5), SO(2), NO(2), and CO during the COVID-19 pandemic over eight most polluted Indian cities (Mumbai, Delhi, Bangalore, Hyderabad, Lucknow, Chandigarh, Kolkata, and Ahmedabad). A significant reduction in the PM(2.5) (63%), PM(10) (56%), NO(2) (50%), SO(2) (9%), and CO (59%) were observed over Major Dhyan Chand Stadium. At Chhatrapati Shivaji International Airport, a decline of 44% in PM(2.5) and 50% in PM(10) was seen just a week during the initial phase of the lockdown. Gaseous pollutants (NO(2), SO(2) & CO) dropped up-to 36, 16, and 41%, respectively. The Air Quality Index (AQI) shows a dramatic change from 7% to 67% during observation at Chandigarh and Ballygunge during the inspection. Whereas, Ahmedabad, Worli, Income Tax Office, Talkatora, Lalbagh, and Ballygaunge have showed a significant change in AQI from 25.76% to 68.55%. However, Zoo Park, CST, Central School, and Victoria show relatively low variation in AQI in the range of 3.0% to 14.50% as compare to 2019 after lockdown. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analysis suggested that long range transportation of pollutants were also a part and parcel contributing to changes in AQI which were majorly coming from the regions of Iran, Afghanistan, Saudi Arabia, as well as a regional grant from Indian Gangatic plains and Delhi Non-capital region. Korean Meteorological Society 2021-02-01 2021 /pmc/articles/PMC7849226/ /pubmed/33552402 http://dx.doi.org/10.1007/s13143-021-00232-7 Text en © Korean Meteorological Society and Springer Nature B.V. 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 | Original Article Gautam, Alok Sagar Kumar, Sanjeev Gautam, Sneha Anand, Aryan Kumar, Ranjit Joshi, Abhishek Bauddh, Kuldeep Singh, Karan Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title | Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title_full | Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title_fullStr | Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title_full_unstemmed | Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title_short | Pandemic induced lockdown as a boon to the Environment: trends in air pollution concentration across India |
title_sort | pandemic induced lockdown as a boon to the environment: trends in air pollution concentration across india |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849226/ https://www.ncbi.nlm.nih.gov/pubmed/33552402 http://dx.doi.org/10.1007/s13143-021-00232-7 |
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