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

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.

2010 ◽  
Author(s):  
K. Kodom ◽  
J. Wiafe-Akenten ◽  
D. Boamah ◽  
Melissa Denecke ◽  
Clive T. Walker

2018 ◽  
Vol 633 ◽  
pp. 1136-1147 ◽  
Author(s):  
Pengyan Zhang ◽  
Chengzhe Qin ◽  
Xin Hong ◽  
Guohua Kang ◽  
Mingzhou Qin ◽  
...  

2019 ◽  
Vol 11 (7) ◽  
pp. 2068
Author(s):  
Hua Lu

Heavy metal pollution of farmland is a significant issue affecting the quality of agricultural products and human health. Farmers’ behaviors can have a direct impact on the level of heavy metal pollution affecting farmland in China. Whether the heavy metal pollution of farmland can be effectively governed at a low cost depends on the farmers. This paper analyzes the mechanism by which the extent of non-agricultural employment and environmental awareness influences farmers’ willingness to govern the heavy metal pollution of farmland using microdata for farmers in China and conducts an empirical analysis via a logit model. The results show that farmers in China display low willingness to govern the heavy metal pollution of farmland and that the increase in non-agricultural income will not significantly improve this willingness. Environmental awareness and farmers’ willingness to govern the heavy metal pollution of farmland are closely related: the higher the environmental awareness of farmers is, the stronger their willingness to govern heavy metal pollution, and the higher the probability of their participating in fallow land treatment. The government can introduce incentives to improve farmers’ environmental awareness of the heavy metal pollution of farmland. In addition, the government should strengthen publicity about the positive effects of fallow land treatment and encourage farmers to participate in the governance of heavy metal pollution of farmland. Given increasing non-agricultural employment opportunities and the transformation of agricultural production modes, agricultural technical training provided by governmental departments can enable them to be more scientific and rational in their agrochemical selection and application, thus reducing or avoiding the heavy metal pollution of farmland at the source. Attention should be paid to the differences between farmers to ultimately reduce the cost and improve the efficiency of treatment.


2013 ◽  
Vol 340 ◽  
pp. 947-951
Author(s):  
Jia Pei Pei ◽  
Zhang Tai ◽  
Shi Xiao Shuang ◽  
Xia Bin Yu ◽  
Liu Ran

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.


2014 ◽  
Vol 14 (6) ◽  
pp. 1599-1610 ◽  
Author(s):  
X. Jiang ◽  
W. X. Lu ◽  
H. Q. Zhao ◽  
Q. C. Yang ◽  
Z. P. Yang

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.


Sign in / Sign up

Export Citation Format

Share Document