Page 67 - Special Topic Session (STS) - Volume 2

STS459 Norshahida S. et al.

Probability distribution model for predicting
ozone (O3) exceedances at two air quality
monitoring sites in Malaysia during dry season
1
Norshahida Shaadan 1,2,3 ; Nabihah Jasri
1 Centre for Statistical and Decision Science Studies, Faculty of Computer & Mathematical
Sciences, UiTM
2 Advanced Analytic Engineering Center, Faculty of Computer & Mathematical Sciences, UiTM
3 Business Datalytic Research Group, UiTM

Abstract
Tropospheric Ozone (O3) is one of the strongest atmospheric oxidants and has
become an important criteria pollutant in the Malaysia environment other
than PM10. Many studies worldwide have proven that, high concentration of
O3 contributes to a certain environmental problem including health problems,
vegetation and materials, as well as climate changing. Thus due to the facts, it
is necessary to gain a good understanding of the characteristics of O3 pollution
so that the information can be the input for managing the problem. In this
study, several probability distributions including Gamma, Lognormal, Normal,
and Weibull were compared with the aim to find the best distribution that can
fit the O3 at two selected air quality monitoring stations in Malaysia located in
Shah Alam and Putrajaya. Based on the two years (2013 and 2014) period of
hourly recorded data, the model parameters were estimated using the method
of maximum likelihood estimator (MLE). The best distribution was determined
using the plot of cumulative distribution function (CDF) and the goodness of
fit statistic including the Kolmogorov-Smirnov, Cramer-von Mises and
Anderson-Darling. The study results have shown that Weibull is found to be
the best model for Shah Alam while Gamma model is for Putrajaya with
expected exceedance return period of seven days.

Keywords
Ozone; Prediction Model; Probability Distribution; Pollutant Exceedances; Air
Quality

1. Introduction
Nowadays, air pollution has become a global problem. Over exposed to
polluted air that contained mixed hazardous gases, dust or hazes has been
proven to be negatively affect human’s health, animals, plants and the
surroundings (Verma et al., 2015; Felzer et al., 2007). The substances that
caused air pollution are called pollutants. In the Malaysia environment, Ozone
(O3) has been identified as the second most dominant pollutant other than
particulate matter (PM10). Ozone (O3) is defined as a secondary type of gas
pollutant and also known as photochemical oxidant that is formed via

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