The Statistical Distributions of PM2.5 in Rayong and Chonburi Provinces, Thailand

Abstract

<jats:p>The fine particulate matter (PM2.5) concentrations is one of the most important issues that are often discussed since it has a greater impact on human health. Statistical distribution modeling plays an important role in predicting PM2.5 concentrations. This research aims to find the optimum statistical distribution model of PM2.5 in Rayong Province and Chonburi Province. The daily average data from 2014 – 2019 for Rayong and from 2015 – 2019 for Chonburi were using. Five statistical distributions were compared. A proper statistical distribution that represents PM2.5 concentrations has been chosen based on three criteria include Anderson-Darling statistic and RMSE. The results show that Pearson type VI distribution performs better compared to other distributions for PM2.5 concentrations in Rayong. For Chonburi, the proper statistical distribution is Log normal distribution. </jats:p>

Human Health Risks and Air Quality Changes Following Restrictions for the Control of the COVID-19 Pandemic in Thailand

“…There was no significant difference in sub-AQI between, before, and after lockdown. Industrial activities (automotive production and burning of fossil fuels) and traffic densities were sources of PM in RY [32,33]. RY is the largest petroleum and petrochemical industrial complex in Thailand and it consists of petrochemical plants, oil refineries, coal-fired power plants, iron and steel plants, and plastic manufacturers.…”