Time Series Analysis and Forecasting of Air Pollution Particulate Matter (PM2.5): An SARIMA and Factor Analysis Approach

Current development of Pakistanrsquo;s economy, transportation and industry with the improvement of urbanization, environmental pollution problems have gradually become prominent, but this is contrary to peoplersquo;s vision of pursuing a high-quality life. Now the problem of haze, photochemical problems in the air, and global warming is already a key issue of global concern. This is focused on the ambient air quality of Lahore city of Pakistan. The study reveals that the particulate matter in the Lahore season (PMnbsp;_2.5nbsp;, PMnbsp;₁₀nbsp;) exceeds Pakistanrsquo;s National Environmental Quality Standards (NEQS). Correlation study suggests the positive correlation between the particulate matter and other mass concentration particles like Ozone (Onbsp;₃nbsp;), Nitrogen Oxide (NO), Sulphur Dioxide (SOnbsp;₂nbsp;). Higher values of CO/NO suggest that mobile sources are one of the major factors of this increase in NO. Further estimation of backward trajectory is done by the Hybrid-Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model which provides the path of those particles in the last year period and the source of origin is from Afghanistan. This study provides in depth analysis of all factors of air pollutants by correlation between those factors. Prediction of future concentration of PMnbsp;_2.5nbsp;is predicted using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model which gives the increasing value of PMnbsp;_2.5nbsp;in next year and provides the lowest and highest predicts