ANALYSIS OF GHAZIABAD AS CRITICALLY POLLUTED AREA USING CEPI

Abstract

Environmental pollution has been a challenging issue for the past few decades and it endangers the health of livings and it have been aggravated by industrialization across the country. Industrial developments could not be ignored as they are backbone of economicsofacountry. The Study is typically based on the usage of data of monitored ambient air pollution, Surface water pollution and Groundwater pollution from various point locations in study area. The pollutant concentration is averaged over these selected locations by using GIS to know the spatial variations of pollutants over the study area and thus to estimate pollution exposure. Environmental pollution index (EPI) is calculated by selecting 3 most critical pollutants dependingontheconcentrationandexceedanceforAir,SurfacewaterandGroundwater. Thereafter, Comprehensive Environmental Pollution Index (CEPI) is calculated by selecting three parameters in air, water and Groundwater for 17 Air quality monitoring locations, 06 Surface water quality monitoring locations and 16 Groundwater quality monitoring locations in Ghaziabad. “In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the Ghaziabad District of Uttar Pradesh, India,whichisoneofthemosthighlyindustrializedcitiesinIndia. Studies have revealed several critical situations in this area, in terms of short-term health effects of air pollution. The objectives of this project report are to study the variability of pollutants in Air, Surface water and Groundwater in the Ghaziabad and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data is studied for year 2009, 2011, 2013 and 2018 and analyzed. Relative and absolute spatial concentration variations were investigated by means of Inverse distance weighting (IDW), which is a type of deterministic method for multivariate interpolation with a known scattered set of points. The assigned values to unknown points are calculated with a weighted averageofthevalues availableattheknown points.Resultsshowsignificantdifferences among stations. The highest correlation between stations was observed for PM10, CO and PM2.5 concentrations for air, Total Phosphorus, Phenol and BOD for Surface water and Total Hardness, Mercury and TDS for Groundwater. Results suggest evaluating the population exposureto pollutantsinstudy areabytakingin to account the possiblezones of influence of different emission sources. Present research forms important baseline for furtherresearchinthisarea.