Browsing by Author "Muhammad Aslam Mohd Safari"

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    Pemodelan Taburan Kebarangkalian Zarah Terampai Melampau di Lembah Klang
    (Penerbit UKM, 2017) Muhammad Aslam Mohd Safari; Wan Zawiah Wan Zin
    This study aims to identify the best statistical model to represent the data set for one of the air pollutants that is the particulate matter with diameters smaller than 10 micrometers (PM10). Data from six air quality monitoring stations in the Klang Valley from 2009 to 2011 were used in this study. In determining the more appropriate probability distribution,both parametric and non-parametric approaches were tested. Two series of extreme data for PM10 were used, which are the monthly maximum and the Peak over threshold data series. Next, two parametric distributions, which are the Generalized Extreme Value (GEV) and Generalized Pareto (GPD) were fitted to the monthly maximum and the Peak over threshold data series, respectively. L-moment parameter estimation method and Anderson Darling goodness of fit test were used to identify the best parametric distribution as well as the more suitable data series to represent extreme data. For the non-parametric approach, the kernel density estimation (KDE) is used in this study to determine the best distribution for extreme PM10.
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    Risk assessment of extreme air pollution based on partial duration series: IDF approach
    (Springer, 2020) Nurulkamal Masseran; Muhammad Aslam Mohd Safari
    The occurrences of extreme pollution events have serious effects on human health, environmental ecosystems, and the national economy. To gain a better understanding of this issue, risk assessments on the behavior of these events must be effectively designed to anticipate the likelihood of their occurrence. In this study, we propose using the intensity–duration–frequency (IDF) technique to describe the relationship of pollution intensity (i) to its duration (d) and return period (T).