DATA DRIVEN APPROACH FOR ASSESSING AND PREDICTING IMPACT OF METEOROLOGICAL VARIABLES ON AIR QUALITY

Abstract

Air Pollution is a serious health hazard affecting the lives of millions specifically in the Indian sub-continent. Meteorological parameters play a vital role in maintaining the air quality. Nature has its self -cleansing mechanism and it achieves that through varying weather conditions or catastrophic episodes. Studying the effect of meterological parameters on primary air pollutant concentrations serve a long way in understanding the pollutant dispersion mechanism and mitigating the long term impacts of pollutant concentration. Weather and Air quality data available in public domain of Delhi NCR is correlated and air pollutant concentration variation is studied using various machine learning algorithms in Python coding language to understand the trend and predicting their concentration under different weather condition.