Probabilistic And Distribution Modelling For Predicting Pm10 Concentration In Malaysia
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Date
2013-06
Authors
Hamid, Hazrul Abdul
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Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
The decline in air quality can have a significant impact, particularly on human health. The elderly, children and people with asthma are among the most affected if faced with low air quality level. In Malaysia, the Department of Environment is responsible for monitoring and recording air quality and at this point, there are a total of 52 air quality monitoring stations operated by Alam Sekitar Malaysia Berhad (ASMA). The parameters monitored are airborne particles smaller than 10 μm, sulphur dioxide, nitrogen dioxide, carbon monoxide, ambient temperature, relative humidity and wind speed. It is important to do air pollution forecasting to give an early warning to people in addition to help the management of air quality by the local authorities. Since the forecasting model for air pollutants previously developed only focused on statistical distribution model with two parameters for long-term forecasting, this research compares the three parameter statistical distributions technique to search for the best models for improving the prediction accuracy. Seven air quality monitoring stations chosen in this study represent the industrial area (Nilai, Kuching and Seberang Perai), urban and sub-urban areas (Bachang, Kuala Terengganu and Seberang Jaya) and one station categorized as the background station which is Jerantut. Hourly PM10 concentrations from 2003 to 2009 are used to assess and compare the behaviour of PM10 concentrations at the selected monitoring stations. These monitoring records are also used to obtain the best statistical distribution models.
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Keywords
Probabilistic And Distribution , Pm10 Concentration In Malaysia