Siting MSW landfill using weighted linear combination and analytical hierarchy process (AHP) methodology in GIS environment (case study: Karaj)

Selection of landfill site is a complex process and needs many diverse criteria. The purpose of this paper is to evaluate the suitability of the studied site as landfill for MSW in Karaj. Using weighted linear combination (WLC) method and spatial cluster analysis (SCA), suitable sites for allocation of landfill for a 20-year period were identified. For analyzing spatial auto-correlation of the land suitability map layer (LSML), Maron’s I was used. Finally, using the analytical hierarchy process (AHP), the most preferred alternative for the landfill siting was identified. Main advantages of AHP are: relative ease of handling multiple criteria, easy to understand and effective handling of both qualitative and quantitative data.As a result, 6% of the study area is suitable for landfill siting and third alternative was identified as the most preferred for siting MSW landfill by AHP.The ranking of alternatives were obtained only by applying the WLC approach showed different results from the AHP. The WLC should be used only for the identification of alternatives and the AHP is used for prioritization. We suggest the employed procedure for other similar regions.     

Statistical source identification of major and trace elements in groundwater downward the tailings dam of Miduk Copper Complex, Kerman, Iran

Identifying the possible sources of potential harmful metals in groundwater systems plays a crucial role in evaluating the potential risks to residents and local plant cover. An attempt was made to define the origin of Al, Cd, Cu, Fe, Mo, Ni, and Pb in groundwater using multivariate statistic approaches [principal component analysis (PCA), hierarchical cluster analysis], and tailings sequential extraction by the method of Tessier et al. The concentrations of studied elements were measured in 42 samples collected from 15 stations surrounding and downward the tailings dam of Miduk Copper Complex, central province of Kerman, Iran. According to the PCA results, confirmed by cluster dendrogram and metal content measurement of tailings sequential extracts, two components accounting for nearly 73% of the total variance, controlled the heavy metal variability and classified the possible source of groundwater contamination into two categories: (1) upper seepage which controls the variability of Cd, Cu, Fe, Ni, and Pb and (2) toe seepage of tailings dump affecting on Mo and Al concentration in downstream groundwater.     

Evaluating the metallic pollution of riverine water and sediments: a case study of Aras River

Metallic pollution caused by elements Zn, Cu, Fe, Pb, Ni, Cd, and Hg in water and sediments of Aras River within a specific area in Ardabil province of Iran is considered. Water and sediment samples were collected seasonally and once respectively from the five selected stations. Regarding WHO published permissible values, only Ni concentration in spring and summer water samples has exceeded the acceptable limit up to four times greater than the limit. The concentration of metals Ni, Pb, and Fe in river water shows a direct relationship with river water discharge and the amount of precipitation. Enhanced soil erosion, bed load dissolution, and runoffs may play a key role in remarkable augmentation of metallic ions concentration. Furthermore, excessive use of pesticides which contain a variety of metallic ions (mainly Cu) in spring and summer may also result in an increase in the metals’ concentration. The potential risk of Ni exposure to the water environment of the study area is assigned to juice, dairy products, edible oil, and sugar cane factories as well as soybean crop lands which are located within the sub-basin of Aras River in the study area. Regarding the sediment samples, the bioavailable metal concentrations indicate an ascending order from the first station towards the last one. In comparison with earth crust, sedimental and igneous rocks the reported metallic concentration values, except for Cd, lie within the low-risk status. Regarding Cd, the reported values in some stations (S2, S4, and S5) are up to ten times greater than that of shale which may be considered as a remarkable risk potential. The industrial and municipal wastewater generated by Parsabad moqan industrial complex and residential areas, in addition to the discharges of animal husbandry centers, may be addressed as the key factors in the sharp increase of metallic pollution potential in stations 4 and 5.     

An improved optimization model for predicting Pb recovery efficiency from residual of liberator cells: a hybrid of support vector regression and modified tunicate swarm algorithm

Journal of Material Cycles and Waste Management - In this study, a hybrid of support vector regression and a modified tunicate swarm algorithm (SVR-MTSA) strategy is developed to optimize the...