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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 | ||
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