Big Data Analysis for Effects of the COVID-19 Outbreak on Ambient PM2.5 in Areas that Were Not Locked Down

ABSTRACT At the end of 2019, the coronavirus COVID-19 outbreak was first observed. Also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SAS-cov-2), it rapidly spread globally in the first half of 2020. COVID-19 disease was well-controlled in Taiwan without a nation-wide lockdown. Our study aimed to investigate PM2.5 levels and patterns from PM2.5 sensors during the COVID-19 situation in 2020 compared with those in the corresponding periods in 2019. Our sampling areas were located at industrial areas in the north and south Taiwan and were used to gather PM2.5 data from approximately 1,500 PM2.5 sensors every 1 or 3 minutes between January and March of 2019 and 2020. Compared with the corresponding period of 2019 (16.3 and 32.4 μg m-3 in north and south Taiwan, respectively), PM2.5 was significantly reduced by 3.70% and 10.6% in north and south Taiwan, respectively, during the COVID-19 situation from January to March in 2020 based on a big data analysis. Similar PM2.5 patterns were observed in the industrial areas in north and south Taiwan in 2019 and 2020. Based on our results, the decline in PM2.5 during the COVID-19 outbreak has mainly been due to decreased domestic emissions of PM2.5 precursors (i.e., nitrogen dioxide and sulfur dioxide) and to a lesser degree is due to reductions in transboundary transportation of PM2.5, such as long-range PM2.5 transport from China. PM2.5 may be temporarily decreased during the COVID-19 outbreak, but the patterns remained similar to those in the past. Considering restrictions related to the rapid spread of the SAS-cov-2 virus during the COVID-19 episode, control of PM2.5 emissions from local sources might help reduce the number of COVID-19 cases.