Comparative health risk assessment of nitrate in drinking groundwater resources of urban and rural regions (Isfahan, Iran), using GIS

Gis-Based Assessment of Risk for Drinking Water Contamination to Children’s Health in Rural Settlements

Nitrates and heavy metals are two of the most significant groundwater pollutants that have an impact on people’s health all around the world. In order to assess their risk to children’s health, this study aims to determine the total iron, manganese, and nitrate content in drinking water sources of non-centralized water supply of the educational institutions in the rural settlements of Zhytomyr region. A total of 114 water samples from wells and bores used by the educational institutions to supply domestic and drinking water to rural residential areas were collected. The Measurement Laboratory of Polissia National University conducted analytical studies. The danger to children’s health was evaluated using the hazard quotient and following the methodology recommended by the US Environmental Protection Agency. The software ArcGIS Pro was used to identify risk zones.

The average total iron content in the drinking water of the Berdichev, Zhytomyr, and Novohrad-Volinsky districts was 1.5–2.8 times higher. In all regions, the average manganese concentration did not go above the allowable level. On average, the nitrate content was also below the threshold, but in 22.6–42.9% of the samples, it exceeded the allowable level. Children aged 6–12 years were at the highest risk, and children living in Berdichev district had the highest hazard quotient at 1.972. The fact that nitrates accounted for 67–84% of the total risk indicates the danger associated with the intake of nitrates, even in amounts below the allowable concentration.

A GIS-based multi-criteria fuzzy approach to select a suitable location for a MSW-based power plant and landfill: a case study, Khuzestan province, Iran

The aim of this study was to find the best location for municipal solid waste (MSW)-based power plant and landfill. Another goal was to investigate the energy recovery potential of MSW by anaerobic digestion and recycling process. A combination of multi-criteria fuzzy decision making system was applied in GIS environment to select the most suitable site for MSW-based power plant and landfill. The effective sub-criteria were classified into three main categories of environmental, social, and economic criteria, and fuzzy analytic hierarchy process was used to weight and integrate them. The method was used in a case study to find the best location of MSW-based plant and landfill in Khuzestan province, Iran. Based on the amount of MSW production in this province and as a result, the potential for energy savings by recycling the recyclable part and recovering energy from the digestible part, the amount of fossil fuel that can be saved and the emission of greenhouse gases that can be avoided were estimated. Based on the results, in total, recycling the recyclable portion (dry waste) and producing energy from the digestible portion (wet waste) of MSW in Khuzestan province, leads to avoid burning 7.4 billion MJ of fossil fuels and emitting 644,169 t of CO₂eq GHG. The results also showed that the integration of fuzzy logic and multi-criteria fuzzy decision making system provides more flexibility in choosing the best location for the MSW-based plant. This method is flexible enough and in other situations can include other necessary criteria and can provide a comprehensive guideline for decision makers in choosing the optimal location for a power plant or a landfill.