ASSESMENT OF TEMPORAL PATTERNS AND TRENDS OF AMBIENT AIR QUALITY AROUND LANDFILLS USING LINEAR REGRESSION ANALYSIS

Abstract

Landfill is responsible for methane and carbon dioxide generation and the ground level emission like PM2.5, PM10, NO, NOx, NO2, SO2, NH3, CO, Ozone, Benzene, Toluene responsible for what we call pollution. Due to COVID-19 outbreak whole world faces lockdown which lead to the shutdown of industries, construction activities which eventually lead to decrease in pollution. Lockdown started from 24th March 2020 in four phases and then unlock from June till November, which lead to decrease in air and water pollution. In this study, concentrations of major pollutants like PM2.5, PM10, NO, NOx, NO2, SO2, NH3, CO, Ozone, Benzene, Toluene within the proximity of landfill were analysed during lockdown and unlock period and the seasonal variation of the particle has also been discussed, their regression model has been estimated to know the good fit curve. Descriptive statistics and correlation have also been estimated to know the variation of particles with each other, also how they vary with the meteorological parameter like wind speed (WS), wind direction (WD) solar radiation (SR), barometric pressure (BP), ambient temperature (AT) and rainfall (RF). Maximum PM2.5 value near Ghazipur, Narela and Okhla was 632.63 µg/m³ in 2020, 689.1 µg/m³ in 2019 and 551.19 µg/m³ in 2019 respectively, and for PM10 maximum emission for Ghazipur, Narela and Okhla was 692.3 µg/m³ in 2020, 717.35 µg/m³ in 2020 and 740.19 µg/m³ in 2020 respectively, the common thing between these emissions was that peak occurred during winter season. Even though the lockdown was there PM10 still peaked in 2020 during winter, same is the case for most of the pollutants that the emission peaked during winter season. The linear regression model has been generated using MATLAB between PM2.5 vs PM10, NO vs NOx and NO2 vs NOx, graph has shown how much error has been there between true and predicted value and how much deviation is there from regression line. The model has given RMSE, MSE, MAE and R-Squared value for each regression model with their governing linear equation, model between NO2 vs NOx has given negative intercept meaning that the oxide of nitrogen (NOx) decreases as the nitrogen dioxide (NO2) increases, other model has given positive intercept. study gives governing bodies that during crisis of air pollution certain measures can be taken to improve the condition of air quality otherwise detrimental effect of these can be seen every year to the people.