Assessment of AIR Quality Index for Delhi region: A comparison between odd-even policy 2019 and Lock Down Period

The aim behind doing this research is to analyse the impact of odd-even policy and lockdown implementation on the air quality index of Delhi by doing the case study on the four regions Ashok Vihar, Anand Vihar, Dwarka and R.K. Puram. The data is been collected from DPCC and the main parameters we looked for are PM10 and PM2.5. In which we find out that. highest levels of the pollutants PM10 and PM2.5 been observed during the time of odd-even policy implementation for the year 2019 (04 November 2019- 15 November 2019) whereas during the lockdown period (23 March 2020-31st August 2020) a great decline in pollutant levels is been detected. This we further try to correlate with the spatial variations of Delhi region and able to discern that meteorological parameters (Ambient Temperature, Relative Humidity, Wind Speed and Solar Radiations) in respect with seasonal variations have a major influence on PM 10 and PM 2.5 levels. During the winter season both the parameters PM10 & PM2.5 are touching the peak because of the impact of three major meteorological parameters Ambient Temperature, Wind Speed and Solar Radiation and during the monsoon season air quality conditions are quite favourable because of Ambient Temperature and Wind Speed parameters. In the end we use the ensembled machine learning algorithms like Random Forest and Extra trees regressor to have an accurate estimation of PM2.5 levels for all the four regions of Delhi and perceived that these ensembled learning techniques are better than other machine learning algorithms like Neural Networks, Linear regression and SVMs. The Random Forest and Extra trees regressor models give the R2 value 0.75 and 0.78 respectively for estimation of PM2.5; R2 value is a statistical measurement which explains the variance of dependent variable based on the independent variables of a regression model.