Footprints of COVID-19 on PM 2.5 /PM 10 Ratio in a Brazilian Tropical Metropolis

Aerosol Science and Engineering(2024)

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摘要
PM 2.5 /PM 10 ratio is a metric that is used both to determine the main origin of particulate matter and to evaluate the concentration of one component in the absence of monitoring for the other. However, further research is required to fully understand the relationship between this ratio, its components, and meteorological conditions in various scenarios. This study analyzed the effect of COVID-19 restrictions on the PM 2.5 /PM 10 ratio in Recife, Brazil. The data showed that the PM 2.5 /PM 10 ratio significantly decreased in 2020 due to the reduction in urban mobility and human activities. The strictest restrictions were maintained in the state until August and as soon as the first major loosening took place, the ratio began to approach typical pollution levels. The average daily PM 2.5 /PM 10 ratios for 2020, 2021 and 2022 were 0.52 ± 0.08, 0.58 ± 0.03 and 0.58 ± 0.02, respectively, lower than those found in other metropolitan areas. During the phases of greater restrictions, the PM 2.5 /PM 10 ratio had an average value of 0.48 ± 0.08 and as restrictions were lifted, it became 0.56 ± 0.03. The results showed that the reductions observed in 2020 were directly related to the decrease in anthropogenic emissions of PM 2.5 . A machine learning approach was used to estimate the expected PM 2.5 /PM 10 ratio, corrected for the meteorological conditions and it was found that the observed ratios were lower than expected even in this scenario. Furthermore, only temperature and wind speed presented significant correlation to the PM 2.5 /PM 10 ratio in both the scenarios with and without restriction of activities. Our study provides valuable insights into the efficacy of restriction measures in the Brazilian tropical and coastal metropolis of Recife and also highlight the intrinsic relation between the ratio and the local meteorological variables.
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关键词
Air pollution,Meteorological parameters,Machine learning,Brazil,Air quality
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