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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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A Cost Allocation Decision Model for Air Pollution Control.

Dong-Sheng Qin1, Chang-Yuan Gao1

  • 1Harbin University of Science and Technology, Harbin, China.

Computational Intelligence and Neuroscience
|February 10, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a fair cost allocation model for air pollution control projects using the Shapley value. This approach reduces costs and risks for stakeholders, maximizing overall social benefits.

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Area of Science:

  • Environmental Science
  • Environmental Management
  • Public Policy

Background:

  • Air pollution control necessitates effective cost allocation strategies.
  • Existing methods may not adequately address stakeholder fairness.
  • Coordinated governance is crucial for atmospheric pollution mitigation.

Purpose of the Study:

  • To develop a fair cost allocation model for air pollution control projects.
  • To identify core stakeholders in pollution governance.
  • To establish a collaborative governance framework for atmospheric pollution.

Main Methods:

  • Utilizing the Shapley value for cost allocation.
  • Analyzing stakeholder contributions and benefits.
  • Developing a governance cost allocation model.

Main Results:

  • The Shapley value-based model provides a more reasonable cost distribution.
  • Stakeholder costs are reduced through equitable allocation.
  • Participant risks are minimized, enhancing project viability.

Conclusions:

  • The Shapley value model offers an equitable and efficient solution for air pollution control costs.
  • This approach enhances collaboration and maximizes social benefits in environmental governance.
  • Fair cost allocation is key to successful coordinated air pollution mitigation efforts.