پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 163 |
| تعداد شماره‌ها | 6,762 |
| تعداد مقالات | 72,833 |
| تعداد مشاهده مقاله | 131,762,167 |
| تعداد دریافت فایل اصل مقاله | 103,491,187 |
ارزیابی شاخصهای آلودگی فلزات سنگین در آب‌های سطحی معدن مس سرچشمه با روش‌های آماری چندمتغیره و GIS | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 14، دوره 50، شماره 1، فروردین و اردیبهشت 1398، صفحه 161-176 اصل مقاله (1.4 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2018.254261.667869 | ||
| نویسندگان | ||
| اکرم سیفی* ؛ حسین ریاحی | ||
| استادیار گروه مهندسی آب، دانشگاه ولیعصر (عج) رفسنجان، ایران | ||
| چکیده | ||
| معدن مس سرچشمه دومین معدن روباز مس بزرگ جهان است که فعالیتهای معدنی، عملیات آبگیری و سدسازی آن میتواند سبب آلودگی منابع آب سطحی و زیرسطحی منطقه شود. در این مطالعه به منظور ارزیابی غلظت فلزات سنگین در 82 نمونه آب سطحی (924 پارامتر کیفی) از شاخص آلودگی فلزات سنگین (HPI)، شاخص ارزیابی فلزات سنگین (HEI) و درجه آلودگی (Cd) استفاده شده است. همچنین متغیرهای اصلی مؤثر بر شاخصهای آلودگی با استفاده از تحلیل مؤلفههای اصلی (PCA) شناسایی و از ترکیب PCA و مدل رگرسیون خطی چندگانه (MLR) به منظور تدوین روابط جدید برای محاسبه شاخصهای HPI, HEI, Cd با حداقل پارامترهای مورد نیاز استفاده شد. منطقه مورد بررسی به سه زیربخش با فعالیتهای مختلف تقسیم و غلظت عناصر سنگین آب در هر زیربخش با حداکثر مجاز قابل شرب WHO مقایسه شد. با توجه به نقشههای پهنهبندی GIS، بیشترین مقادیر فلزات در سایتهای معدنکاری و در سد رسوبگیر و کمترین آنها در رودخانه شور مشاهده شد. طبق نتایج شاخص HPI، 70 درصد نمونهها در محدوده بحرانی 100 تا 3/482245 قرار گرفتند و فقط 30 درصد از نمونهها در طبقه آلودگی کم قرار داشتند. نتایج شاخصهای HEI و Cd نشان دادند که به ترتیب 79 (96%) و 69 (٪2/84) نمونه به فلزات سنگین آلوده میباشند. چهار مؤلفه اصلی با روش PCA انتخاب که مؤلفه اول با 3/63 درصد از واریانس کل دادهها شامل بارگذاری عناصر آلومینیوم، کادمیوم، کبالت، آهن، روی، منگنز و نیکل بود. علیرغم محدوده بسیار وسیع تغییرات شاخصها، کارآیی مطلوب روابط پیشنهادی MLR-PCA با تعداد متغیرهای کمتر برای منطقه مطالعاتی تائید شد. از یافتههای تحقیق حاضر و روابط خطی پیشنهادی میتوان به منظور بررسی اقدامات پیشگیرانه و کنترل آلودگی آبها به فلزات سنگین در آینده در منطقه مس سرچشمه و توسعه روابطی برای مناطق مشابه استفاده کرد. | ||
| کلیدواژه‌ها | ||
| تحلیل خوشه‌ای؛ تحلیل مؤلفههای اصلی؛ حد بحرانی آلودگی؛ درجه آلودگی؛ طبقه‌بندی کیفی | ||
| عنوان مقاله [English] | ||
| Evaluation of Heavy Metal Pollution Indices for Surface Water of the Sarcheshmeh Copper Mine using Multivariate Statistical Methods and GIS | ||
| نویسندگان [English] | ||
| Akram Seifi؛ Hossien Riahi | ||
| Assistant Professor, Department of Water Engineering, Vali-e-Asr University, Rafsanjan, Iran | ||
| چکیده [English] | ||
| Sarcheshmeh copper mine is the second largest open-pit copper mine in the world which its mining activities, dewatering operations, and dam construction could cause pollution to the surface and groundwater of the region. In this study, the heavy metal pollution index (HPI), heavy metal evaluation index (HEI), and degree of contamination (Cd) were used to evaluate heavy metal concentration in the 82 samples of surface water. Also, the main effective parameters on the heavy metal pollution indices were investigated using principal component analysis (PCA). The hybrid multiple linear regression (MLR) and PCA model was used to develop new equations for HPI, HEI, and Cd indices using minimum number of heavy metal variables. The study area was divided into three sub-sections with different mining activities. The concentrations of elements in water samples were compared with the maximum admissible concentration values of WHO standard for drinking purposes. Based on the spatial distribution maps in GIS, the highest concentrations of heavy metals were found in mining sites and sedimentary dam, and the lowest ones found in the Shour River. Based on the HPI values, 70% of the samples were in the critical range of 100- 482245.3 and only 30% of samples were classified as having low pollution levels. The HEI and Cd results revealed that the 79 (96%) and 69 (84.2%) samples were polluted with heavy metals, respectively. The PCA extracted four components, of which the first component with 63.3% of the total variance contains high loadings for Al, Cd, Co, Fe, Zn, Mn, and Ni elements. Despite of very wide ranges of indices variation, the accuracy of proposed MLR-PCA model was confirmed for less number variables in the study area. Findings of this study can be used for investigating preventive measures and to control pollution in the study area and similar regions for drinking purposes in the future. | ||
| کلیدواژه‌ها [English] | ||
| Cluster Analysis, Principal Component Analysis, Pollutant critical limit, Degree of contamination, Quality classification | ||
| مراجع | ||
|
Ahmad, Z., Rahim, N. A., Bahadori, A. and Zhang, J. (2017). Improving water quality index prediction in Perak River basin Malaysia through a combination of multiple neural networks. International Journal of River Basin Management, 15(1), 79-87. Akoto, O., Bruce, T. N. and Darko, D. (2008). Heavy metals pollution profiles in streams serving the Owabi reservoir. African Journal of Environmental Science and Technology, 2(11), 354-359. Araghi Nezhad, S., Dezfuli, D., Hosseini Moghari, S. M. and Ebrahimi, K. (2017). Water quality classification based on minimum qualitative parameter (Case Study: Karun River). Natural environment, 70(3), 583-595 (In Farsi). Cheng, H., & Hu, Y. (2010). Lead (Pb) isotopic fingerprinting and its applications in lead pollution studies in China: a review. Environmental Pollution, 158(5), 1134-1146. Edet, A. E. and Offiong, O. E. (2002). Evaluation of water quality pollution indices for heavy metal contamination monitoring.A study case from Akpabuyo-Odukpani area, Lower Cross River Basin (southeastern Nigeria). GeoJournal, 57(4), 295-304. Fakhri, M.S., Asghari Moghaddam, A. and Najib, M. (2016). Application of statistical methods and saturation indices in groundwater quality assessment of the Marand plain. Water and Soil Conservation, 22(6): 117-133 (In Farsi). Ficklin, W. H., Plumlee, G. S., Smith, K. S. and McHugh, J. B. (1992). Geochemical classification of mine drainages and natural drainages in mineralized areas. Water-Rock Interaction, 1, 381-384. Gazzaz, N. M., Yusoff, M. K., Aris, A. Z., Juahir, H. and Ramli, M. F. (2012). Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors. Marine pollution bulletin, 64(11), 2409-2420. Ghaderian, S. M. and Ravandi, A. A. G. (2012). Accumulation of copper and other heavy metals by plants growing on Sarcheshmeh copper mining area, Iran. Journal of Geochemical Exploration, 123, 25-32. Giri, S. and Singh, A. K. (2014). Assessment of surface water quality using heavy metal pollution index in Subarnarekha River, India. Water Quality, Exposure and Health, 5(4), 173-182. Jahanshahi, R. and Zare, M. (2015). Assessment of heavy metals pollution in groundwater of Golgohar iron ore mine area, Iran. Environmental Earth Sciences, 74(1), 505-520. Kargar, M., Khorasani, N., Karami, M., Rafiee, G. and Naseh, R. (2012). Statistical source identification of major and trace elements in groundwater downward the tailings dam of Miduk Copper Complex, Kerman, Iran. Environmental monitoring and assessment, 184(10), 6173-6185. Keshavarzi, B., Moore, F. and Sharifi, R. (2013). Evaluation of dispersion and chemical partitioning patterns of heavy metals in the SarCheshmeh porphyry copper deposit: geochemical data from mine waste, water and stream sediments. International journal of environmental studies, 70(1), 73-93. Khorasanipour, M. and Eslami, A. (2014). Hydrogeochemistry and contamination of trace elements in Cu-porphyry mine tailings: a case study from the Sarcheshmeh mine, SE Iran. Mine Water and the Environment, 33(4), 335-352. Khorasanipour, M., Tangestani, M. H., Naseh, R. and Hajmohammadi, H. (2011). Hydrochemistry, mineralogy and chemical fractionation of mine and processing wastes associated with porphyry copper mines: a case study from the Sarcheshmeh mine, SE Iran. Applied Geochemistry, 26(5), 714-730. Liu, R. X., Kuang, J., Gong, Q. and Hou, X. L. (2003). Principal component regression analysis with SPSS. Computer methods and programs in biomedicine, 71(2), 141-147. Mahato, M. K., Singh, G., Singh, P. K., Singh, A. K. and Tiwari, A. K. (2017). Assessment of mine water quality using heavy metal pollution index in a coal mining area of Damodar River Basin, India. Bulletin of environmental contamination and toxicology, 99(1), 54-61. Malakooti, S. J., Shahhosseini, M., Ardejani, F. D., Tonkaboni, S. Z. S. and Noaparast, M. (2015). Hydrochemical characterisation of water quality in the Sarcheshmeh copper complex, SE Iran. Environmental Earth Sciences, 74(4), 3171-3190. Marcovecchio, J. E., Botté, S. E. and Freije, R. H. (2007). Heavy metals, major metals, trace elements. Handbook of water analysis, 2, 275-311. Mehrabi, B., Mehrabani, S., Rafiei, B. and Yaghoubi, B. (2015). Assessment of metal contamination in groundwater and soils in the Ahangaran mining district, west of Iran. Environmental monitoring and assessment, 187(12), 727. Mishra, S., Kumar, A., Yadav, S. and Singhal, M. K. (2017). Assessment of heavy metal contamination in water of Kali river using principle component and cluster analysis, India. Sustainable Water Resources Management, 1-9. Mohammadpour, R., Shaharuddin, S., Zakaria, N. A., Ghani, A. A., Vakili, M. and Chan, N. W. (2016). Prediction of water quality index in free surface constructed wetlands. Environmental Earth Sciences, 75(2), 139. Mohammadpour, R., Shaharuddin, S., Chang, C. K., Zakaria, N. A., Ab Ghani, A. and Chan, N. W. (2015). Prediction of water quality index in constructed wetlands using support vector machine. Environmental Science and Pollution Research, 22(8), 6208-6219. Mohan, S. V., Nithila, P. and Reddy, S. J. (1996). Estimation of heavy metals in drinking water and development of heavy metal pollution index. Journal of Environmental Science and Health: Part A, 31(2), 283-289. Prasad, B. and Sangita, K. (2008). Heavy metal pollution index of ground water of an abandoned open cast mine filled with fly ash: a case study. Mine water and the Environment, 27(4), 265-267. Prasanna, M. V., Praveena, S. M., Chidambaram, S., Nagarajan, R. and Elayaraja, A. (2012). Evaluation of water quality pollution indices for heavy metal contamination monitoring: a case study from Curtin Lake, Miri City, East Malaysia. Environmental Earth Sciences, 67(7), 1987-2001. Rakotondrabe, F., Ngoupayou, J. R. N., Mfonka, Z., Rasolomanana, E. H., Abolo, A. J. N. and Ako, A. A. (2018). Water quality assessment in the Betare-Oya gold mining area (East-Cameroon): Multivariate Statistical Analysis approach. Science of the Total Environment, 610, 831-844. Rezaei, A., Hassani, H., Hayati, M., Jabbari, N. and Barzegar, R. (2017). Risk assessment and ranking of heavy metals concentration in Iran’s Rayen groundwater basin using linear assignment method. Stochastic Environmental Research and Risk Assessment, 1-20. Riahi, H. and Seifi, A. (2016). Spatial group analysis and fuzzy spatial analysis of Shahr-e-Babak plain groundwater quality for drinking and irrigation. Iranian Water Resources Research, 12(2), 152-157 (In Farsi). Riahi, H. and Seifi, A. (2017). Qualitative zoning of Shahr-e-Babak aquifer based on its corrosiveness, sedimentation, and applicability for agricultural, drinking, and pressure irrigation uses. Water and Wastewater, 28(5), 92-105 (In Farsi). Sahu, M., Mahapatra, S. S., Sahu, H. B. and Patel, R. K. (2011). Prediction of water quality index using neuro fuzzy inference system. Water Quality, Exposure and Health, 3(3-4), 175-191. Salehi, H., ZaneiWand, H. and Ahmadi, S. (2017). Groundwater quality assessment and selecting the most appropriate interpolation method using GIS (Case study: Saghez city, Iran). Wetland Ecobiology, 9 (2), 5-18 (In Farsi). Seifi, A., Mirlatifi, S.M. and Riahi, H. (2011). Developing a Combined Model of Multiple Linear Regression-Principal Componenet and Factor Analysis (MLR-PCA) for Estimation of Reference Evapotranspiration (Case Study: Kerman Station). Water and Soil, 24(6): 1186-1196 (In Farsi). Senapaty, A. and Behera, P. (2012).Concentration and distribution of trace elements in different coal seams of the Talcher Coalfield, Odisha. Earth Science Engineering, 5(05), 80-87. Sharifinia, M., Mahmoudifard, A., Namin, J. I., Ramezanpour, Z. and Yap, C. K. (2016). Pollution evaluation in the Shahrood River: Do physico-chemical and macroinvertebrate-based indices indicate same responses to anthropogenic activities. Chemosphere, 159, 584-594. Shyu, G. S., Cheng, B. Y., Chiang, C. T., Yao, P. H. and Chang, T. K. (2011). Applying factor analysis combined with kriging and information entropy theory for mapping and evaluating the stability of groundwater quality variation in Taiwan. Environmental Research and Public Health, 8(4), 1084-1109. Simeonov, V., Stratis, J. A., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A. and Kouimtzis, T. (2003). Assessment of the surface water quality in Northern Greece.Water research, 37(17), 4119-4124. Sobhanardakani, S., Taghavi, L., Shahmoradi, B, and Jahangard, A. (2016). Groundwater quality assessment using the water quality pollution indices in Toyserkan Plain. Environmental Health Engineering and Management, 4(1), 21-27. Sobhanardakani, S. (2016). Evaluation of the water quality pollution indices for groundwater resources of Ghahavand plain, Hamadan province, western Iran. Iranian Journal of Toxicology, 10(3), 35-40. Tahri, M., Benyaich, F., Bounakhla, M., Bilal, E., Gruffat, J. J., Moutte, J. and Garcia, D. (2005). Multivariate analysis of heavy metal contents in soils, sediments and water in the region of Meknes (central Morocco). Environmental Monitoring and Assessment, 102(1-3), 405-417. Tiwari, A. K., Singh, P. K., Singh, A. K. and De Maio, M. (2016). Estimation of heavy metal contamination in groundwater and development of a heavy metal pollution index by using GIS technique. Bulletin of Environmental Contamination and Toxicology, 96(4), 508-515. Upadhyay, A. K., Gupta, K. K., Sircar, J. K., Deb, M. K. and Mundhara, G. L. (2006). Heavy metals in freshly deposited sediments of the river Subernarekha, India: an example of lithogenic and anthropogenic effects. Environmental Geology, 50(3), 397-403. World Health Organization (WHO). (2011) Guidelines for drinking water quality (4th ed.). ISBN 9241546387 Zabowski, D., Henry, C. L., Zheng, Z. and Zhang, X. (2001). Mining impacts on trace metal content of water, soil, and stream sediments in the Hei River basin, China. Water, Air, and Soil Pollution, 131(1-4), 261-273. | ||
|
آمار تعداد مشاهده مقاله: 976 تعداد دریافت فایل اصل مقاله: 874 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب