A Fuzzy-Based Model to Detect Hotspots of Air Pollutants During Heatwaves in Urban Settlements

High concentrations of pollutants in urban areas generate cardiovascular and respiratory problems in citizens; these are aggravated by the persistence of summer heat waves. For this reason, in this research, we propose a fuzzy-based method for detecting air pollutant hotspots and determining critical urban areas for air pollution during heat waves. After acquiring the pollutant concentration values recorded by monitoring stations during heatwaves, a spatial interpolation method is applied to obtain the distribution of the pollutant concentration during heatwaves and, subsequently, a fuzzification process is performed to determine urban hotspots in which the pollutant concentration assumes critical values. Finally, the critical urban areas are determined, consisting of the areas within hotspots with a high population density exposed to health risks. The method was implemented in a GIS platform and tested on an urban study area in the Lombardy region, Italy, to determine the urban areas with high criticality during the heatwaves that occurred in the summer months of 2024. The test results show that the method can provide valid support for decision makers and local administrators when evaluating which urban areas are most critical for the population due to the high rate of air pollution during heatwaves.