Air quality assessment using spatial interpolation techniques for Kanpur city, India.

Air pollution is a significant concern for urban areas, particularly in industrial cities like Kanpur located in the state of Uttar Pradesh, India. The proposed study aims to present the findings of an assessment conducted to determine ambient air pollution during summer season for Kanpur City using the Geospatial techniques. In this context, two spatial interpolation techniques namely Inverse Distance Weighting (IDW) and Kriging were used for the analysis. The pollutant selected for the assessment was particulate matter (PM10) since it is responsible for the poor air quality in the city. Monitored Data for the pollutant were collected from different monitoring stations located across the city. Since, these monitoring locations are located at far apart distances, they fail to provide any spatial representation of the monitored pollutants, and it is in this context that spatial interpolation techniques were used for representing the air quality over the entire city. The study period selected varies from March to May 2017, representing the summer season and when dispersion characteristics of air pollutants are high. The selected interpolation techniques were used to generate spatial distribution maps of air pollution concentrations. The study aims that by using these spatial interpolation techniques a comprehensive and accurate representation of the ambient air pollution existing within the Kanpur city perimeter will be represented. Further, the suitability of the two spatial interpolation techniques used will be discussed in greater details. The maps generated through these analyses provide crucial insights into the spatial distribution and potential hotspots of air pollution within Kanpur during the summer season. The findings of this study will have significant implications for urban planning, environmental management and public health in Kanpur. It was inferred from the study that the concentration of PM was significantly higher in areas with heavy traffic and industrial activities.