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Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi
Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM(2.5) and PM(10 -) categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459164/ https://www.ncbi.nlm.nih.gov/pubmed/34580626 http://dx.doi.org/10.1016/j.uclim.2021.100944 |
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author | Das, Manob Das, Arijit Sarkar, Raju Mandal, Papiya Saha, Sunil Ghosh, Sasanka |
author_facet | Das, Manob Das, Arijit Sarkar, Raju Mandal, Papiya Saha, Sunil Ghosh, Sasanka |
author_sort | Das, Manob |
collection | PubMed |
description | Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM(2.5) and PM(10 -) categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future. |
format | Online Article Text |
id | pubmed-8459164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84591642021-09-23 Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi Das, Manob Das, Arijit Sarkar, Raju Mandal, Papiya Saha, Sunil Ghosh, Sasanka Urban Clim Article Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM(2.5) and PM(10 -) categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future. Elsevier B.V. 2021-09 2021-08-06 /pmc/articles/PMC8459164/ /pubmed/34580626 http://dx.doi.org/10.1016/j.uclim.2021.100944 Text en © 2021 Elsevier B.V. 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 Das, Manob Das, Arijit Sarkar, Raju Mandal, Papiya Saha, Sunil Ghosh, Sasanka Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title | Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title_full | Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title_fullStr | Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title_full_unstemmed | Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title_short | Exploring short term spatio-temporal pattern of PM(2.5) and PM(10) and their relationship with meteorological parameters during COVID-19 in Delhi |
title_sort | exploring short term spatio-temporal pattern of pm(2.5) and pm(10) and their relationship with meteorological parameters during covid-19 in delhi |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459164/ https://www.ncbi.nlm.nih.gov/pubmed/34580626 http://dx.doi.org/10.1016/j.uclim.2021.100944 |
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