Air quality predictions using log normal distribution functions of particulate matter in Kuala Lumpur

Abstract

Malaysia’s capital city of Kuala Lumpur has been developed from a small settlement at the confluence of the Klang and Gombak rivers into a vibrant and bustling metropolis. The associated rapid economic growths have started to impose costs in terms of industrial pollution and the degradation of urban environment. Air pollution is a major issue in this city that has been affecting human health, agricultural crops, forest species, and ecosystems. This paper reports findings of a research aimed at developing a tool needed to analyze the statistical characters of air quality data in Kuala Lumpur, Malaysia. In this study, the theoretical distribution Log Normal was used to fit the parent distribution of PM10 for 1998 and 2002 for Kuala Lumpur. Two estimating methods namely method of maximum likelihood and method of moments, were used to estimate the parameters of the theoretic distributions. From the statistical properties of air pollutants, the probabilities of air pollutant concentration exceeding Malaysia Ambient Quality Standards can be predicted. The results of this work provide useful information for air quality management, and can also be used to develop the corresponding air pollution control strategy