PM10 Modeling by using Time Series Analysis in Oil and Gas Industry

High particulate event has been caught to attention for a long time as it cannot be controlled by humans to reduce it. However, high particulate event usually can be predicted as it is categorized as air pollution which means it is caused by human activities such as open burning, motor vehicles, and industrial activities. As time goes on, it can be generalized that high particulate is most likely to occur during the dry season, which is from February to April due to several meteorological factors such as wind speed, humidity and temperature. In this study, the main aim is to monitor the concentration of the pollutant which is particulate matter with aerodynamic diameter less than 10 micrometer (PM10) and it will be focused on oil and industry area. This is to allow understanding in the concentration pattern of the pollutant in industrial area particularly in oil and gas industry. Through that, the meteorological factor that may affect the occurrence of high particulate event can be identified and will be able to relate with the occurrence of high particulate event. The sample of pollutant was collected from various locations and it was collected hourly for 24 hours per day for 3 years that is from 2008 to 2010, using the equipment Aeroqual AQM 60. From the analyzed data, the concentration of PM10 in oil and gas industry was found to exceed the Malaysian Ambient Air Quality Guidelines (MAAQG) that has been set by the Malaysia’s Department of Environment (DOE). The meteorological factor such as humidity and ambient temperature was determined and is believed to have effects on the PM10 concentration in oil and gas industry. It was concluded that there are relation between the pollutants and meteorological factor.