Application of geostatistical models to identify spatial distribution of groundwater quality parameters.

Groundwater quality management is a priority in arid and semi-arid zones where water is scarce. Leachate from open dumping of municipal solid wastes may threaten groundwater quality. This research aimed at assessing groundwater quality of the aquifer of Shur river basin in Tehran province, Iran. The pollution potential of leachate from a landfill, located at the center of the basin, was estimated to assess its impact on the aquifer. Samples from 38 wells and 2 leachate ponds around the landfill were analyzed for their physico-chemical parameters and heavy metals. Leachate Pollution Index (LPI) and Water Quality Index (WQI) were calculated and multivariate statistical techniques were employed through geostatistical models to predict the spatial variability of groundwater quality and assess its contamination sources. The groundwater quality map was developed by GIS Interface. LPI indicated that leachate from the closed cell (LPI = 36) was more contaminating than that of the active site (LPI = 25). Kriging and cokriging geostatistical interpolation methods were applied to groundwater quality parameters. The best interpolation model was then identified through cross-validation with RMSE and GSD criteria. Cokriging yielded more accurate results than kriging. Spatial distribution maps showed high groundwater contamination and degraded water quality mainly in the central part of the basin, where the landfill was. Also, 293.7 ha of the study area possessed poor and very poor water quality, unsuitable for drinking. This study implicated multiple approaches for groundwater quality assessment and estimated its spatial structure as an effort toward effective groundwater quality management in Shur river basin.

Application of MCAT to provide multi-objective optimization model for municipal waste management system.

Choosing an appropriate municipal waste management method is a very complicated environmental problem in cities. This research introduces an optimization model for waste management in the southwest region of Tehran province. It was developed by a metaheuristic algorithm that was used to minimize the economic and environmental costs. Incineration, composting, recycling and landfilling waste management methods were considered. Three scenarios were developed to determine the optimum allocation of waste to each method such to fulfill the objective of overall minimum of environmental burdens and costs. A multi-objective scenario selection model was implemented by the compromise programming method in MCAT software. Considering the budget limitation and available facilities on site, optimum allocations to recycling, composting, incineration and landfilling methods were obtained as 115,486, 132,094, 71,905 and 45,516 tons/year, respectively. The results of this study indicated that the metaheuristic algorithm in MCAT software was an efficient tool in decision making about waste management systems and thus, it was suggested to municipality managers and regional planning authorities.