Diagnostic Analysis and Modelling of Air Quality for Medium Sized City

Abstract

It is witnessed that air pollution is an important issue regarding not only for human health but also for plants, animals and building materials. Increase in industrialisation, abundant use of automobiles, and network of highways, the quality of air of Amravati city is degrading day by day. The data has been collected for a period ranging from March 2020 to February 2021 for analysis and pollution forecasting model work. The concentration of Suspended Particulate Matter (SPM), Respiratory Suspended Particulate Matter (RSPM), Sulphur dioxide (SO2), Nitrogen dioxide (NO2) and Ozone (O3) have been monitored over successive periods of time and also data is collected from monitoring stations controlled by MPCB. Numerous studies have been proposed for predicting pollution concentrations and improvement of performance of predictable models is an important issue. As is well known, collaborative observations proved that it can improve predictive performance. In this study, multivariate linear regression approach-based model was constructed to predict the RSPM in the air using the meteorological (air temperature, relative humidity, wind speed, rainfall) and air quality monitoring data (SPM, NO2, SO2, O3). Correlation between measured and model predicted vales of RSPM were 0.717,0.691,0.64 and 0.60 for winter, summer, monsoon and annual seasons respectively. However, the regression model based on seasonal data for winter was found to be more effective.