tetano
Editor, Senior Moderator
Sci Total Environ
. 2020 Oct 21;143161.
doi: 10.1016/j.scitotenv.2020.143161. Online ahead of print.
How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh
Md Siddiqur Rahman[SUP] 1 [/SUP], Md Abul Kalam Azad[SUP] 1 [/SUP], Md Hasanuzzaman[SUP] 1 [/SUP], Roquia Salam[SUP] 1 [/SUP], Abu Reza Md Towfiqul Islam[SUP] 2 [/SUP], Md Mostafizur Rahman[SUP] 3 [/SUP], Mir Md Mozammal Hoque[SUP] 4 [/SUP]
Affiliations
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, NO[SUB]2[/SUB], SO[SUB]2[/SUB], O[SUB]3[/SUB], 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, NO[SUB]2[/SUB], SO[SUB]2[/SUB], O[SUB]3[/SUB], 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 O[SUB]3[/SUB] 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 O[SUB]3[/SUB] 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.
Keywords: Air pollution; CO; COVID-19; Humidity; Ozone; PM2.5.
. 2020 Oct 21;143161.
doi: 10.1016/j.scitotenv.2020.143161. Online ahead of print.
How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh
Md Siddiqur Rahman[SUP] 1 [/SUP], Md Abul Kalam Azad[SUP] 1 [/SUP], Md Hasanuzzaman[SUP] 1 [/SUP], Roquia Salam[SUP] 1 [/SUP], Abu Reza Md Towfiqul Islam[SUP] 2 [/SUP], Md Mostafizur Rahman[SUP] 3 [/SUP], Mir Md Mozammal Hoque[SUP] 4 [/SUP]
Affiliations
- PMID: 33129520
- DOI: 10.1016/j.scitotenv.2020.143161
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, NO[SUB]2[/SUB], SO[SUB]2[/SUB], O[SUB]3[/SUB], 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, NO[SUB]2[/SUB], SO[SUB]2[/SUB], O[SUB]3[/SUB], 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 O[SUB]3[/SUB] 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 O[SUB]3[/SUB] 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.
Keywords: Air pollution; CO; COVID-19; Humidity; Ozone; PM2.5.