Modeling and Prediction of Heavy Metal Pollution in Mining Areas Based on Grey Model GM (1, 1)

Author(s):  
Shuitai Xu ◽  
Lingyan Xiong ◽  
Yunzhang Rao ◽  
Jianping Pan
2021 ◽  
Author(s):  
Xun Wang

Abstract In this study, taking a coal mining area as an example, three vegetation restoration modes were designed: Populus L., Ligustrum lucidum Ait., and Amygdalus persica L., and soil and plant samples were collected to determine and evaluate the heavy metals. It was found that all the three modes were effective in eliminating heavy metal pollution in the soil, especially Populus L. and Ligustrum lucidum Ait.; in the soil layer at a depth of 0–20 cm, the content of Cd was the lowest (2.68 mg/kg) in Populus L., and the content of Cr and Pb was the lowest (58.64 mg/kg and 95.36 mg/kg) in Ligustrum lucidum Ait., which was significantly lower than that in the bare land. The evaluation results demonstrated that the pollution under Populus L. and Ligustrum lucidum Ait. modes was moderate. In the aspect of the heavy metal content in plants, the content of Cd was the lowest, and the content of Cr and Pb was high. In the same plant, the content of heavy metals in the leaf was the lowest, followed by the stem and root. The experimental results show that the vegetation restoration mode can relieve the heavy metal pollution, which makes some contributions to solve the ecological restoration problem in coal mining areas.


2021 ◽  
Author(s):  
Minjie Chen ◽  
Xiaoru Jiang ◽  
Zhansheng Mi ◽  
Yafei Li ◽  
Zhe Wang ◽  
...  

Abstract Background Environmental pollution from rare earth mining areas is of great concern, but the impact on microbial ecology and genomics has received little attention. In this study, the relationship between heavy metals and soil microbial community in the northern rare earth mining area was explored. Methods In order to study the detoxification mechanisms of heavy metals by microorganisms in this typical rare earth mining area, the study area was divided into three parts (mining area, residential area and control area). Analysis of microbial community diversity, structure and functional abundance using high-throughput sequencing techniques. Analysis of the effect of heavy metal pollution on the abundance of heavy metal resistance genes in soils of different regions using real-time fluorescence quantitative PCR. Results The results showed that the heavy metal pollution rules: mining area > residential area > control area. Under the condition of long-term heavy metal pollution, the original microbial community composition was changed, and the species richness and evenness of soil in mining areas were higher than that in residential areas. The high-throughput sequencing analysis showed that existed metal-resistant microbial communities such as Actinobacteria, Proteobacteria, Korarchaeota and so on under the stress of heavy metal. High concentrations of heavy metals can inhibit the activities of catalase and sucrase. According to Tax4Fun function prediction analysis, heavy metal accumulation increased the ABC transporter protein in microbial function. The results of fluorescence quantification experiments also demonstrated that the abundance of heavy metal resistance genes, czcA, czcB, czcC and czcD, encoding ABC transporter proteins, increased with increasing heavy metal concentrations. Conclusions In conclusion, the accumulation of heavy metals not only changed the soil physicochemical properties and the microbial community structure, but also decreased soil enzyme activities and increased the abundance of resistance genes, which activated the detoxification mechanism of heavy metals. which provided a reference for future ecological remediation.


2011 ◽  
Vol 66 (2) ◽  
pp. 673-682 ◽  
Author(s):  
Jihong Dong ◽  
Min Yu ◽  
Zhengfu Bian ◽  
Yindi Zhao ◽  
Wei Cheng

2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.


Sign in / Sign up

Export Citation Format

Share Document