A study of pollution of heavy metals in surface water sediments &amp;#x2014; A case study of the gold mining area in Xiaoqinling, Puyugou

Xi-cheng, Xue; Pan, Wang; He, Yi; Zhang, Rui; Jisong, Bi

doi:10.1109/icetce.2011.5776242

Cited by 2 publications

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“…This kind of mine water used for irrigation of farmland will cause the soil to form a cumulative "black soil", which will lead to soil hardening and then lead to vegetation degradation, crop withering, yield reduction, etc. [5,6].Mine water seeps into groundwater or drains directly into rivers [7], on the one hand, causes waste of water resources and pollution of rivers [5,8], on the other hand, because there are a lot of coal dust, rock powder and bacteria in the mine water, longterm discharge will also seriously affect the health of local residents' drinking water [9][10][11]. In soil, coal derived carbon is different from plant derived organic carbon.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Inversion of Coal Concentration in Mine Water by Visible-Near Infrared Spectroscopy

Hong

Yan

et al. 2023

IEEE Access

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The coal concentration in mine water is the main indicator of mine water discharge. The accurate determination of coal concentration is of great significance for the purification and secondary utilization of mine water. In order to study the spectral inversion method of coal concentration in mine water, samples with different coal concentrations of 0mg/L-1000mg/L are prepared in this paper, and the ASD Field Spec 4 spectrometer is used for spectral collection (350-2500nm) ,It is found that the maximum influence of different coal content on spectral reflectance is 0.9. Based on this, a CKCNN (C-K -Convolutional Neural Networks) inversion model of coal content in mine water is proposed. This model uses CARS (Competitive Adapative Reweighted Sampling) algorithm to extract sensitive wave bands, and uses CNN (Convolutional Neural Networks) to establish spectral inversion model in sensitive wave bands, K-fold cross validation is used to optimize the model , the model inversion accuracy is R 2 =0.9994, RMSE=6.1401,RPD=41.9692. In this study, CKCNN was compared with five models: SPA+BF, CARS+BF, SPA+CNN, All Band +CNN and CARS+CNN. The results show that CKCNN model has the best effect. In addition, The concentration of water coal in Jiaozuo Zhongma Coal Mine is 18.75mg/L, the actual concentration measured in the laboratory is 18.92mg/L, and the inversion error is 0.17mg/L. The inversion results meet the requirements of laboratory measurement in GB11901-1989. The research results show that the hyperspectral remote sensing in the visible-near-infrared band can quickly detect the coal concentration in the mine water. The CKCNN model provides a new method for the determination of the coal content in the mine water. It is of great significance to promote the research on the influence of the coal concentration in the mine water on the visible-nearinfrared spectrum.

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Section: Introductionmentioning

confidence: 99%

Experimental Study on the Inversion of Coal Concentration in Mine Water by Visible-Near Infrared Spectroscopy

Hong

Yan

et al. 2023

IEEE Access

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“…The potential pollution risk was more serious due to the prolonged duration of pollution, outdated treatment technology, and poor supervision and management [9]. Therefore, the pilot project to address historical legacy issues about ailing ponds, waste storage sites, agricultural land contaminated by heavy metals, landfill surroundings, and ecological damage in mining areas was explicitly listed as one of the key projects in the national 'Comprehensive Prevention and Control Plan for Heavy Metal Pollution' [10]. The state of heavy metal contamination in a pyrite mining location with historical residues was examined in this study and the remediation strategies that could serve as a model for similar operations were provided.…”

Section: Introductionmentioning

confidence: 99%

Ecological Risk Assessment and Spatial Distribution of Heavy Metal in an Abandoned Mining Area, a Case Study of Liaoyang Pyrite Mining Area in China: Implications for the Environmental Remediation of Mine Sites

Zhu,

Li,

Yan

et al. 2023

Pol. J. Environ. Stud.

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An important hidden source of soil heavy metal pollution was the discharge of wastewater and waste rock during mining production activities. Numerous processes could result in the buildup of heavy metals in soil, and exposure to these metals could irreversibly harm a person's health. The source, distribution and quantity of historical waste residue in a pyrite mining area were described, and the nature of the waste residue was determined based on the results of toxic leaching identification in this study. The study showed that the pH value of the leaching solution of the waste residues was less than 6. Therefore, these waste residues was the second category of general industrial solid waste. The soil around the waste residues was basically acidic. Also, the content of arsenic, cadmium and copper in farmland soil around the waste residues exceeded the screening value in the Soil Environmental Quality Standard Risk Control of Soil Pollution in Farmland (GB15618-2018). Therefore, the arsenic, cadmium and copper in the waste residue could migrate with rainwater and cause some pollution to the neighboring farmland soil. The surface water was acidic and the arsenic concentration in the surface water exceeded the standard limit. Therefore, surface water was affected by acidic wastewater. However, the impact of project wastewater on groundwater was not significant. Through the analysis of the pollution status, comprehensive treatment countermeasures and secondary pollution prevention measures for the waste residue were proposed, as well as the issues

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A study of pollution of heavy metals in surface water sediments — A case study of the gold mining area in Xiaoqinling, Puyugou

Cited by 2 publications

References 0 publications

Experimental Study on the Inversion of Coal Concentration in Mine Water by Visible-Near Infrared Spectroscopy

Experimental Study on the Inversion of Coal Concentration in Mine Water by Visible-Near Infrared Spectroscopy

Ecological Risk Assessment and Spatial Distribution of Heavy Metal in an Abandoned Mining Area, a Case Study of Liaoyang Pyrite Mining Area in China: Implications for the Environmental Remediation of Mine Sites

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