文章基本信息

标题：Modeling of Daily PM₁₀ Concentration Occurrence Using Markov Chain Model in Shah Alam, Malaysia
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作者：Norsalwani Mohamad ; Sayang Mohd Deni ; Ahmad Zia Ul-Saufie Mohamad Japeri 等
期刊名称：Journal of Environmental Science and Technology
印刷版ISSN：1994-7887
电子版ISSN：2077-2181
出版年度：2017
卷号：10
期号：2
页码：96-106
DOI：10.3923/jest.2017.96.106
出版社：Asian Network for Scientific Information
摘要：Background and Objective: The analysis of the behavior of daily PM₁₀ occurrence is becoming important nowadays and the results obtained may be useful for the prediction and decision making purposes. This study considered the behavior of PM₁₀ concentration that related with its dependency nature. Therefore, this study is attempted to determine the sequences of polluted and non-polluted days affected by PM₁₀ concentration based on the optimum order of a Markov chain model. Methodology: Twelve years of monitoring records which is from 2002-2013 and have been analyzed for this purpose. The PM₁₀ concentration data that possess Markov chain properties show that the successive event is dependent on the previous event and is suited for further analysis using this model. Results: The optimum order of the Markov chain model for Shah Alam monitoring station shows that the order of two and three are optimum for threshold values less than 120 μg m³ and a simple order is optimum for a threshold value of 150 μg m³. The results mean that the occurrence of the polluted or non-polluted days affected by PM₁₀ is dependent on the 2 or 3 days before the observed day for threshold value less than 120 μg m³. For a threshold value of 150 μg m³, the occurrence depends only on a day before the observed day. Besides that, the distribution of polluted events is well fitted based on the optimum order for each threshold value used. Conclusion: The information of polluted (non-polluted) occurrences is important in monitoring the PM₁₀ concentrations which can be used for predicting related future events and helpful in providing the necessary precautionary measures to public and protect their health.