Prediction PM10 Concentration Using VAR Time Series - R, Norazrin; Shukri Yahaya, Ahmad; Abdul Hamid, Hazrul (International Journal of Engineering and Technology, 2018)
This paper presents a case study from Kangar’s monitoring station using a monthly average data (1999-2015).  The objective of this study is to predict the PM10 concentration by using the VAR time series model. This model was adapted to quantify and understand the interaction of PM10 concentration and meteorological parameters for air quality control using (temperature, wind speed, and relative humidity) as independent parameters and particulate matter (PM10) as a dependent parameter. The performance indicator results were (R2 = 0.887), (IA = 0.954), (PA=0.966), and (NAE=0.087) respectively. This study indicates that the VAR time series model is a good model to predict PM10 concentration since the results obtained are close to the performance criteria.