Assessment of spatio-temporal variations in air quality of Jaipur city, Rajasthan, India

Abstract

This paper presents the evaluation of air quality in different wards of Jaipur city. Geo-spatial and geo-statistical techniques were utilized to estimate the seasonal and temporal variations (2004–2015) of gaseous and particulate pollutants. Data of six fixed monitoring stations was collected from Central Pollution Control Board (CPCB) and Rajasthan Pollution Control Board (RPCB) and the relationship between air quality and local weather parameters were also analyzed for the Jaipur city. It was found that SPM and PM10 is the major contributor to the deterioration of air quality in Jaipur city, while NOX and SO2 concentrations were below the CPCB standards. Results show that the concentrations of the air pollutants are high in winter and summer in comparison to the monsoon. The spatio-temporal distribution of Air Quality Index (AQI) clearly depicts the severe air pollution in Vidhyadhar nagar, Civil lines, Hawa Mahal, Kishanpole and Aadarsh Nagar area of Jaipur city. Ordinary least square (OLS) regression reveals good correlation between AQI and weather conditions (temperature, relative humidity and wind speed) for summer and winter seasons. The spatial analysis was also conducted to ascertain the degree of spatial association between AQI and weather conditions in different wards of Jaipur city using bivariate Moran’s I and LISA (Local Indicator of Spatial Association). Moran’s I results imply strong positive autocorrelation between AQI and relative humidity followed by temperature and wind speed. The combination of GIS and statistical analyses contributes to characterize the spatial influences of weather conditions on air pollutants and provide a quick view of the relatively critical areas that need more attention from decision makers to initiate the policies geared towards developing appropriate strategies for reducing air pollution. Keywords: Air quality, Geographical information system, Spatial autocorrelation, Bivariate Moran’s I, LISA