Cargando…
Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine
One of the most critical issues for city viability and global health is air quality. The shutdown interval for the COVID-19 outbreaks has turned into an ecological experiment, allowing researchers to explore the influence of human/industrial operations on air quality. In this study, we have observed...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633110/ https://www.ncbi.nlm.nih.gov/pubmed/36349349 http://dx.doi.org/10.1016/j.rsase.2022.100862 |
_version_ | 1784824191590072320 |
---|---|
author | Haque, Md. Nazmul Sharif, Md. Shahriar Rudra, Rhyme Rubayet Mahi, Mahdi Mansur Uddin, Md. Jahir Ellah, Radwan G. Abd |
author_facet | Haque, Md. Nazmul Sharif, Md. Shahriar Rudra, Rhyme Rubayet Mahi, Mahdi Mansur Uddin, Md. Jahir Ellah, Radwan G. Abd |
author_sort | Haque, Md. Nazmul |
collection | PubMed |
description | One of the most critical issues for city viability and global health is air quality. The shutdown interval for the COVID-19 outbreaks has turned into an ecological experiment, allowing researchers to explore the influence of human/industrial operations on air quality. In this study, we have observed and examined the spatial pattern of air pollutants, specifically CO, NO(2), SO(2), O3 as well as AOD Over Bangladesh. For that reason, the timeline was chosen from March 2019 to October 2020 (before and during the first surge of COVID-19). The full analysis has been performed in Google Earth Engine (GEE). The findings showed that, CO, SO(2), and AOD levels dropped significantly, but SO(2) dropped slowly and O(3) levels were similar, with marginally greater quantities in some areas during the lockdown than in 2019. During the shutdown, the association involving airborne pollutants and weather parameters (temperature and rainfall) revealed that rainfall and temperature were directly associated with air pollutants. COVID-19 mortality had a high positive connection with NO(2) (R(2) = 0.145; r = 0.38) and AOD (R(2) = 0.17; r = 0.412). It is also found that various air impurities concentration has a strong relationship with Covid death. It would help the policymakers and officials to gain a better understanding of the sources of atmospheric emissions to develop a substantial proof of short- and long-term mitigation ways to enhance air quality and reduce the associated disease and disability burden. |
format | Online Article Text |
id | pubmed-9633110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96331102022-11-04 Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine Haque, Md. Nazmul Sharif, Md. Shahriar Rudra, Rhyme Rubayet Mahi, Mahdi Mansur Uddin, Md. Jahir Ellah, Radwan G. Abd Remote Sens Appl Article One of the most critical issues for city viability and global health is air quality. The shutdown interval for the COVID-19 outbreaks has turned into an ecological experiment, allowing researchers to explore the influence of human/industrial operations on air quality. In this study, we have observed and examined the spatial pattern of air pollutants, specifically CO, NO(2), SO(2), O3 as well as AOD Over Bangladesh. For that reason, the timeline was chosen from March 2019 to October 2020 (before and during the first surge of COVID-19). The full analysis has been performed in Google Earth Engine (GEE). The findings showed that, CO, SO(2), and AOD levels dropped significantly, but SO(2) dropped slowly and O(3) levels were similar, with marginally greater quantities in some areas during the lockdown than in 2019. During the shutdown, the association involving airborne pollutants and weather parameters (temperature and rainfall) revealed that rainfall and temperature were directly associated with air pollutants. COVID-19 mortality had a high positive connection with NO(2) (R(2) = 0.145; r = 0.38) and AOD (R(2) = 0.17; r = 0.412). It is also found that various air impurities concentration has a strong relationship with Covid death. It would help the policymakers and officials to gain a better understanding of the sources of atmospheric emissions to develop a substantial proof of short- and long-term mitigation ways to enhance air quality and reduce the associated disease and disability burden. Elsevier B.V. 2022-11 2022-11-04 /pmc/articles/PMC9633110/ /pubmed/36349349 http://dx.doi.org/10.1016/j.rsase.2022.100862 Text en © 2022 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 Haque, Md. Nazmul Sharif, Md. Shahriar Rudra, Rhyme Rubayet Mahi, Mahdi Mansur Uddin, Md. Jahir Ellah, Radwan G. Abd Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title | Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title_full | Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title_fullStr | Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title_full_unstemmed | Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title_short | Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine |
title_sort | analyzing the spatio-temporal directions of air pollutants for the initial wave of covid-19 epidemic over bangladesh: application of satellite imageries and google earth engine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633110/ https://www.ncbi.nlm.nih.gov/pubmed/36349349 http://dx.doi.org/10.1016/j.rsase.2022.100862 |
work_keys_str_mv | AT haquemdnazmul analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine AT sharifmdshahriar analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine AT rudrarhymerubayet analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine AT mahimahdimansur analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine AT uddinmdjahir analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine AT ellahradwangabd analyzingthespatiotemporaldirectionsofairpollutantsfortheinitialwaveofcovid19epidemicoverbangladeshapplicationofsatelliteimageriesandgoogleearthengine |