Geographic Information Systems for Appraisal of Spatial Disparities of Air Pollution in Karachi

Arsalan, Mudassar Hassan · 2004 · Crossref

DOI: 10.31384/jisrmsse/2004.02.2.2

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Summary

This study addresses the critical environmental health issue of air pollution in Karachi, Pakistan, the country’s largest metropolis. Motivated by rapid urbanization, industrial growth, and the lack of spatial analysis techniques in developing nations, the research aims to evaluate the spatial disparities of air pollution using Geographic Information Systems (GIS). The authors identify traffic and industrial activity as primary pollution sources and seek to develop a prototype monitoring system capable of mapping concentration patterns and risk zones, which could serve as a model for nationwide environmental monitoring. The methodology combines remote sensing, statistical data, and GIS modeling. SPOT satellite imagery was utilized to map Karachi’s road network, while air quality statistics were sourced from a collaborative project between the Space and Upper Atmosphere Research Commission (SUPARCO) and Karachi Electric Supply Corporation (KESC). Data on Total Suspended Particulates (TSP), Nitrogen Oxides (NOx), Sulphur Dioxide (SO2), Carbon Monoxide (CO), and Surface Ozone (O3) were collected from eleven specific sites across the city. The researchers employed Inverse Distance Weighted (IDW) interpolation to generate continuous raster surfaces from these point data. Subsequently, map algebra was used to reclassify pollutant concentrations into weighted classes and calculate a cumulative risk index, integrating the impacts of multiple pollutants to identify high-risk areas. The results indicate that Karachi suffers from severe air pollution, with atmospheric levels 40% higher than other Pakistani cities. Specific findings reveal that industrial activities, particularly at the Bin Qasim thermal power plant and Pakistan Steel Mills, are the prime contributors to SO2 emissions. Vehicular traffic, notably from rickshaws and buses, is identified as the major source of CO and PM10. The spatial analysis highlights three distinct high-risk zones: the densely built-up old city area (District South), the Landhi Korangi industrial/residential area (District East), and the SITE Industrial region (District West). These areas exhibit elevated concentrations of TSP, NOx, and O3, correlating with heavy traffic volumes and industrial proximity. The study notes that while average TSP levels generally remained within US-EPA permissible limits, specific vicinities like Korangi and Elender Road exceeded these thresholds. The significance of this work lies in its demonstration of GIS as an effective tool for environmental investigation in developing countries. By merging grid layers through algebraic functions, the study provides a comprehensive view of cumulative pollution intensity, moving beyond isolated point measurements. The findings underscore the urgent need for remedial measures targeting vehicular emissions and industrial outputs. The authors conclude that this prototype system validates the use of spatial interpolation and risk evaluation for monitoring large metropolises, recommending further micro-geographic studies with larger sample sizes to better assess health impacts and inform policy.

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