Employing gene chip technology for monitoring and assessing soil heavy metal pollution

2021 ◽  
Vol 194 (1) ◽  
Author(s):  
ZiChun Lu ◽  
HaiFeng Su
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Gene Chip ◽  
Soil Heavy Metal ◽  
Chip Technology

Soil Heavy Metal Pollution along Subin River in Kumasi, Ghana; Using X-Ray Fluorescence (XRF) Analysis

2010 ◽  
Author(s):  
K. Kodom ◽  
J. Wiafe-Akenten ◽  
D. Boamah ◽  
Melissa Denecke ◽  
Clive T. Walker
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
X Ray ◽  
Soil Heavy Metal ◽  
Xrf Analysis

Risk assessment and source analysis of soil heavy metal pollution from lower reaches of Yellow River irrigation in China

2018 ◽  
Vol 633 ◽  
pp. 1136-1147 ◽  
Author(s):  
Pengyan Zhang ◽  
Chengzhe Qin ◽  
Xin Hong ◽  
Guohua Kang ◽  
Mingzhou Qin ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Yellow River ◽  
Source Analysis ◽  
Soil Heavy Metal

Soil Heavy Metal Pollution Analysis of City Surface Based on Neural Network

2013 ◽  
Vol 340 ◽  
pp. 947-951
Author(s):  
Jia Pei Pei ◽  
Zhang Tai ◽  
Shi Xiao Shuang ◽  
Xia Bin Yu ◽  
Liu Ran
Keyword(s):  
Neural Network ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Degree Distribution ◽  
Heavy Metal Pollution ◽  
Urban Soil ◽  
Soil Heavy Metal ◽  
Network Building ◽  
Synthetic Index ◽  
Analysis System

Identified the urban soil has heavy metal pollution degree and the cause of the contamination of the overall analysis system. Through the mat lab software to realize pollution degree distribution visualization, use numerous evaluation pollution degree synthetic index methods, and then the reference neural network building the knowledge about the cause of the contamination analysis to determine the mechanism of the main causes of the pollution.

scholarly journals Potential ecological risk assessment and prediction of soil heavy-metal pollution around coal gangue dump

2014 ◽  
Vol 14 (6) ◽  
pp. 1599-1610 ◽  
Author(s):  
X. Jiang ◽  
W. X. Lu ◽  
H. Q. Zhao ◽  
Q. C. Yang ◽  
Z. P. Yang
Keyword(s):  
Heavy Metal ◽  
Ecological Risk ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Pearson Correlation ◽  
Risk Index ◽  
Potential Ecological Risk ◽  
Coal Gangue ◽  
Index Method ◽  
Soil Heavy Metal

Abstract. The aim of the present study is to evaluate the potential ecological risk and trend of soil heavy-metal pollution around a coal gangue dump in Jilin Province (Northeast China). The concentrations of Cd, Pb, Cu, Cr and Zn were monitored by inductively coupled plasma mass spectrometry (ICP-MS). The potential ecological risk index method developed by Hakanson (1980) was employed to assess the potential risk of heavy-metal pollution. The potential ecological risk in the order of ER(Cd) > ER(Pb) > ER(Cu) > ER(Cr) > ER(Zn) have been obtained, which showed that Cd was the most important factor leading to risk. Based on the Cd pollution history, the cumulative acceleration and cumulative rate of Cd were estimated, then the fixed number of years exceeding the standard prediction model was established, which was used to predict the pollution trend of Cd under the accelerated accumulation mode and the uniform mode. Pearson correlation analysis and correspondence analysis are employed to identify the sources of heavy metals and the relationship between sampling points and variables. These findings provided some useful insights for making appropriate management strategies to prevent or decrease heavy-metal pollution around a coal gangue dump in the Yangcaogou coal mine and other similar areas elsewhere.

scholarly journals Multi-Evolutionary Game Research on Heavy Metal Pollution Control in Soil: Based on a Third-Party Perspective

2020 ◽  
Vol 12 (13) ◽  
pp. 5306
Author(s):  
Songtao Xu ◽  
Zhifang Zhou ◽  
Ke Liu
Keyword(s):  
Heavy Metal ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Evolutionary Game ◽  
Rent Seeking ◽  
Strategy Choice ◽  
Third Party ◽  
Soil Heavy Metal ◽  
Pollution Treatment ◽  
The Government

The introduction of third-party governance models for the treatment of soil heavy metal pollution has promoted the marketization, professionalization, and efficiency of pollution treatment, but also can result in distortions of relevant stakeholder relationships and conflicts of interest. The game relationship among the government, soil-polluting companies, and third-party governance companies may solve the practical dilemma of comprehensive management of soil heavy metal pollution and establish a good cooperative mechanism. We constructed a three-party evolutionary game model to analyze the interaction mechanism of each agent’s strategy choice as well as the evolution of each agent’s strategy choice under different parameter trends and simulation analyses. The research showed that the amount of fines and supervision costs, rent-seeking costs and governance costs, and government subsidies and rent-seeking benefits were key factors affecting the evolution and stability strategies of government departments, soil-polluting companies, and third-party governance companies. By cooperating with third-party governance companies, the government can effectively suppress the improper behavior of soil-polluting companies. The conclusions of the study are helpful to broaden the research boundary of soil heavy metal pollution treatment and provide theoretical guidance for the treatment of soil heavy metal pollution in China.

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