Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach

Abstract

Air pollution has emerged as one of the major public health threats. In recent years, Bangladesh has ranked among top air polluted countries around the globe. Air quality in Bangladesh is measured on daily basis using national standards of five pollutants—NO₂, CO, Ozone (O₃), SO₂, and particulate matter (PM_2.5 and PM₁₀) and presented as indexed value ranged from 0 to 500 which is further classified from good to extremely unhealthy. In this study, we have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast weekly air quality of Dhaka and Sylhet divisions in Bangladesh. Our study reveals the existence of seasonal pattern of the air quality and suggests extremely unhealthy and very unhealthy air in January–March 2020. Therefore, policymaker should address this period as the air quality directly influences public health.