Cargando…
Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital
The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM(2.5) and PM(10)) virtually ineffective during April to May 2021. The air quality...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903175/ https://www.ncbi.nlm.nih.gov/pubmed/35276107 http://dx.doi.org/10.1016/j.chemosphere.2022.134271 |
_version_ | 1784664710214320128 |
---|---|
author | Beig, Gufran Jayachandran, K.S. George, M.P. Rathod, Aditi Sobhana, S.B. Sahu, S.K. Shinde, R. Jindal, V. |
author_facet | Beig, Gufran Jayachandran, K.S. George, M.P. Rathod, Aditi Sobhana, S.B. Sahu, S.K. Shinde, R. Jindal, V. |
author_sort | Beig, Gufran |
collection | PubMed |
description | The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM(2.5) and PM(10)) virtually ineffective during April to May 2021. The air quality remained not only unabated but also was marred by some unusual extreme pollution events. SAFAR-framework model simulations with different sensitivity experiments were conducted using the newly developed lockdown emission inventory to understand various processes responsible for these anomalies in PM. Model results well captured the magnitude and variations of the observed PM before and after the lockdown but significantly underestimated their levels in the initial period of lockdown followed by the first high pollution event when the mortality counts were at their peak (∼400 deaths/day). It is believed that an unaccounted emission source was playing a leading role after balancing off the impact of curtailed lockdown emissions. The model suggests that the unprecedented surge in PM(10) (690 μg/m(3)) on May 23, 2021, though Delhi was still under lockdown, was associated with large-scale dust transport originating from the north west part of India combined with the thunderstorm. The rainfall and local dust lifting played decisive roles in other unusual events. Obtained results and the proposed interpretation are likely to enhance our understanding and envisaged to help policymakers to frame suitable strategies in such kinds of emergencies in the future. |
format | Online Article Text |
id | pubmed-8903175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89031752022-03-09 Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital Beig, Gufran Jayachandran, K.S. George, M.P. Rathod, Aditi Sobhana, S.B. Sahu, S.K. Shinde, R. Jindal, V. Chemosphere Article The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM(2.5) and PM(10)) virtually ineffective during April to May 2021. The air quality remained not only unabated but also was marred by some unusual extreme pollution events. SAFAR-framework model simulations with different sensitivity experiments were conducted using the newly developed lockdown emission inventory to understand various processes responsible for these anomalies in PM. Model results well captured the magnitude and variations of the observed PM before and after the lockdown but significantly underestimated their levels in the initial period of lockdown followed by the first high pollution event when the mortality counts were at their peak (∼400 deaths/day). It is believed that an unaccounted emission source was playing a leading role after balancing off the impact of curtailed lockdown emissions. The model suggests that the unprecedented surge in PM(10) (690 μg/m(3)) on May 23, 2021, though Delhi was still under lockdown, was associated with large-scale dust transport originating from the north west part of India combined with the thunderstorm. The rainfall and local dust lifting played decisive roles in other unusual events. Obtained results and the proposed interpretation are likely to enhance our understanding and envisaged to help policymakers to frame suitable strategies in such kinds of emergencies in the future. Elsevier Ltd. 2022-07 2022-03-08 /pmc/articles/PMC8903175/ /pubmed/35276107 http://dx.doi.org/10.1016/j.chemosphere.2022.134271 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Beig, Gufran Jayachandran, K.S. George, M.P. Rathod, Aditi Sobhana, S.B. Sahu, S.K. Shinde, R. Jindal, V. Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title | Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title_full | Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title_fullStr | Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title_full_unstemmed | Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title_short | Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital |
title_sort | process-based diagnostics of extreme pollution trail using numerical modelling during fatal second covid-19 wave in the indian capital |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903175/ https://www.ncbi.nlm.nih.gov/pubmed/35276107 http://dx.doi.org/10.1016/j.chemosphere.2022.134271 |
work_keys_str_mv | AT beiggufran processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT jayachandranks processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT georgemp processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT rathodaditi processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT sobhanasb processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT sahusk processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT shinder processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital AT jindalv processbaseddiagnosticsofextremepollutiontrailusingnumericalmodellingduringfatalsecondcovid19waveintheindiancapital |