To find out the most prominent pollutant concerning AQI statistically, we have done Pearson’s correlation analysis by the means of plotting heatmaps corresponding to each site. Pearson’s correlation is also known as the “product-moment correlation coefficient” (PMCC) and is suitable for measuring the extent of the linear relationship between any two quantitative variables statistically. A Pearson’s correlation is a number ranging between − 1 and + 1 showing negative to positive linear correlation. Given a pair of random variables (X1, X2), the formula for Pearson’s correlation is given by\documentclass[12pt]{minimal} 				\usepackage{amsmath} 				\usepackage{wasysym} 				\usepackage{amsfonts} 				\usepackage{amssymb} 				\usepackage{amsbsy} 				\usepackage{mathrsfs} 				\usepackage{upgreek} 				\setlength{\oddsidemargin}{-69pt} 				\begin{document}$${\rho}_{X_1,{X}_2}=\frac{Cov\left({X}_1,{X}_2\right)}{\sigma_{X_1}\ {\sigma}_{X_2}}$$\end{document}ρX1,X2=CovX1X2σX1σX2where Cov(X1, X2) is the covariance between the variables under study and \documentclass[12pt]{minimal} 				\usepackage{amsmath} 				\usepackage{wasysym} 				\usepackage{amsfonts} 				\usepackage{amssymb} 				\usepackage{amsbsy} 				\usepackage{mathrsfs} 				\usepackage{upgreek} 				\setlength{\oddsidemargin}{-69pt} 				\begin{document}$${\sigma}_{X_1},{\sigma}_{X_2}$$\end{document}σX1,σX2 are the standard deviation of X1, X2 respectively.