Application of the first order of Markov chain model in describing the PM10 occurences in Shah Alam and Jerantut, Malaysia

Abstract

PM10 has been identified as being a common problem in Malaysia and many other countries all over the world. A Markov chain probability model is found to fit the average daily PM10 concentrations data of urban station (Shah Alam) and background area station (Jerantut) in Malaysia. This study aims to identify the occurrence of polluted and non-polluted days affected by PM10 concentrations based on data for 12 years' period (2002-2013).

Description

Keywords

Markov chain model, PM10 concentrations, polluted days, non-polluted days, occurrence

Citation

Mohamad, N. S., Deni, S. M., & Ul-Saufie, A. Z. (2018). Application of the First Order of Markov Chain Model in Describing the PM10 Occurrences in Shah Alam and Jerantut, Malaysia. Pertanika Journal of Science & Technology, 26(1).

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