Literature DB >> 33129520

How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh.

Md Siddiqur Rahman1, Md Abul Kalam Azad1, Md Hasanuzzaman1, Roquia Salam1, Abu Reza Md Towfiqul Islam2, Md Mostafizur Rahman3, Mir Md Mozammal Hoque4.   

Abstract

The transmission of novel coronavirus (COVID-19) can be reduced by implementing a lockdown policy, which has also been proven as an effective control measure for air pollution in the urban cities. In this study, we applied ground- and satellite-based data of five criteria air pollutants (PM2.5, NO2, SO2, O3, and CO) and meteorological factors from March 8 to May 15, 2020 (before, partial-, and full-lockdown). The generalized additive models (GAMs), wavelet coherence, and random forest (RF) model were employed to explore the relationship between air quality indicators and COVID-19 transmission in Dhaka city. Results show that overall, 26, 20.4, 17.5, 9.7 and 8.8% declined in PM 2.5, NO2, SO2, O3, and CO concentrations, respectively, in Dhaka City during the partial and full lockdown compared to the period before the lockdown. The implementation of lockdown policy for containing COVID-19 transmission played a crucial role in reducing air pollution. The findings of wavelet coherence and partial wavelet coherence demonstrate no standalone coherence, but interestingly, multiple wavelet coherence indicated a strong short-term coherence among air pollutants and meteorological factors with the COVID-19 outbreak. Outcomes of GAMs indicated that an increase of 1-unit in long-term exposure to O3 and CO (lag1) was associated with a 2.9% (95% CI: -0.3%, -5.6%), and 53.9% (95% CI: 0.2%, -107.9%) decreased risk of COVID-19 infection rate during the full-lockdown period. Whereas, COVID-19 infection and MT (mean temperature) are modulated by a peak during full-lockdown, which is mostly attributed to contact transmission in Dhaka city. RF model revealed among the parameters being studied, MT, RH (relative humidity), and O3 were the dominant factors that could be associated with COVID-19 cases during the study period. The outcomes reported here could elucidate the effectiveness of lockdown scenarios for COVID-19 containment and air pollution control in Dhaka city.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Air pollution; CO; COVID-19; Humidity; Ozone; PM2.5

Mesh:

Substances:

Year:  2020        PMID: 33129520      PMCID: PMC7577272          DOI: 10.1016/j.scitotenv.2020.143161

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  16 in total

1.  Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions.

Authors:  Yong Jie Wong; Huan-Yu Shiu; Jackson Hian-Hui Chang; Maggie Chel Gee Ooi; Hsueh-Hsun Li; Ryosuke Homma; Yoshihisa Shimizu; Pei-Te Chiueh; Luksanaree Maneechot; Nik Meriam Nik Sulaiman
Journal:  J Clean Prod       Date:  2022-06-27       Impact factor: 11.072

Review 2.  A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020.

Authors:  Ivan Franch-Pardo; Michael R Desjardins; Isabel Barea-Navarro; Artemi Cerdà
Journal:  Trans GIS       Date:  2021-07-11

3.  Impact of meteorological parameters on COVID-19 transmission in Bangladesh: a spatiotemporal approach.

Authors:  Al-Ekram Elahee Hridoy; Md Abdul Mohiman; Shekh Md Shajid Hasan Tusher; Sayed Ziaul Amin Nowraj; Mohammad Atiqur Rahman
Journal:  Theor Appl Climatol       Date:  2021-02-03       Impact factor: 3.179

4.  Impact of the COVID-19 pandemic on air pollution in Chinese megacities from the perspective of traffic volume and meteorological factors.

Authors:  Chanchan Gao; Shuhui Li; Min Liu; Fengying Zhang; V Achal; Yue Tu; Shiqing Zhang; Chaolin Cai
Journal:  Sci Total Environ       Date:  2021-02-03       Impact factor: 7.963

5.  Revisiting air quality during lockdown persuaded by second surge of COVID-19 of megacity Delhi, India.

Authors:  Susanta Mahato; Swades Pal
Journal:  Urban Clim       Date:  2022-01-06

6.  Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation.

Authors:  Mostafa Keshtkar; Hamed Heidari; Niloofar Moazzeni; Hossein Azadi
Journal:  Environ Sci Pollut Res Int       Date:  2022-01-26       Impact factor: 5.190

7.  How do pollutants change post-pandemic? Evidence from changes in five key pollutants in nine Chinese cities most affected by the COVID-19.

Authors:  Qiang Wang; Xuan Yang
Journal:  Environ Res       Date:  2021-04-02       Impact factor: 8.431

8.  COVID-19 mortality and exposure to airborne PM2.5: A lag time correlation.

Authors:  Longyi Shao; Yaxin Cao; Tim Jones; M Santosh; Luis F O Silva; Shuoyi Ge; Kátia da Boit; Xiaolei Feng; Mengyuan Zhang; Kelly BéruBé
Journal:  Sci Total Environ       Date:  2021-10-29       Impact factor: 7.963

Review 9.  How changes in human activities during the lockdown impacted air quality parameters: A review.

Authors:  Samuele Marinello; Maria Angela Butturi; Rita Gamberini
Journal:  Environ Prog Sustain Energy       Date:  2021-05-10       Impact factor: 2.824

10.  Containment measures limit environmental effects on COVID-19 early outbreak dynamics.

Authors:  Gentile Francesco Ficetola; Diego Rubolini
Journal:  Sci Total Environ       Date:  2020-12-16       Impact factor: 7.963

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