Abstract

Air pollution is characterised as the presence of one or more pollutants in the outdoor environment, such as dust, gases, mist, odour, smoke, or vapour. They are harmful to human, plant, or animal life or property or interfere with the healthy nature of life or property in specific amounts, characteristics, or periods. This study aimed to investigate the characteristics of ambient air pollution through relations between determinants to each SO2, NO2, PM10, and suspended particulate matter (SPM) by applying linear regression. The data has been obtained from the official websites of the Indian government based on the real-time pollutant concentrations monitored by stations in an urban and resident areas from 2000 until 2015. The data consisted of eight (8) variables; SO2, NO2, PM10, and SPM as outcomes, month, year, area, and monitoring stations as determinants. The model showed that the month, year, monitoring station, and area were correlated to SO2, NO2, and PM10 concentration. Yet, in SPM concentration, month, year, the station was correlated. The area was not correlated to SPM. Investigation of other predictors was needed to gain information about the increasing air pollution on a global scale.