Contamination and Ecological Risk Assessment of Heavy Metals in Surface Sediments of Huangshui River, Northwest China

Fang, Yining; Wei, Qi; Xu, Guangsu; Wei, Meng; Chen, Hao

doi:10.1155/2022/4282992

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…This indicates that soil salinization and soil heavy metal pollution may jointly affect the cultivated lands in the study area. This may be related to the soil texture and irrigation using Bosten Lake water [55]. Additionally, soil salinity is closely related to the transformation of SOM, AN, and heavy metal forms, which further affects the distribution and migration of nutrients and heavy metals in the soil [56].…”

Section: Analysis Of Soil Quality Evaluation Indicesmentioning

confidence: 99%

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Fan,

Gao,

Zuo

et al. 2023

Land

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Accurate soil quality evaluation is an important prerequisite for improving soil management systems and remediating soil pollution. However, traditional soil quality evaluation methods are cumbersome to calculate, and suffer from low efficiency and low accuracy, which often lead to large deviations in the evaluation results. This study aims to provide a new and accurate soil quality evaluation method based on graph convolution network (GCN). In this study, soil organic matter (SOM), alkaline hydrolysable nitrogen (AN), available potassium (AK), salinity, and heavy metals (iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn)) were determined and evaluated using the soil quality index (SQI). Then, the graph convolution network (GCN) was first introduced in the soil quality evaluation to construct an evaluation model, and its evaluation results were compared with those of the SQI. Finally, the spatial distribution of the evaluation results of the GCN model was displayed. The results showed that soil salinity had the largest coefficient of variation (86%), followed by soil heavy metals (67%) and nutrients (30.3%). The soil salinization and heavy metal pollution were at a low level in this area, and the soil nutrients and soil quality were at a high level. The evaluation accuracy of the GCN model for soil salinity/heavy metals, soil nutrients, and soil quality were 0.91, 0.84, and 0.90, respectively. Therefore, the GCN model has a high accuracy and is feasible to be applied in the soil quality evaluation. This study provides a new, simple, and highly accurate method for soil quality evaluation.

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Section: Analysis Of Soil Quality Evaluation Indicesmentioning

confidence: 99%

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Fan,

Gao,

Zuo

et al. 2023

Land

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“…However, burning procedures are the greatest imperative causes of metallic elements, specifcally the production of energy, melting, ignition, and the inner fring engine in various countries around the world [22]. General farming, as well as fast development, is possible foundations of dense metal contamination [23]. Unprocessed wastes after agrochemicals, insecticides, vehicle reparation, washes, steel coating, workrooms, waste discharges, and other sources are liquidated into the surrounding streams, which are primarily used for vegetable production via irrigation [24].…”

Section: Vegetable Production In Ethiopiamentioning

confidence: 99%

Impacts of Heavy Metal Pollution on Ethiopian Agriculture: A Review on the Safety and Quality of Vegetable Crops

Gelaye

Musie

2023

Advances in Agriculture

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Lack of nutritive and consumption of polluted food sources are the main health implications in African countries. Vegetable production is an optional balanced food source easily grown in the urban and rural areas. However, the levels of contaminant heavy metals in cultivated vegetables have not yet been identified. This review scrutinizes the contamination route, sources, health effects, environmental problems, food safety complications, and remedial activities of vegetable production in Ethiopian agriculture. Informal settlement, the rapid rate of urbanization, and the lack of community-based industrial expansion lead to massive increases in toxic heavy metals in ecosystems. They are supplied with food source diets unrestrictedly, mainly for vegetable consumption. Among the assessed metals, Zn (112.7 mg/kg), Cr (47.7 mg/kg), Pb (17.76 mg/kg), and Cd (0.25 mg/kg) existed in vegetables, with the highest concentrations in Ethiopia. They have negative effects on public safety, environmental security, and nutrient levels in horticultural crops. Hence, Ethiopia has no permissible standards for vegetable consumption and hazard analysis, critical control point, or food safety system. Additionally, physical, biological, and natural remedial strategies such as phytoremediation, phytoextraction, phytostabilization, rhizofiltration, bioremediation, and phytovolatilization are not applied to curtail deadly substance contents in Ethiopia. Despite this, some mitigation strategies, such as industrial waste treatment activities, are underway in Ethiopia’s universities and beer and sugar factories. This review found that the use of integrated remedial strategies could help to improve the efficiency of strategies in a sustainable manner, solid safety control for heavy metal management in Ethiopia, and management should begin with local solutions.

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“…For example, Xining had a population of 2.476 million in 2021 and received a total of 240.39 million tourists during the same year. The significant increase in human activities has introduced a tremendous burden to the ecological environment of the Huangshui River [21]. In 2022, agriculture and animal husbandry were also found to be contaminating the Huangshui River [22].…”

Section: Influence Of Seasons On the Vocs In Different Samplesmentioning

confidence: 99%

Human Activities Aggravate VOC Pollution in the Huangshui River of the Tibetan Plateau

Yang

Deng

et al. 2022

Sustainability

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Many xenobiotic compounds can threaten human health and natural ecosystems. The ability to predict the level of human activities and identify major impact factors is crucial for the design of pollutant risk-reduction plans. In this study, a total of 25 volatile organic compounds (VOCs) including eight alkenes, six alkanes, and eleven aromatics were identified at 11 monitoring locations along the Huangshui River of the Tibetan Plateau. GC-MS analysis was applied to detect the concentrations of the VOCs. The results showed that the alkene, alkane, and aromatic concentrations in the sediment were significantly higher than in the water in all seasons (p < 0.001). The VOC concentrations in summer were significantly higher than in spring and winter (p < 0.01). In addition, several VOCs were found to surpass the national standard, i.e., bromoform reached 312.43 μg/L in water during the summer (the national standard is 100 μg/L), carbon tetrachloride was 209.58 μg/L (the national standard is 2 μg/L), and vinyl chloride was 10.99 μg/L (the national standard is 5 μg/L), which were all related to human activities. Principal component analysis (PCA) was used to comprehensively evaluate the water quality and the VOCs. The total organic carbon (TOC) was found to be responsible for the presence of the VOCs in the river, accounting for 77.93%, 81.97%, and 82.13% of the total variance in the datasets in spring, summer, and winter, respectively.

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Contamination and Ecological Risk Assessment of Heavy Metals in Surface Sediments of Huangshui River, Northwest China

Cited by 5 publications

References 31 publications

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Impacts of Heavy Metal Pollution on Ethiopian Agriculture: A Review on the Safety and Quality of Vegetable Crops

Human Activities Aggravate VOC Pollution in the Huangshui River of the Tibetan Plateau

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