Fitting Statistical Distribution Functions of Air Pollutant Concentration in Different Urban Locations in Malaysia

Abstract

Ground level ozone is an unstable substance in the atmosphere which reacts with nitrogen dioxide (NOx) in the presence of sunlight normally found near ground level. Ground level ozone is known as one of the major air quality issues worldwide. The presence of the NOx volatile organic compounds (VOCs) can influence the concentration levels of ground level ozone. This pollutant can affect crops and human health. The main aim of this research is to find the best fit distribution for urban monitoring stations in Kuala Terengganu, Kota Bharu and Alor Setar. Secondary data from 2011 to 2015 used in this study was obtained from the Department of Environment (DOE). This research used the central fitting probability distribution which is between gamma, Nakagami, lognormal and log logistic distributions. Meanwhile, the method of moments was used to estimate the parameters. The best distribution represented the monitoring station and predicted the return period of the concentration. The results show that the Nakagami distribution represented the Kuala Terengganu station from 2011 to 2015. In Kota Bharu however, the gamma distribution fit better compared to other distributions in 2013. The gamma distribution seems to fit the data from 2011 to 2014 whereas in 2015, the Nakagami distribution fit better than other distributions for the Alor Setar station. In addition, no return period was predicted for concentrations above 0.10 ppm found at the Kuala Terengganu monitoring station.