An integrated approach to optimal siting of air quality monitoring networks: Fuzzy based decision-making, multi-pollutant methodology, and health risk assessment

The aim of this study is optimal siting of air quality monitoring networks (types A, B, and C) using fuzzy based multi-criteria decision-making and multi-pollutant methodology. Digital Glob and Landsat 8 satellites from Google Earth and Stichmap were used. After pre-processing, automobiles (QuickBird images), green space (NDVI), asphalt, buildings, and ground classes were separated. The produced layers were combined on the basis of the weight gained from Easy AHP. The weight of all criteria was combined by WLC method. In the fuzzy method, by selecting the fuzzy function and applying its middle point for each parameter in its raster layer in QGIS, the maps needed to locate the desired areas of stations were obtained. Based on investigated methods, as well as field visits, 10 priority points were proposed for air quality stations. The Z-score and p-value in nearest neighbor average method for fuzzy method (1.76 and 0.007) and AHP method (0.43 and 0.15) showed that the fuzzy method has the best pattern with99 % confidence in the distribution of the proposed points. Multi-pollutant methodology using XLSTAT and Map Algebra extension showed a good relationship of pollutants with layers of industrial units, commercial density, and vehicle density and suggests that most of the proposed stations in both methods with a priority of 1 to 10 are located in polluted areas of the city. The report of high pollution in the present study in some locations shows that the establishment of air quality measurement stations in Sabzevar city is a necessity.