Application of Statistical Distributions to PM10 Concentrations: Van, Türkiye

Abstract

Air pollution is one of the most serious environmental pollution problems that adversely affect human health and the environment. Industrializing and frequent use of low-quality coals for heating purposes and incorrect combustion techniques may cause intense air pollution in the winter season. There are several studies on air quality employing different methods using various air pollutants (carbon monoxide, nitrogen oxides, ground-level ozone, and particle pollution) in the related literature. In this study PM_10 (concentration of 10 micrometers or smaller size of air pollutants) levels in Van province which is one of the most crowded provinces in Eastern Anatolia, Türkiye. Due to the fuels used for heating in Van, the air quality may be higher than limits set by regulations several times during the year. In this study, PM_10 levels of Van are modeled using lognormal, Weibull, and Gamma distributions. Information and goodness of fit criteria are used to compare their performance. In addition, predictions of exceedances are provided for the PM_10 concentration higher than given limits. According to the results, the Gamma distribution performed better than the other two distributions in modeling the PM_10 concentrations in Van and predicted the exceedances accurately.