آنالیز شاخص‌های ارزیابی فلزهای سنگین آب سواحل جنوبی دریای خزر(پایش سال 1400)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی محیط‌زیست، پژوهشکده محیط‌زیست، جهاد دانشگاهی، رشت، ایران

2 مرکز ملی مطالعات و تحقیقات دریای خزر، موسسه تحقیقات آب، تهران، ایران

چکیده

دریای خزر به‌عنوان بزرگ‌ترین دریاچه‌ جهان، از جنبه‌های مختلف اقتصادی، اجتماعی، گردشگری و محیط زیستی دارای اهمیت بسیار است. در همین راستا، پایش کیفیت آب سواحل جنوبی دریای خزر به منظور بررسی آن بر طبق استانداردهای ملی و بین المللی و کنترل آلودگی‌های احتمالی نوار ساحلی ایران از اهمیت ویژه‌ای برخوردار است. بنابراین، کیفیت آب از نظر مقدار فلزهای سنگین توسط مرکز ملی مطالعات و تحقیقات دریای خزر با استقرار 14 ایستگاه در نوار ساحلی از میانکاله تا آستارا مطالعه گردید. در این مطالعه غلظت عنصرهای فلزی و غیر فلزی سنگین و خطرناک در عمق‌های یک و هفت متر از ایستگاه فرح‌آباد تا لیسار و در دو عمق یک و چهار متر در ایستگاه‌های میانکاله و آستارا با روش  ICP-MSاندازه‌گیری و شاخص‌های ارزیابی فلزات سنگین، شاخص درجه آلودگی، شاخص آلودگی فلزات سنگین و ضریب همبستگی اسپیرمن نیز بر طبق داده‌های غلظت محاسبه شد. نتایج بدست آمده نشان می‌دهد که میانگین غلظت فلزات سنگین و خطرناک (ppm 37/2),B (ppb 9/24)Ba و (ppb 3/18)Zn در عمق یک متر و (ppm 44/2),B (ppb 5/26)Zn و (ppb 5/17)As در عمق هفت متر بیشترین غلظت ثبت شده در ایستگاه‌های پایش می‌باشند. با توجه به داده‌ها، بیشترین مقدار شاخص ارزیابی (58/1)، شاخص درجه آلودگی(96/5-) و شاخص آلودگی (49/68) فلزات سنگین به ترتیب در عمق‌های هفت متر ایستگاه فرح‌آباد، عمق یک متر ایستگاه فریدونکنار و عمق یک متر ایستگاه میانکاله بدست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Analysis of heavy metal indexes in the water of the southern shores of the Caspian Sea (monitoring year 1400)

نویسندگان [English]

  • seyyed javad mousavi 1
  • Seyede Masoume Banihashemi 2
1 Department of Environmental Engineering, Environmental Research Institute, Jihade Daneshgahi, Rasht, Iran.
2 Caspian Sea National Research Center, Water Research Institute, Tehran, Iran
چکیده [English]

 
The Caspian Sea as the largest lake in the world is very important from the different aspects of economic, social, tourist, and environmental. In this regard, monitoring the water quality of the southern shores of the Caspian Sea has a special importance in order to study it according to national and international standards and control the possible pollution of the coastal strip of Iran. Therefore, the National Research Center of Caspian Sea was analyzed and checked the quality of water in terms of amount heavy metal by establishing 14 stations in the coastal strip from Miankala to Astara. In this study, the concentration of heavy and dangerous metallic and non-metallic elements in depth 1 and 7 meters from Farah Abad station to Lisar and at two depths of 1 and 4 meters in Miankala and Astara stations were measured by ICP-MS method and heavy metal evaluation index, pollution degree index, heavy metal pollution index and Spearman's correlation coefficient were calculated according to the concentration data. The obtained results show that the average concentration of heavy and dangerous metals B(2.37ppm), Ba(24.9ppb) and Zn(18.3ppb) at a depth of one meter and B(2.44ppm), Zn(26.5ppb) and As(17.5ppb) at a depth of seven meters are the highest concentrations recorded in the monitoring stations. According to the data, the highest value of the HEI(1.58), the Cd(-5.96) and  the HPI(68.49) of heavy metals were obtained at depth of seven meters in Farah-Abad station and one meter Faridoonkanar and Miankale station, respectively.

کلیدواژه‌ها [English]

  • "Caspian Sea"
  • "heavy metals"
  • "pollution degree index"
  • "evaluation index"
  • "correlation coefficient"

Analysis of heavy metal indexes in the water of the southern shores of the Caspian Sea (monitoring year 1400)

EXTENDED ABSTRACT

Introduction:

Coastal areas are considered as important and sensitive regions due to their abundant water resources, unique ecological and biological resources, economic activities, social interactions, and tourism. However, due to population growth and improper exploitation, significant environmental damages have been inflicted upon these areas. One of the most pressing global issues is environmental pollution by heavy and hazardous metals. Heavy metals are considered persistent and enduring pollutants in the environment, as they accumulate in food chains or organisms and have various adverse effects. Assessing different indexes of water pollution is a simple and practical method to examine water quality, analyze its qualitative changes, and identify sensitive areas. Evaluation indexes for heavy metals, such as the Heavy Metal Evaluation Index (HEI), Heavy Metal Pollution Index (HPI), and Contamination degree (Cd), are utilized in various studies for classifying water pollution in terms of heavy metals.

The Caspian Sea, as the largest enclosed water body on Earth, possesses unique natural conditions and plays a significant geopolitical role in the region. Therefore, due to the importance of coastal protection, water resource management, pollutant control, and the examination of environmental changes and their causes, this article presents the results of the analysis of heavy metal and toxic parameters in the water of the Caspian Sea during the monitoring of the year 1400. Additionally, the results were analyzed using statistical methods and calculated various indexes for heavy metals at the sampling stations.

Method:

The sampling in this monitoring was conducted using a water sampling device at depths of one meter and seven meters. However, in the Astara and Miankaleh stations, due to coastal conditions, sampling was carried out at depths of one meter and four meters. The sampling stations from east to west in the Caspian Sea are: Miankaleh, Farahabad, Larim, Fereydunkenar, Mahmudabad, Sisangan, Namakabroud, Tonekabon, Ramsar, Dastak, Bandar-e Anzali, Rezvanshahr, Lisar, and Astara. For sampling at each station, the sampling container was rinsed with water from the same location, and then 1000 milliliters of water were collected from an approximate depth of 35 centimeters. The samples were sent to the laboratories in cooling chambers on the same day, according to the relevant standards.

In this monitoring, the concentrations of heavy elements such as molybdenum (Mo), mercury (Hg), copper (Cu), selenium (Se), bromine (Br), strontium (Sr), silicon (Si), arsenic (As), boron (B), aluminum (Al), barium (Ba), uranium (U), rubidium (Rb), lead (Pb), nickel (Ni), zinc (Zn), cobalt (Co), cadmium (Cd), and chromium (Cr) were measured using the inductively coupled plasma method, and their composition was determined by mass spectrometry, following the standard method number 3125. This monitoring was carried out in Mehr 1400, with three replicates for each station's sampling, and the average of the results was reported.

Conclusions:

In this study, the concentrations of various heavy and hazardous metals were assessed, and some of them, such as arsenic, boron, nickel, and copper, were found to exceed the standard limits in the Caspian Sea. Furthermore, based on the obtained concentrations at a depth of one meter, the Heavy Metal Evaluation Index (HEI) indicated that the Astara station (53.1) had the highest value, indicating a moderate impact of heavy metals, while Tonekabon had the lowest value (0.46), indicating relatively clean water in terms of heavy metals. In addition, the pollution degree index value (Cd) of all stations is less than one, so they are in the category of low pollution.In this project, based on the performed statistical analysis, at a depth of one meter, significant correlations were found at a 95% confidence level between copper and lead, the Heavy Metal Evaluation Index and the Heavy Metal Pollution Index, molybdenum and barium, aluminum and lead, nickel and the Heavy Metal Evaluation Index. The positive and negative coefficients in the correlation relationships indicate a direct and inverse relationship between these parameters, respectively.  At a depth of seven meters, significant correlations were found at a 99% confidence level between copper and molybdenum, nickel and lead. Moreover, a significant correlation at a 95% confidence level was observed between nickel and copper, and also between molybdenum and selenium

Aazami J, Moradpour H, KianiMehr N. (2017). A review of biotic indices for heavy metals in polluted environment. Human & Environment, 15(1), 13-24. (In Persian)
Abadi M, Zamani A, Parizangane A, Khosravi Y, Badiee H. (2018). Spatial distribution of heavy metals (Zn, Cu, Pb, Co, Ni and Cd) in water and algae Spirogyra sp. in the southern Iranian coasts of the Caspian Sea. Marine Biology,10(3), 39-52. (In Persian)
Ameh E, Akpah F. (2011). Heavy metal pollution indexing and multivariate statistical evaluation of hydrogeochemistry of River PovPov in Itakpe Iron-Ore mining area, Kogi State, Nigeria. Advances in applied science research, 2(1), 33-46.
Appiah Opong R, Ofori A, Ofosuhene M, Ofori-Attah E, Nunoo FK, Tuffour I, et al. (2021). Heavy metals concentration and pollution index (HPI) in drinking water along the southwest coast of Ghana. Applied Water Science, 11(3), 1-10. https://doi.org/10.1007/s13201-021-01386-5.
Asgharai Moghaddam A, Nadiri AA, Sadeghi Aghdam F. (2020). Investigation of hydrogeochemical characteristics of groundwater of Naqadeh plain aquifer and heavy metal pollution index (HPI). Scientific Quarterly Journal of Geosciences, 29(115), 97-110. https://doi.org/10.22071/gsj.2018.127310.1464. (In Persian)
Atangana E, Oberholster PJ. (2021). Using heavy metal pollution indices to assess water quality of surface and groundwater on catchment levels in South Africa. Journal of African Earth Sciences, 182,104254. https://doi.org/10.1016/j.jafrearsci.2021.104254.
Bagheri H, Bostami KD. (2022). Investigation of Heavy Metal Concentrations in Estuarine Sediments of Important Rivers in The Southern Part of The Caspian Sea. Environment and Water Engineering, 8(1), 31-46. https://doi.org/10.22034/JEWE.2021.286828.1569. (In Persian).
Behnam H, Farrokhian Firouzi A. (2022). Application of linear and non-linear kinetic and isotherm models for evaluation of lead removal efficiency from aqueous solutions using biochars. Iranian Journal of Soil and Water Research, 53(2), 333-46. https://doi.org/10.22059/ijswr.2022.333585.669124. (In Persian).
Bhuyan MS, Bakar MA, Rashed-Un-Nabi M, Senapathi V, Chung SY, Islam MS. (2019).Monitoring and assessment of heavy metal contamination in surface water and sediment of the Old Brahmaputra River, Bangladesh. Applied Water Science, 9(5), 1-13. https://doi.org/10.1007/s13201-019-1004-y.
Celik A, Kartal AA, Akdoğan A, Kaska Y. (2005). Determining the heavy metal pollution in Denizli (Turkey) by using Robinio pseudo-acacia L. Environment international, 31(1), 105-12. https://doi.org/10.1016/j.envint.2004.07.004.
Chabukdhara M, Gupta SK, Kotecha Y, Nema AK. (2017). Groundwater quality in Ghaziabad district, Uttar Pradesh, India: multivariate and health risk assessment. Chemosphere, 179, 167-78. https://doi.org/10.1016/j.chemosphere.2017.03.086.
Ghobadi A, Cheraghi M, Sobhan Ardakani S, Lorestani B, Merrikhpour H. (2022). Heavy Metals Pollution Assessment in Groundwater Resources of Hamadan-Bahar Plain in 2018. Journal of Water and Soil Science, 26(1), 239-57. http://dx.doi.org/10.47176/jwss.26.1.43971. (In Persian)
Chou Y-M, Polansky AM, Mason RL. (1998). Transforming non-normal data to normality in statistical process control. Journal of Quality Technology, 30(2), 133-41 https://doi.org/10.1080/00224065.1998.11979832.
Hamzehpour A, Darvish Bastami K, Bagheri H, Azimi A, Einali A, Rahnama R. (2016). Survey of physicochemical properties and nutrients in surface waters of the southern Caspian Sea-Seasangan. Journal of Marine Science & Technology Research, 11(1), 41-52. (In Persian).
Hassanpour M, Pourkhabbaz A, Ghorbani R. (2011). The measurement of heavy metals in water, sediment and wild bird (common coot) in Southeast Caspian Sea, Journal of Mazandaran University of Medical Sciences, 20(1), 184-94. (In Persian).
Herrera-Silveira JA, Morales-Ojeda SM. (2009). Evaluation of the health status of a coastal ecosystem in southeast Mexico: Assessment of water quality, phytoplankton and submerged aquatic vegetation. Marine Pollution Bulletin, 59(1-3), 72-86. https://doi.org/10.1016/j.marpolbul.2008.11.017.
Iran IoSaIRo. Drinking water -Physical and chemical specifications(5th.revision). (2010). Iran: Institute of Standards and Industrial Research of Iran. (In Persian).
Khalili R, Montaseri H, Motaghi H, Jalili MB. (2021). Water quality assessment of the Talar River in Mazandaran Province based on a combination of water quality indicators and multivariate modeling. Water and Soil Management and Modelling, 1(4), 30-47. https://doi.org/10.22098/mmws.2021.9322.1033. (In Persian).
Kone K, Rodrigue KA, Kouassi KE, Adouby K. (2019). Heavy metal pollution index of surface water and groundwater around Tongon Mine (Côte d'Ivoire). International Journal of Environmental Monitoring and Analysis, 7(5), 103-11. https://doi.org/10.11648/j.ijema.20190705.12.
Li M, Zhang Z, Li R, Wang JJ, Ali A. (2016). Removal of Pb (II) and Cd (II) ions from aqueous solution by thiosemicarbazide modified chitosan. International journal of biological macromolecules. 86, 876-84. https://doi.org/10.1016/j.ijbiomac.2016.02.027.
Mahmoudi N, Ahmadi M, Babanezhad M. Seifabadi J, Roohi A. (2013). Spatial characteristics assessment of water quality and identify its controlling factors along Mazandaran coastsduring summer (multivariate approach). Fisheries Science and Technology, 2(2), 47-61. http://dorl.net/dor/20.1001.1.23225513.1392.2.2.6.2. (In Persian).
Mahmud HNME, Huq AO, binti Yahya R. (2016). The removal of heavy metal ions from wastewater/aqueous solution using polypyrrole-based adsorbents: a review. Rsc Advances, 6(18), 14778-91. https://doi.org/10.1039/C5RA24358K.
Majhi A, Biswal SK. (2016). Application of HPI (heavy metal pollution index) and correlation coefficient for the assessment of ground water quality near ash ponds of thermal power plants. International Journal of Science Engineering and Advance Technology, 4(8), 395-405.
Marcovecchio JE, Botté SE. (2007). Heavy metals, major metals, trace elements.  Handbook of water analysis, CRC Press, 289-326.
Mishra S, Kumar A, Yadav S, Singhal MK. (2018). Assessment of heavy metal contamination in water of Kali River using principle component and cluster analysis, India. Sustainable Water Resources Management, 4, 573-81. https://doi.org/10.1007/s40899-017-0141-4.
Mohan SV, Nithila P, Reddy SJ. (1996). Estimation of heavy metals in drinking water and development of heavy metal pollution index. Journal of Environmental Science & Health Part A, 31(2), 283-9. https://doi.org/10.1080/10934529609376357.
Mousavi SJ, Parvini M, Ghorbani M. (2018). Adsorption of heavy metals (Cu2+ and Zn2+) on novel bifunctional ordered mesoporous silica: Optimization by response surface methodology. Journal of the Taiwan Institute of Chemical Engineers, 84, 123-41. https://doi.org/10.1016/j.jtice.2018.01.010.
Mousavi SJ, Parvini M, Ghorbani M. (2018). Experimental design data for the zinc ions adsorption based on mesoporous modified chitosan using central composite design method. Carbohydrate polymers, 188, 197-212. https://doi.org/10.1016/j.carbpol.2018.01.105.
Nasrollahzadeh Saravi H, Najafpour S, Rezaei M, Solaimaniroudi A. (2014). Temporal and spatial ofheavy metals concentrations (Zn, Cu, Ni, Pb, Cd and Hg) in Iraniancoastalwaters of the Southern Caspian Sea. Marine Biology, 6(1), 1-12. (In Persian)
Nguyen TTH, Zhang W, Li Z, Li J, Ge C, Liu J, et al. (2016). Assessment of heavy metal pollution in Red River surface sediments, Vietnam. Marine pollution bulletin, 113(1-2), 513-9. https://doi.org/10.1016/j.marpolbul.2016.08.030.
Nzeve JK, Njuguna SG, Kitur EC. (2015). Assessment of heavy metal contamination in surface water of Masinga Reservoir, Kenya. Journal of Natural Sciences Research, 5(2), 101-108.
Ojekunle OZ, Ojekunle OV, Adeyemi AA, Taiwo AG, Sangowusi OR, Taiwo AM, et al. (2016). Evaluation of surface water quality indices and ecological risk assessment for heavy metals in scrap yard neighbourhood. SpringerPlus, 5(1), 1-16. https://doi.org/10.1186/s40064-016-2158-9.
Organization EP. (2015). Iranian water quality standard. Environmental Protection Organization. (In Persian)
Panigrahy BP, Singh PK, Tiwari AK, Kumar B, Kumar A. (2015). Assessment of heavy metal pollution index for groundwater around Jharia coalfield region, India. Journal of Biodiversity and Environmental Sciences, 6(3), 33-9.
Prasad B, Bose J. (2001). Evaluation of the heavy metal pollution index for surface and spring water near a limestone mining area of the lower Himalayas. Environmental geology, 41(1-2), 183-8. https://doi.org/10.1007/s002540100380.
Prasanna M, Praveena S, Chidambaram S, Nagarajan R, 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. https://doi.org/10.1007/s12665-012-1639-6.
Qishlaqi A, Moore F, Forghani G. (2009). Characterization of metal pollution in soils under two landuse patterns in the Angouran region, NW Iran; a study based on multivariate data analysis. Journal of Hazardous Materials, 172(1), 374-84. https://doi.org/10.1016/j.jhazmat.2009.07.024.
Qu L, Huang H, Xia F, Liu Y, Dahlgren RA, Zhang M, et al. (2018). Risk analysis of heavy metal concentration in surface waters across the rural-urban interface of the Wen-Rui Tang River, China. Environmental pollution, 237, 639-49. https://doi.org/10.1016/j.envpol.2018.02.020.
Seifi A, Riahi H. (2019). Evaluation of heavy metal pollution indices for surface water of the Sarcheshmeh copper mine using multivariate statistical methods and GIS. Iranian Journal of Soil and Water Research, 50(1), 161-76. https://doi.org/10.22059/ijswr.2018.254261.667869. (In Persian).
Shirodkar P, Mesquita A, Pradhan U, Verlekar X, Babu M, Vethamony P. (2009). Factors controlling physico-chemical characteristics in the coastal waters off Mangalore—a multivariate approach. Environmental Research, 109(3), 245-57. https://doi.org/10.1016/j.envres.2008.11.011.
Shyu G-S, Cheng B-Y, Chiang C-T, Yao P-H, 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. International journal of environmental research and public health, 8(4), 1084-109. https://doi.org/10.3390/ijerph8041084.
Singh PK, Tiwari A, Panigarhy B, Mahato M. (2013). Water quality indices used for water resources vulnerability assessment using GIS technique: a review. Int J Earth Sci Eng, 6(6-1), 1594-600.
Sinka Karimi MH, Pourkhabbaz AR, Hassanpour M. (2015). Study of using water and waterfowl organs for evaluation of metal pollution (case study: Miankaleh and Gomishan international wetlands). Wetland Ecobiology, 7(23), 15-28. (In Persian).
Sobhan Ardakani 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. http://dx.doi.org/10.29252/arakmu.10.3.35.
Sobhan Ardakani S, Taghavi L, Shahmoradi B, Jahangard A. (2017). Groundwater quality assessment using the water quality pollution indices in Toyserkan Plain. Environmental Health Engineering and Management Journal, 4(1), 21-7. http://dx.doi.org/ 10.15171/EHEM.2017.04
Sobhan Ardakani S, Yari AR, Taghavi L, Tayebi L. (2016). Water quality pollution indices to assess the heavy metal contamination, case study: groundwater resources of Asadabad Plain in 2012. Archives of Hygiene Sciences, 5(4), 221-8. http://dorl.net/dor/20.1001.1.22519203.2016.5.4.3.8.
Tiwari MK, Bajpai S, Dewangan U, Tamrakar RK. (2015). Assessment of heavy metal concentrations in surface water sources in an industrial region of central India. Karbala International Journal of Modern Science, 1(1),9-14. https://doi.org/10.1016/j.kijoms.2015.08.001.
Zaker NH, Ghaffari P, Jamshidi S. (2007). Physical study of the southern coastal waters of the Caspian Sea, off Babolsar, Mazandaran in Iran. Journal of Coastal Research, 564-9. https://www.jstor.org/stable/26481651.
Zhou Q, Yang N, Li Y, Ren B, Ding X, Bian H, et al. (2020). Total concentrations and sources of heavy metal pollution in global river and lake water bodies from 1972 to 2017. Global Ecology and Conservation, 22, e00925. https://doi.org/10.1016/j.gecco.2020.e00925.