Evaluation of Heavy Metal Contamination and Ecological Risk Assessment in Sediments of Karun using Aquatic Pollution Indices

Hedayatzadeh, Fariba; Hassanzadeh, Nasrin

doi:10.29252/archhygsci.9.1.10

Cited by 3 publications

(3 citation statements)

References 39 publications

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“…When the metal results were evaluated in general, sampling point T3 was found to be above the standard values for almost every metal according to both the background values and the SQG values. High amounts of heavy metals in ecosystems are usually described in the literature due to the discharge of wastewater from agriculture (pesticides and fertilizers), industrial activities and domestic wastewater (Yang et al 2009;Hedayatzadeh and Hassanzadeh 2020). Accordingly, the fact that sampling point T3 was the channel sample within the industry of Tekkeköy District and the industrial and domestic wastewater discharges in the environment led to an increase in metal contamination at this sampling point.…”

Section: Distribution Of Heavy Metals In the Sediment And Assessment According To Sqgmentioning

confidence: 99%

Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkeköy, North of Turkey

Şimşek

Özkoç

Bakan

2021

Environ Sci Pollut Res

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A detailed study was conducted in order to evaluate the effects of heavy metal pollution in the sediments in terms of environmental, ecological and human health. Sediment samples were collected from 5 different points in two seasons, namely summer (August 2017) and winter (December 2017), to determine the distribution of heavy metals, potential pollutants, toxic and ecological risks in the river sediments in Samsun -Tekkeköy district located in the Mid-Black Sea Region of Turkey and to evaluate the human health risk. The distribution of heavy metals at the sampling points was Fe > Al > Mn > Zn > Cu > Cr > Ni > Pb > Cd based on their averages. According to the toxic risk index (TRI) results, sampling point OIZ (Organized Industrial Zone) Channel (T3) was also found to have a moderate risk, and it was determined that the highest contribution was from Cu > Ni > Cd > Cr, respectively. Potential ecological risk (PERI) results revealed a low risk except for Cd metal at all sampling points. While the sediment enrichment factor (EF) did not show much metallization at many points, the highest enrichment was observed in Cd, Cu, and Zn metals and at sampling point T3. According to the geoaccumulation index (I geo ) and contamination factor (C F ), sampling point T3 showed contamination with Cd, Cu, Cr, and Zn. Evaluation of human health risk showed that the hazard index (HI) results of carcinogenic and non-carcinogenic risks were higher among children than adults. The total lifetime cancer risks (TLCR) of heavy metals were within the limits determined by USEPA. However, the risk was ranked as Cr > Cd > Pb. Sediment Quality Guidelines (SQG) and pollution index results showed that heavy metal contamination was due to anthropogenic and industrial activities since the region was an industrial zone. It was determined that heavy metals posed ecological risks and that Samsun-Tekkeköy region was moderately and signi cantly contaminated.

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Section: Distribution Of Heavy Metals In the Sediment And Assessment According To Sqgmentioning

confidence: 99%

Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkeköy, North of Turkey

Şimşek

Özkoç

Bakan

2021

Environ Sci Pollut Res

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“…The regional water environment ecosystem health assessment model based on GNN can evaluate the regional water environment ecosystem health status faster and more accurately, and the model has strong generalization. [3]…”

Section: Introductionmentioning

confidence: 99%

Regional water environment risk assessment and ecological health regulation based on genetic neural network

Wang,

Bu,

Wang

et al. 2024

International Conference on Smart Transportation and City Engineering (STCE 2023)

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Groundwater is one of the important water resources in China. Its advantages include rich reserves, good water quality, convenient access and not easy to lose. According to the groundwater resources survey, two-thirds of cities in China exploit groundwater, which has become the main drinking water source of these cities. Therefore, groundwater is of great significance in protecting the ecological environment and human health. In this paper, Genetic neural network(GNN) algorithm is proposed for regional water environment risk assessment(RA) and ecological health regulation(EHR), and the water environment RA index system based on GNN model is studied and analyzed; The regulation measures of ecological health of water environment are put forward; Taking the groundwater environment of a city as the research object, the regional water environment RA and health regulation test analysis are carried out. The test results verify the effectiveness of the regional water environment RA and EHR based on GNN proposed in this paper, and ensure the rationality of the design of ecological regulation and control scheme, which has strong popularization.

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“…[1][2][3] Soil contaminants can be solid or liquid that can be mixed with natural soil. 4,5 The main types of soil pollutants are oil contamination, industrial inputs, urban pollutants (sewage and waste) and agricultural pollutants. 6,7 The potentially toxic elements (PTEs) such as lead (Pb), cadmium (Cd), zinc (Zn), copper (Cu), herbicides and pesticides are the most important soil contaminants.…”

mentioning

confidence: 99%

Ecological and Human Health Risks Assessment of Potentially Toxic Elements Contamination of Surface Soils in Shushtar and Dezful, Iran

Payandeh

2023

Journal of Advances in Environmental Health Research

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Background: The potentially toxic elements (PTEs) are one of the most dangerous pollutants in the environment. In this study, the elements namely cadmium, lead, chromium, nickel, copper and zinc were investigated in the soil. Methods: In this study, 144 composite samples were randomly prepared from surface soils in a depth of 10 cm in the cities of Shushtar and Dezful. Soil sampling was performed in 12 stations in Shushtar and Dezful. The PTEs were determined by ICP Varian 710-ES device. Results: The pattern of accumulation of PTEs was as Cu>Pb>Cd>Zn>Ni>Cr in Dezful. In Shushtar, the accumulation of metals in the soil was as Cu>Pb>Cd>Ni>Zn>Cr. The concentration of Ni and Cr in the surface soils of Shushtar was higher than Dezful. The Ecological risk of Cd in the surface soils of Dezful and Shushtar was higher than other PTEs. The most important risk factor for carcinogenicity was related to Cr (3.15×10-7) in children. Hazard quotient (HQ) value of studied PTEs for adults and children were obtained by ingestion, inhalation, and dermal contact absorption of less than 1. Conclusion: According to the results, the PTEs of Cd, Pb and Cu caused high pollution in the soils of Shushtar and Dezful, which is due to agricultural, industrial and urban activities in these areas. In general, the metals Cr, Zn and Ni slightly contaminated the soil. Also, the ecological risk of PTEs showed that the highest effects on soil was related to Cd and Pb metals.

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Evaluation of Heavy Metal Contamination and Ecological Risk Assessment in Sediments of Karun using Aquatic Pollution Indices

Cited by 3 publications

References 39 publications

Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkeköy, North of Turkey

Environmental, ecological and human health risk assessment of heavy metals in sediments at Samsun-Tekkeköy, North of Turkey

Regional water environment risk assessment and ecological health regulation based on genetic neural network

Ecological and Human Health Risks Assessment of Potentially Toxic Elements Contamination of Surface Soils in Shushtar and Dezful, Iran

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