Author: Pongpiachan, Siwatt; Chetiyanukornkul, Thaneeya; Manassanitwong, Wirat
Title: Relationship Between COVID-19-Infected Number and PM(2.5) Level in Ambient Air of Bangkok, Thailand Cord-id: fsuaiuex Document date: 2021_5_27
ID: fsuaiuex
Snippet: Several empirical studies of reductions in air pollutants as social distancing and working from home (WFH) policies have sparked recommendations that the COVID-19 pandemic might have been responsible for better air quality particularly in urban area. These findings offer a compelling provocation for the scientific community to detect and investigate variations to air quality as a consequence of government enforced quarantine. In spite of countless research studies focusing on the connection betw
Document: Several empirical studies of reductions in air pollutants as social distancing and working from home (WFH) policies have sparked recommendations that the COVID-19 pandemic might have been responsible for better air quality particularly in urban area. These findings offer a compelling provocation for the scientific community to detect and investigate variations to air quality as a consequence of government enforced quarantine. In spite of countless research studies focusing on the connection between WFH policy and air pollutant levels, the majority of discussion has unfortunately ignored the central role of other potential sources (e.g. agricultural waste burnings, cooking emissions, and industrial releases) in governing air quality, or has neglected the psychological and social impacts of COVID-19. In this study, a t test was used to compare the average concentrations of PM(2.5) and COVID-19-infected numbers (n) in three different periods which were n < 300 vs. n ≧ 300, n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700. Some significant differences were observed in the groups of n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700 indicating that the psychological and social impacts play a crucial role in restricting daily activities and thus reducing the atmospheric contents of PM(2.5) in some areas. Further assessments were conducted by separating PM(2.5) contents into three different periods (i.e. Period-I: day-1 ~ day-10; Period-II: day-11 ~ day-20; Period-III: day-21 ~ day-31). Some significant reductions of PM(2.5) during the Period-I were detected in the eastern area of Bangkok. In addition, Pearson correlation analysis showed that hot-spot numbers appear to be a minor of importance in controlling PM(2.5) levels in the ambient air of Bangkok, Thailand.
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