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بررسی خطر آلودگی فلزات سنگین در رسوبات معلق وخاک سطحی (مطالعه موردی: حوزه لانیز، کرج) | ||
تحقیقات آب و خاک ایران | ||
دوره 53، شماره 12، اسفند 1401، صفحه 2937-2954 اصل مقاله (2.57 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2023.351189.669395 | ||
نویسندگان | ||
مسلم برجی حسن گاویار1؛ علی اکبر نظری سامانی* 2؛ سادات فیضنیا2؛ حسن فتحآبادی3 | ||
1گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران، تهران، ایران | ||
2گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران. | ||
3گروه منابع طبیعی و کشاورزی، دانشکده منابع طبیعی، دانشگاه گنبد کاووس، گنبد کاووس، ایران. | ||
چکیده | ||
در این تحقیق محتوای فلزات سنگین (Zn، V، Ti، Pb، Ni، Mn، Cu، Cr و As) در 40 نمونه خاک و رسوب به همراه پنج نمونه رسوب معلق در آبراهههای حوزه لانیز کرج مورد بررسی قرار گرفت. با توجه به فعالیت عمرانی به ویژه احداث آزادراه تهران – شمال در این حوزه، شاخصهای آلودگی تک عنصره شامل Contamination Factor (CF)، شاخص زمین انباشتگی (Igeo) ، فاکتور غنی شدگی نرمال شده (EF) و فاکتور پتانسیل ریسک اکولوژیک تک عنصره (ER)؛ به همراه دو شاخص چند عنصر Pollution Load Index (PLI) و ریسک اکولوژیک (RI) استفاده شدند. همچنین از تحلیل مولفههای اصلی و آنالیز خوشهای برای گروه بندی عناصر و نمونهها استفاده شد. نتایج PCA نشان داد که دو گروه از عناصر با منشاء طبیعی و انسانی-طبیعی قابل تفکیک است. نتایج آنالیز خوشهای بیانگر تفکیک 50 درصد نمونههای مرتبط با آزادراه در دو خوشه مجزا میباشد. براساس شاخصهای CF، آلودگی شدید آرسنیک و سپس سرب و منگنز در نمونههای رسوب معلق و خاک مرتبط با آزادراه حاکم است. این آلودگی در شاخص Igeo برای آرسنیک نیز وجود دارد. همچنین براساس این شاخص اکثر نمونههای رسوب معلق مرتبط با آزادراه دارای کلاس شدید آلودگی از همه عناصر هستند. اما براساس شاخص غنی شدگی اصلاح شده با عنصر منگنز فقط یک نمونه متاثر و دو نمونه غیر متاثر از آزادراه دچار غنی شدگی شدید هستند و سایر نمونهها غنی شدگی کم یا متوسطی دارند. بر خلاف شاخصهای تک عنصره، در شاخصهای تجمعی PLI و RI نمونههای رسوب معلق و خاک مرتبط با آزادراه دارای بار آلودگی و ریسک اکولوژیک پایینی هستند. نتایج این تحقیق نشان داد که استفاده جداگانه از شاخصهای منفرد یا شاخصهای یکپارچه آلودگی نمیتواند واقعیت آن در حوزه را نشان دهد. | ||
کلیدواژهها | ||
فلزات سنگین؛ آلودگی؛ شاخص آلایندگی؛ ریسک اکولوژیک؛ آنالیز چند متغیره | ||
عنوان مقاله [English] | ||
Investigating the Risk of Heavy Metal Contamination in Suspended Sediments and Surface Soil of Laniz Watershed, Karaj | ||
نویسندگان [English] | ||
Moslem Borji Hassangavyar1؛ Ali Akbar Nazari Samani2؛ Sadat Feiznia2؛ Abolhasan Fathabadi3 | ||
1Department of Arid and Mountainous Reclamation Regions, Faculty of Natural Resources, University of Tehran, Iran | ||
2Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran. | ||
3Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Gonbad-e Kavus, Gonbad-e Kavus, Iran. | ||
چکیده [English] | ||
Water and soil play an important role in all human environmental activities and controling physical, chemical and biological processes in the environment. The existence of limitations of water resources, especially the fresh water of rivers and dams, makes it necessary to pay more attention to them against pollution. Contamination of water and soil with heavy metals are serious environmental pollutants that enter the environment in many different ways with natural and human origin and cause serious damage. Karaj Dam is one of the most vital sources of drinking water supply in the metropolis of Tehran, which faces a serious risk of pollution due to the development of human activities. This study investigated the concentrations of heavy metals (Zn, V, Ti, Pb, Ni, Mn, Cu, Cr, and As) in 40 soil samples and sediments, as well as five suspended sediment samples, in the river of the Laniz watershed in Karaj, Iran. Due to the construction activities in the watershed including the construction of the Tehran-North Freeway, the natural condition has been affected over the past decade and therefore need to use and new inventory method to separate the effects of natural geochemical from humane effects. The single-element indices of contamination factor (CF), geoaccumulation index (Igeo), normalized enrichment factor (EF), and ecological risk potential factor (ER), as well as two multi-element indices of pollution load index (PLI) and ecological risk index (RI), were employed. At first the elements and samples were grouped by principal component analysis (PCA) and cluster analysis. FA distinguished two groups of elements; called natural and human-natural origins. The cluster analysis divided 50% of the freeway-affected samples into two distinct clusters. Based on the CF index, the As contamination was extreme in the suspended sediment samples and soil samples related to the Freeway while the Pb and Mn carried out the next rank. Also, the single Igeo index revealed the high As contamination. Moreover, based on the Igeo, most suspended sediment samples related to the Freeway put in the extreme contamination class for all of the elements. However, the Mn-modified enrichment factor showed only one freeway-affected and two freeway-unaffected samples exhibited extreme enrichment, and the enrichment of other samples was low or moderate. Unlike the single-element indices, PLI and RI showed that the suspended sediment and soil samples related to the freeway had low pollution load and ecological risk. Compare of single and multiple contamination indices revealed an inconsistency of pollution risk that can be addressed into the background value (in single indices) and the toxicity response factor of the metals (in multiple indices). Results indicated that due to spatial-temporal changes of human effects, it would be better to use different values for both background and elements toxicity response. Therefore, to reach a reality image of contamination risk, more researches are needed to elucidate the mentioned standard value based on the regional variations. | ||
کلیدواژهها [English] | ||
contamination index, ecological risk, metals and metalloids, multivariate analysis | ||
مراجع | ||
Ayyanar, A., & Thatikonda, S. (2021). Enhanced Electrokinetic Removal of Heavy Metals from a Contaminated Lake Sediment for Ecological Risk Reduction. Soil and Sediment Contamination: An International Journal, 30(1), 12-34.
Birch, G. F. (2017). Determination of sediment metal background concentrations and enrichment in marine environments–a critical review. Science of the total environment, 580, 813-831.
Castillo-Nava, D., Elias-Santos, M., López-Chuken, U. J., Valdés-González, A., de la Riva-Solís, L. G., Vargas-Pérez, M. P., ... & Luna-Olvera, H. A. (2020). Heavy metals (lead, cadmium and zinc) from street dust in Monterrey, Mexico: ecological risk index. International Journal of Environmental Science and Technology, 17(6), 3231-3240.
Dash, S., Borah, S. S., & Kalamdhad, A. S. (2021). Heavy metal pollution and potential ecological risk assessment for surficial sediments of Deepor Beel, India. Ecological Indicators, 122, 107265.
Desaules A (2012) Critical evaluation of soil contamination assessment methods for trace metals. Sci Total Environ 426:120–131
Dung, T. T. T., Cappuyns, V., Swennen, R., & Phung, N. K. (2013). From geochemical background determination to pollution assessment of heavy metals in sediments and soils. Reviews in Environmental Science and Bio/Technology, 12(4), 335-353.
Egbueri, J. C., & Enyigwe, M. T. (2020). Pollution and ecological risk assessment of potentially toxic elements in natural waters from the Ameka Metallogenic District in southeastern Nigeria. Analytical Letters, 53(17), 2812-2839.
Facchinelli, A., Sacchi, E., & Mallen, L. (2001). Multivariate statistical and GIS-based approach to identify heavy metal sources in soils. Environmental pollution, 114(3), 313-324.
Fathabadi, A., Selajeghe, A., Pezeshk, H., Nazari Samani, A.A., Rohani, H. (2016), Origination of suspended sediments and estimation of its uncertainty (case study: Zaydasht-Fashandak basin of Taleghan). Pasture and Watershed Journal, 70(1): 57-69. [In Persian]
Ghorbanzadeh zaferani, S. G., Hoseini tayefeh, F., Azimi, S., Gandomkar, M., & Badamfirooz, J. (2021). Environmental qualitative assessment of Karaj River sediments (Alborz Province). Iranian Scientific Fisheries Journal, 30(1), 37-52. doi: 10.22092/isfj.2021.123946 [In Persian]
Hakanson, L. (1980). An ecological risk index for aquatic pollution control. A sedimentological approach. Water research, 14(8), 975-1001.
Hashim, M. A., Mukhopadhyay, S., Sahu, J. N., & Sengupta, B. (2011). Remediation technologies for heavy metal contaminated groundwater. Journal of environmental management, 92(10), 2355-2388.
Hassaan, M. A., El Nemr, A., & Madkour, F. F. (2016). Environmental assessment of heavy metal pollution and human health risk. American Journal of Water Science and Engineering, 2(3), 14-19.
Hou, D., O'Connor, D., Nathanail, P., Tian, L., & Ma, Y. (2017). Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review. Environmental Pollution, 231, 1188-1200.
Huang, J., Li, F., Zeng, G., Liu, W., Huang, X., Xiao, Z., ... & He, Y. (2016). Integrating hierarchical bioavailability and population distribution into potential eco-risk assessment of heavy metals in road dust: A case study in Xiandao District, Changsha city, China. Science of the Total Environment, 541, 969-976.
Hu, Z., & Gao, S. (2008). Upper crustal abundances of trace elements: A revision and update. Chemical Geology, 253(3-4), 205-221.
Izah, S. C., Bassey, S. E., & Ohimain, E. I. (2018). Ecological risk assessment of heavy metals in cassava mill effluents contaminated soil in a rural community in the Niger Delta Region of Nigeria. Molecular Soil Biology, 9.
Jaishankar, M., Tseten, T., Anbalagan, N., Mathew, B. B., & Beeregowda, K. N. (2014). Toxicity, mechanism and health effects of some heavy metals. Interdisciplinary toxicology, 7(2), 60.
Jeong, H., Choi, J. Y., Choi, D. H., Noh, J. H., & Ra, K. (2021). Heavy metal pollution assessment in coastal sediments and bioaccumulation on seagrass (Enhalus acoroides) of Palau. Marine Pollution Bulletin, 163, 111912.
Jorfi, S., Maleki, R., Jaafarzadeh, N., & Ahmadi, M. (2017). Pollution load index for heavy metals in Mian-Ab plain soil, Khuzestan, Iran. Data in brief, 15, 584-590.
Kamani, H., Mahvi, A. H., Seyedsalehi, M., Jaafari, J., Hoseini, M., Safari, G. H., ... & Ashrafi, S. D. (2017). Contamination and ecological risk assessment of heavy metals in street dust of Tehran, Iran. International journal of environmental science and technology, 14(12), 2675-2682.
Kaur, M., Kumar, A., Mehra, R., & Kaur, I. (2020). Quantitative assessment of exposure of heavy metals in groundwater and soil on human health in Reasi district, Jammu and Kashmir. Environmental geochemistry and health, 42(1), 77-94.
Kumar, A., & Kumar, V. (2018). Heavy metal pollution load in the sediment of the river mahananda within Katihar district, Bihar, India. International journal of basic and applied research, 8(11), 515-532.
Kumar, V., Sharma, A., Kaur, P., Sidhu, G. P. S., Bali, A. S., Bhardwaj, R., ... & Cerda, A. (2019). Pollution assessment of heavy metals in soils of India and ecological risk assessment: A state-of-the-art. Chemosphere, 216, 449-462.
Lim, K. Y., Zakaria, N. A., & Foo, K. Y. (2021). Geochemistry pollution status and ecotoxicological risk assessment of heavy metals in the Pahang River sediment after the high magnitude of flood event. Hydrology Research, 52(1), 107-124.
Linnik, P. M., & Zubenko, I. B. (2000). Role of bottom sediments in the secondary pollution of aquatic environments by heavy‐metal compounds. Lakes & Reservoirs: Research & Management, 5(1), 11-21.
Liu, D., Ma, J., Sun, Y., & Li, Y. (2016). Spatial distribution of soil magnetic susceptibility and correlation with heavy metal pollution in Kaifeng City, China. Catena, 139, 53-60.
Long, X., Liu, F., Zhou, X., Pi, J., Yin, W., Li, F., ... & Ma, F. (2021). Estimation of spatial distribution and health risk by arsenic and heavy metals in shallow groundwater around Dongting Lake plain using GIS mapping. Chemosphere, 269, 128698.
Ma, Y., Egodawatta, P., McGree, J., Liu, A., & Goonetilleke, A. (2016). Human health risk assessment of heavy metals in urban stormwater. Science of the Total Environment, 557, 764-772.
Martin, J. M., & Meybeck, M. (1979). Elemental mass-balance of material carried by major world rivers. Marine chemistry, 7(3), 173-206.
Miretzky, P., & Cirelli, A. F. (2010). Remediation of arsenic-contaminated soils by iron amendments: a review. Critical Reviews in Environmental Science and Technology, 40(2), 93-115.
Muller, G. (1969). Index of geoaccumulation in sediments of the Rhine River. Geojournal, 2, 108-118.
Nosrati, K., & Collins, A. L. (2019). Investigating the importance of recreational roads as a sediment source in a mountainous catchment using a fingerprinting procedure with different multivariate statistical techniques and a Bayesian un-mixing model. Journal of hydrology, 569, 506-518.
Nosrati, K., Akbari-Mahdiabad, M., Fiener, P., & Collins, A. L. (2021). Using different size fractions to source fingerprint fine-grained channel bed sediment in a large drainage basin in Iran. CATENA, 200, 105173.
Ota, Y., Suzuki, A., Yamaoka, K., Nagao, M., Tanaka, Y., Irizuki, T., ... & Nishimura, O. (2021). Geochemical distribution of heavy metal elements and potential ecological risk assessment of Matsushima Bay sediments during 2012–2016. Science of The Total Environment, 751, 141825.
Paul, V., Sankar, M. S., Vattikuti, S., Dash, P., & Arslan, Z. (2021). Pollution assessment and land use land cover influence on trace metal distribution in sediments from five aquatic systems in southern USA. Chemosphere, 263, 128243.
Phillips, J. M., Russell, M. A., & Walling, D. E. (2000). Time‐integrated sampling of fluvial suspended sediment: a simple methodology for small catchments. Hydrological Processes, 14(14), 2589-2602.
Proshad, R., Kormoker, T., & Islam, S. (2021). Distribution, source identification, ecological and health risks of heavy metals in surface sediments of the Rupsa River, Bangladesh. Toxin reviews, 40(1), 77-101.
Rahmanian, M., & Safari, Y. (2020). Contamination factor and pollution load index to estimate source apportionment of selected heavy metals in soils around a cement factory, SW Iran. Archives of Agronomy and Soil Science.
Saxena, G., Purchase, D., Mulla, S. I., Saratale, G. D., & Bharagava, R. N. (2019). Phytoremediation of heavy metal-contaminated sites: eco-environmental concerns, field studies, sustainability issues, and future prospects. Reviews of Environmental Contamination and Toxicology Volume 249, 71-131.
Singh, M., Müller, G., & Singh, I. B. (2002). Heavy metals in freshly deposited stream sediments of rivers associated with urbanisation of the Ganga Plain, India. Water, Air, and Soil Pollution, 141(1), 35-54.
Taghipour, M., Ayoubi, S., & Khademi, H. (2011). Contribution of lithologic and anthropogenic factors to surface soil heavy metals in western Iran using multivariate geostatistical analyses. Soil and Sediment Contamination: An International Journal, 20(8), 921-937.
Trujillo-González, J. M., Torres-Mora, M. A., Keesstra, S., Brevik, E. C., & Jiménez-Ballesta, R. (2016). Heavy metal accumulation related to population density in road dust samples taken from urban sites under different land uses. Science of the Total Environment, 553, 636-642.
Yan- Chu, H. (1994). Arsenic Distribution in Soils. In: Arsenic in The Environment, Part I,Cycling and Characterization, Ed. J. O. Nriagu, p. 17- 51.
Ukah, B. U., Egbueri, J. C., Unigwe, C. O., & Ubido, O. E. (2019). Extent of heavy metals pollution and health risk assessment of groundwater in a densely populated industrial area, Lagos, Nigeria. International Journal of Energy and Water Resources, 3(4), 291-303.
Weissmannová, H. D., & Pavlovský, J. (2017). Indices of soil contamination by heavy metals–methodology of calculation for pollution assessment (minireview). Environmental monitoring and assessment, 189(12), 1-25.
Wen, X., Lu, J., Wu, J., Lin, Y., & Luo, Y. (2019). Influence of coastal groundwater salinization on the distribution and risks of heavy metals. Science of the Total Environment, 652, 267-277.
Xiong, Q., Zhao, W., Zhao, J., Zhao, W., & Jiang, L. (2017). Concentration levels, pollution characteristics and potential ecological risk of dust heavy metals in the metropolitan area of beijing, china. International journal of environmental research and public health, 14(10), 1159.
Yujun, Y. I., Zhaoyin, W., Zhang, K., Guoan, Y. U., & Xuehua, D. (2008). Sediment pollution and its effect on fish through food chain in the Yangtze River. International Journal of Sediment Research, 23(4), 338-347.
Zare Chahoki, M.A. (2011). Data analysis in natural resources research with SPSS software. Academic Jihad Publications, Tehran branch. 310 p. [In Persian]
Zhang, L., & Liu, J. (2014). In situ relationships between spatial–temporal variations in potential ecological risk indexes for metals and the short-term effects on periphyton in a macrophyte-dominated lake: a comparison of structural and functional metrics. Ecotoxicology, 23(4), 553-566.
Zhao, S., Feng, C., Yang, Y., Niu, J., & Shen, Z. (2012). Risk assessment of sedimentary metals in the Yangtze Estuary: New evidence of the relationships between two typical index methods. Journal of hazardous materials, 241, 164-172.
Qi, S., Leipe, T., Rueckert, P., Di, Z., & Harff, J. (2010). Geochemical sources, deposition and enrichment of heavy metals in short sediment cores from the Pearl River Estuary, Southern China. Journal of marine systems, 82, S28-S42. | ||
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