|تعداد مشاهده مقاله||111,502,699|
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بررسی غلظت و منشأ آلایندههای فلزی در رسوبات خور موسی، خلیجفارس
|مقاله 8، دوره 40، شماره 2، تیر 1393، صفحه 345-360 اصل مقاله (1.21 M)|
|نوع مقاله: مقاله پژوهشی|
|شناسه دیجیتال (DOI): 10.22059/jes.2014.51204|
|علیرضا واعظی1؛ عبدالرضا کرباسی* 2؛ مجتبی فخرایی3؛ علیرضا ولی خانی سامانی4؛ مهدی حیدری3|
|1دانشجوی دکتری مهندسی محیطزیست- منابع آب دانشکدۀ تحصیلات تکمیلی محیطزیست دانشگاه تهران|
|2دانشیار مهندسی محیطزیست دانشکدۀ تحصیلات تکمیلی محیطزیست دانشگاه تهران|
|3کارشناس ارشد مهندسی محیطزیست- منابع آب دانشکدۀ تحصیلات تکمیلی محیطزیست دانشگاه تهران|
|4کارشناس ارشد مهندسی محیطزیست – منابع آب دانشکده تحصیلات تکمیلی محیط زیست دانشگاه تهران|
|خور ماهشهر در 65 کیلومتری مدخل ورودی خور موسی واقع در خلیجفارس قرار دارد. به واسطۀ حساسیت خلیجفارس و تأثیرات منفی و مخربی که این منطقه بهدلیل وجود صنایع پتروشیمی واقع در منطقۀ ویژۀ اقتصادی ماهشهر متحمل میشود، مطالعۀ حاضر در تیرماه 1391 در خور ماهشهر واقع در شمالغرب خلیجفارس صورت گرفت. 16 نمونۀ سطحی رسوب به وسیلۀ نمونهگیر پترسون جمعآوری شد. غلظت و منشأ آلایندههای فلزی (Zn، Sr، Ni، Mn، Cu، Cr، Co، Ba، As و Al) در رسوبات از طریق ICP-AES تعیین شد. هدف اصلی از انجام این تحقیق پایش زیستمحیطی فلزات در رسوبات خور ماهشهر به منظور ارتقای کیفیت محیطزیست منطقه است. در همین راستا کمّیسازی شدت آلودگی در رسوبات با استفاده از شاخصهای EF، Igeo، IPOLL و m–ERM–Q صورت گرفت. از دیگر اهداف این مطالعه جداکردن بخش انسانساخت از طبیعی و مشخصکردن منشأ عناصر است. در این تحقیق از روش آزمایشگاهی تفکیک شیمیایی یکمرحلهای استفاده شده است. نتایج بهدستآمده حاکی از آن است که شاخص تجمع زیستی (Igeo) در حالت کلی بیانگر آلودگی کمی است با این حال فاکتور تجمع (EF) و شاخص آلودگی (Ipoll) برای فلزات آلودگی به نسبت بالایی را نمایش میدهد. میانگین مقادیر EF برای هر یک از فلزات بین محدودۀ تجمع کم تا بسیار زیاد قرار دارد. بر اساس شاخص m–ERM–Q همۀ نمونههای رسوبی 30 درصد احتمال سمیت دارند. نتایج آنالیز خوشهای بیانگر این بود که Cr در نمونههای رسوب دارای منشأ نفتی است.|
|آلودگی رسوبات؛ آنالیز خوشهای؛ تفکیک شیمیایی؛ خلیجفارس؛ فلزات سنگین|
|عنوان مقاله [English]|
|Assessment of Sources and Concentration of Metal Contaminants in Marine Sediments of Musa Estuary, Persian Gulf|
|Alireza Vaezi1؛ Abdolreza Karbassi2؛ Mojtaba Fakhraee3؛ Alireza Valikhani Samani4؛ Mehdi Heidari3|
|1PhD Candidate, Environmental Engineering, Graduate Faculty of Environment, University of Tehran, Tehran, Iran|
|2PhD, Associate Professor, Environmental Engineering, Graduate Faculty of Environment, University of Tehran, Tehran, Iran|
|3MSc Student of Environmental Engineering, Graduate Faculty of Environment, University of Tehran, Tehran, Iran|
|4MSc Student, Environmental Engineering, Graduate Faculty of Environment, University of Tehran, Tehran, Iran|
We can obtain useful information about aquatic systems by studying heavy metals in surface sediments. Marine sediments can bring out the aquatic contamination. Due to heavy metal toxicity, hard biodegradation and easy bioaccumulation in aquatic ecosystems, various indices have been developed such as sediment quality guidelines (SQGs), enrichment factor (EF), pollution load index (IPOLL) and index of geo-accumulation (Igeo). Sediment-bound heavy metals may be desorbed from surface sediment and accumulated on fine grained particles which finally move into the depositional. Grain size is an important factor to evaluate heavy metals concentration in the sediment. The recommended size for particles is <63 µm for analysis of sediment contamination. Persian Gulf is a part of Indian Ocean, situated in Southwestern Asia, between longitudes 48°- 56° E and latitudes 24° - 30° N. It is a semi open sea with the area about 40000 m2 and there are about 400-450 types of fishes. The aim of this study was to determine sediment contaminations and ecological risk assessments in the Musa Estuary. The study area is located in the Northwest of the Persian Gulf and is surrounded by ports, harbors, and large petrochemical industry plants.
Materials and methods
Surface sediment samples were collected in July 2012 from 16 sites in Musa Estuary. Samples were collected using a Zinc-plated Peterson grab. A Teflon spatula was used to extract the sediment samples from the center of grab. After collecting surface sediment samples, they were immediately packed in air-tight pre-labeled polyethylene bags and preserved at 4°C for metal analysis. Grain size fractions less than 63 μm were separated for geochemical analysis. All the sediment samples were gently air-dried at 50°C and then sieved. The sediments were weighted and placed into a Teflon beaker and were digested using 7 mL of aqua-regia (1: 3HCl: HNO3). The mixture was heated at 95°C for 1 hour, and refluxed for 5-10 min until the brown fumes were no longer visible. After cooling, 5 mL of hydrogen fluoride (HF) were added. Then, the samples refluxed to room temperature. Sediment samples were filtered by Whatman 0.45 μm membrane and brought to 50 mL volume using 1N HCl. The concentration of elements (Al, As, Ba, Co, Cr, Cu, Mn, Ni, Sr and Zn) in sediment samples were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES). Organic matters were measured by recording the Loss on Ignition (LOI) through heating the samples for 4 hours at 450°C in a muffle furnace. Finally, the origination of metals was investigated. In this study, we used single step chemical extraction. About 2 gr of each sediment sample was placed into a Meyer flask, and mixed with 15 mL of 1N HCl. Sample bottles were shaken for 30 minutes by a shaker. Then, they were filtered by Whatman 0.45 μm membrane and brought to 50 mL volume using 1N HCl. Concentration of metals of Al, As, Ba, Co, Cr, Cu, Mn, Ni, Sr, and Zn in sediment samples were determined by ICP-AES. In accordance to the quality assurance program, procedural blanks, duplicates and MESS-1, standard sediment samples were run alongside the other sediment samples. The accuracy of analysis was about ±4% for all elements. Pollution assessment and evaluation were carried out using several techniques including Enrichment factor (EF), Geo-accumulation index (Igeo), Pollution index (IPOLL), and Effective range median (ERM).
Results and discussion
Table 1. Elemental concentration and organic contents (LOI) of surface sediments in Musa Estuary
According to table 1, there is a significant difference between mean concentration of Al and the correspondent mean crust. The organic contents range from minimum 2.83 to maximum 6.54% with a mean value of 4.49%. The results revealed that the concentration of As is between 6.3 and 2.6 mg/kg with the mean value of 10.5 mg/kg. The maximum concentration of As was found at the station 13. Cu ranges from 14 to 58 mg/kg with a mean value of 22 mg/kg. The maximum, minimum, and mean concentrations of Co are 6.1, 1.3 and 3 mg/kg, respectively. EF is a useful index to differentiate between anthropogenic influences and those from natural procedures. The EF of all elements can be calculated using the following equation.
Where, Mc is the concentration of metals, Mr is the concentration of reference elements, s is the studied sample, and b indicates the background. The obtained mean EF values for various metals were between the minimal enrichment and extremely high enrichment. The maximum mean EF value belongs to As (As=42.6) indicating extremely high enrichment, and also the minimum mean EF value is seen for Co (Co=1.2) showing minimal enrichment. In order to determine the degree of contamination in each sediment sample, Igeo index values are calculated using the following equation:
Where, Cn is the content of metals in sediment samples, and Bn is the geochemical background concentration for each element. Muller’s formula was modified as follows:
Where, Bn and Lp represent bulk concentration and lithogenous portion, respectively. The Igeo index and the Pollution index have seven classes. The results show the limitation of Igeo index in the assessment of pollution. A considerable amount of Cu and Cr were found in the lithogenous portion. The results of Chemical partitioning studies have revealed the arrangement of natural portions for the metals as follows: Cu(96%) > Cr(43%) > Co(34%) > Sr(33%) > Ni(31%) > Mn(24%) > Zn(19%). The values obtained from Ipoll index are indicative of a broad range (from no pollution to strong pollution) for various studied elements. Cluster analysis (CA) is a statistical method which identifies the group of samples that behave similarly or show a significant relationship between different clusters.
Figure 1. Dendrogram showing clustering of metals and LOI
Based on dendrogram, three distinct clusters are identifiable: (A) LOI-Cu, (B) Co-Zn-Al-Cr-Ni, and (C) As-Ba-Mn-Sr. The cluster analysis revealed that Ni joined to Cr by high similarity coefficient which indicates that Cr could be originated from oil sources. Dendrogram also shows that a part of Cr and Ni are derived from lithogenous source as they are linked to Al. Pearson coefficient amongst Zn, Al, and Ni shows that Zn is probably originated from both lithogenous and oil sources. Sr and Mn joined together with a relatively high coefficient that is indicative of a common source. Since LOI is linked with the other clusters at an insignificant level, it can be inferred that the organic contents do not play a major role in elemental concentrations. In order to consider the possible additive toxicity effects of the combined toxicant groups in different concentration, mean SQG quotients were calculated as follows:
Where, Ci is the sediment concentration of compound i, ERMi is the respective Effect Range Median for compound i and n is the number of compound i. Based on the classification of metals contamination, all sediment samples can be categorized as medium-low priority sites with 30% probability of toxicity.
The mean enrichment factor values for various metals were between minimal and extremely high enrichment. The maximum mean EF value was for As (As=42.6) showing the extremely high enrichment, and also the minimum mean EF value was for Co (Co=1.2) indicating the minimal enrichment. The unpolluted Igeo designation is obviously not confirmed by the other methods for calculating the metal pollution impact in Musa Estuary. A considerable amount of Cu and Cr was found in lithogenous portion. The results of partitioning studies revealed that the arrangement of anthropogenic portions for the metals are as follows: Cu (96%) > Cr(43%) > Co(34%) > Sr(33%) > Ni(31%) > Mn(24%) > Zn(19%). The CA revealed that Ni joined to Cr by high similarity coefficients, which is indicative of oil origin for these two elements.
|chemical partitioning, Cluster Analysis, metal pollution, Persian Gulf sediment contamination|
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