Abstract
The sediment of the Sarcheshmeh copper mine in Iran contains high concentrations of trace metals. In this risk assessment study, criteria such as contamination factor, pollution load index, and geoaccumulation index were used to assess levels of Co, Cu, Mo, Zn, Cr, Mn, Ni, Pb, Ti, and Fe in the mine sediment released to the tailings dam. Expert opinions on the relative importance of each of the indicators were used to assign a final weighting of the criteria using the fuzzy Delphi analytic hierarchy process, and the metals in the sediments of the study area were ranked and clustered using the TOPSIS method. Based on the results, the metals were clustered into 10 categories with copper, iron, and zinc having the highest pollution and critical risk.
Zusammenfassung
Das Sediment des Sarchesmeh-Kupferbergwerkes im Iran zeigt hohe Konzentrationen an Spurenmetallen. Bei der vorliegenden Studie zur Gefährdungsabschätzung wurden die Kriterien wie der Kontaminationsfaktor, Umweltbelastungsindex und Geoakkumulationsindex verwendet, um den Grad der Freisetzung von Co, Cu, Mo, Zn, Cr, Mn, Ni, Pb, Ti und Fe aus den Bergbausedimenten in die Staudamm zu bestimmen. Zur relativen Wichtung der einzelnen Indikatoren wurden Expertenmeinungen eingeholt und letztendlich in einen fuzzy Delphi analytic hierarchy process verarbeitet. Die Metalle in den Sedimenten wurden anschließend mit der TOPSIS-Methode gewichtet und klassiert. Auf Basis der Ergebnisse erfolgte die Klassierung der oben genannten Metalle in 10 verschiedene Kategorien, wobei Kupfer, Eisen und Zink die größte Verschmutzung verursachen und bereits ein kritisches Niveau erreicht haben.
Resumen
El sediment de la mina de cobre Sarcheshmeh en Irán contiene altas concentraciones de metales traza. En este estudio de relevamiento ambiental, se usaron criterios tales como factor de contaminación, índice de polución e índice de geoacumulación para relevar los niveles de Co, Cu, Mo, Zn, Cr, Mn, Ni, Pb, Ti y Fe en los sedimentos de la mina provenientes del dique de cola. Se utilizaron opiniones expertas sobre la importancia relativa de cada indicador para asignar un peso final del criterio utilizando el proceso analítico hierático difuso Delphi (FDAHP) y los metales de los sedimentos en el área de estudio fueron clasificados y agrupados usando el método TOPSIS. En base a estos resultados, los metales fueron agrupados en 10 categorías con cobre, hierro y cinc presentando la máxima polución y riesgo crítico.
抽象
伊朗Sarcheshmeh铜矿矿床沉积中含有较多微量金属元素。在污染风险评估中,本文以污染因子、污染负荷指数和地质积累指数等作为评价铜矿释放至尾矿坝中的Co、 Cu、 Mo、 Zn、 Cr、 Mn、 Ni、 Pb、 Ti和Fe等污染评价指标。通过模糊德尔菲层次分析法(FDAHP)实现每一评价指标的重要性专家意见权重分配,利用TOPSIS方法实现研究区内金属离子排序、聚类。基于以上分析结果,研究区尾矿坝内金属离子被分为10类,铜、铁和锌具有最大污染风险。
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References
Abrahim GMS, Parker RJ (2008) Assessment of heavy metal enrichment factors and the degree contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand. Environ Monit Assess 136:227–238
Adama P, Arienzo M, Imporato M, Noimo D, Nardi G, Stanzione D (2005) Distribution and partition of heavy metals in surface and sub-surface sediments of Naples city port. Chemosphere 61:800–809
Adomako D, Nyarko BJB, Dampare SB, Serfor-Armah Y, Osae S, Fianko JR, Akaho EH (2008) Determination of toxic elements in waters and sediments from River Subin in the Ashanti region of Ghana. Environ Monit Assess 141:165–175
Audry S, Schafer J, Blanc G, Jouanneau JM (2004) Fifty- year sedimentary record of heavy metal pollution(Cd, Zn, Cu, Pb) in the Lot River reservoirs (France). Environ Pollut 132(3):413–426
Bermejo Santos JC, Beltran R, Gomez Araiza JL (2003) Spatial variations of heavy metals contamination in sediments from Odiel River (southwest Spain). Environ Int 29(1):69–77
Chen CW, Kao CM, Chen CF, Dong CD (2007) Distribution and accumulation of heavy metals in the sediments of Kaohsiung Harbor, Taiwan. Chemosphere 66(8):1431–1440
Deb D, Deshpande VN, Das KC (2008) Assessment of water quality around surface coal mines using principal component analysis and fuzzy reasoning techniques. Mine Water Environ 27(3):183–193
Ghrefat H, Yusuf N (2006) Assessing Mn, Fe, Cu, Zn and Cd pollution in bottom sediments of Wadi AL- Arab Dam, Jordan. Chemosphere 65:2114–2121
Golestanifar M, Ahangari K (2012) Choosing an optimal groundwater lowering technique for open pit mines. Mine Water Environ 31(3):192–198
Gonzales-Macias C, Schifter I, Liuch-Cota DB, Mendez-Rodriguez L, Hernandez-Vazquez S (2006) Distribution, enrichment and accumulation of heavy metals in coastal sediments of Salina Cruz Bay, Mexico. Environ Monit Assess 118:211–230
Hoseinie SH, Ataei M, Osanloo M (2009) A new classification system for evaluating rock penetrability. Int J Rock Mech Min Sci 46:1329–1340
Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer, Berlin
Kaufmann A, Gupta MM (1988) Fuzzy mathematical models in engineering and management science. Elsevier, Amsterdam
Liu YC, Chen CS (2007) A new approach for application of rock mass classification on rock slope stability assessment. Eng Geol 89:129–143
Muller G (1979) Schwermetalle in den sedimenten des Rheins-Veranderungen seit 1971. Umschau 79(24):778–783
Munendra S, Muller G, Sinhg B (2002) Heavy metals in freshly deposited stream sediments of rivers associated with urbanization of the Ganga plain, India. Water Air Soil Pollut 141:35–54
Qishlag A, Moore F, Forghani G (2007) Impact of untreated wastewater irrigation on soils and crops in Shiraz suburban area, SW Iran. Environ Monit Assess 149:254–262
Reddy M, Basha S, Sravan Kumar VG, Joshi HV, Ramachandraiah G (2004) Distribution, enrichment and accumulation of heavy metals in coastal sediments of the Alang-Sosiya ship scrapping yard, India. Mar Pollut Bull 48:1055–1059
Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, NYC
Selvaraj K, Rom Mohan V, Szefer P (2004) Evaluation of metal contamination in coastal sediments of the Bay of Bengal, India; geochemical and statistical approaches. Mar Pollut Bull 49:174–185
Shayestehfar MR, Rezaei A (2010) Methodology presentation in decreasing the environmental of Sarcheshmeh copper mine with the help of geochemical data. In: Proceedings of 27th Symposium on Geosciences, Tehran, Iran, p 254–264
Shayestehfar MR, Kariminasab S, Mohammadalizadeh H (2007) Mineralogy, petrology, and chemistry studies to evaluate oxide copper ores for heap leaching in Sarcheshmeh copper mine, Kerman, Iran. J Hazard Mater 154(1–3):602–612
Singh TN, Singh VK, Sinha S (2006) Prediction of cadmium removal using an artificial neural network and a neuro-fuzzy technique. Mine Water Environ 25(4):214–219
Vardes J, Var Gas G, Sifeddine M (2005) Distribution and enrichment evaluation of heavy metals in Mejillones Bay (23 AS), northern Chile: geochemical and statistical approach. Mar Pollut Bull 50:1558–1568
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Hayaty, M., Tavakoli Mohammadi, M.R., Rezaei, A. et al. Risk Assessment and Ranking of Metals Using FDAHP and TOPSIS. Mine Water Environ 33, 157–164 (2014). https://doi.org/10.1007/s10230-014-0263-y
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DOI: https://doi.org/10.1007/s10230-014-0263-y