ANALYSIS OF PARTICULATE MATTER (PM10) IN MALAYSIA USING MARKOV CHAIN MODEL

These Particulates matter (PM_10) received great attention due to its potential to cause adverse health effects. This study proposes the application of Markov chain model onto extreme (PM_10) concentration. Data of daily maximum (PM_10) concentration for fifteen years at ten different locations of the monitoring stations selected at random was observed. Transition probability matrix determined and Markov chain model was fitted. Chisquare test for independence was conducted. States of transition are dependent of the observatory stations and the state transition chain does follow Markov chain property. The behavior of the transition state shows that Pasir Gudang, Petaling Jaya and Melaka recorded to have the highest value of (PM_10) concentration while Kota Kinabalu has recorded the healthiest Air Pollutant Index (API) value throughout the past fifteen years. The number of transitions of days for the value of (PM_10) concentration to be in its steadystate for each station is between 36 to 79 days.