Soil vulnerability to heavy metal contaminant using hierarchical fuzzy inference system and its application in GIS

Municipalities all over the world are facing serious crises from all types of pollutions (air, groundwater, soil, and water). Soil contamination is a common problem worldwide. In the past decades industrial activities have caused many types of ground contamination in urban areas. The existence of these lands and their impact on human health and the environment has led the provincial administration to apply restrains in reusing of contaminated sites (Brownfield) and to revitalize the whole sectors of the urban area. The efficiency of all investments in remediation of the contaminated sites and the living environment relies on a powerful and transparent environmental management and environmental impact assessment (EIA). A fast and applicable tool is essential for EIA or exposure analysis to identify and prioritize the contaminated sites for any management decision. In this thesis hierarchical fuzzy inference system (HFIS) was applied, and a tool was developed to introduce the critical environmental and geo-environmental factors for decision making purpose. In this technique the most pertinent factors and parameters involved in heavy metal contamination in topsoil were used to develop a powerful tool. The developed tool permitted the making of environmental decisions regarding identification of the heavy metal vulnerability in the top soil. The validation of the result of this method was satisfactory. The developed tool was applied to GIS in a case study for the Montreal Island to identify the high sorption areas and their impact on public health