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Karachi is Pakistan's largest city, with all the features of a densely populated metropolitan. One of the city's significant issues is air quality, which is linked to the urban environment and pollution. The goal of this study is to show how Geographic Information Systems (GIS) can help with exposure, risk assessment, and emission predicting in Karachi. The study's major goal is to develop a GIS model that can analyze, predict, and analyze carbon monoxide (CO) levels throughout the city as pollution surface. To achieve this objective and aim, sample data have been collected, processed, and managed to generate a dynamic GIS model of Carbon monoxide levels of the study area. To better visualization and analysis, GIS and geostatistical (interpolation) models are used to develop interactive and dynamic CO pollution models. Inverse distance weighted (IDW) interpolation was used to create a surface from CO survey data. For the evaluation of CO, zonal statistics were used as districts wise Minimum, Maximum, Range, Mean and Standard Deviation values. The mean values of later districts were used for mapping displays. Data collected in the field and analyzed during the inquiry found that (CO) emissions were within acceptable ambient air quality requirements and limits. However, carbon monoxide (CO) levels are higher in business zones and commercial marketplaces in the central city, this area is more likely to cause respiratory problems. [ABSTRACT FROM AUTHOR]