Best-compromise solutions for waste management: Decision support system for policymaking

Area of Science:

• Environmental Science
• Operations Research
• Waste Management

Background:

• Urban organic waste management is critical for sustainable and circular development.
• The organic fraction is the largest component of municipal solid waste, representing a valuable resource.
• Mismanagement leads to increased costs and socio-environmental issues.

Purpose of the Study:

• To propose a Decision Support System (DSS) for policymakers to improve organic waste management planning.
• To utilize linear programming techniques for optimizing resource allocation in the organic waste sector.
• To provide insights for cost-effective and sustainable treatment solutions for the organic fraction of municipal solid waste.

Main Methods:

• Development of an optimization model based on linear programming techniques.
• Application and testing of the model on the Campania Region (Italy) waste management system.
• Analysis of three distinct scenarios: Ideal Solution, Max NPV Solution, and Best Compromise Solution.

Main Results:

• The 'Ideal Solution' serves as a benchmark but is not practically achievable.
• The 'Max NPV Solution' is feasible but presents significant drawbacks.
• The 'Best Compromise Solution' demonstrates substantial improvements, increasing regional composting capability sixfold and biogas availability sevenfold.

Conclusions:

• The proposed DSS effectively identifies cost-effective and sustainable solutions for organic waste treatment.
• The 'Best Compromise Solution' offers a viable pathway to enhance circular economy objectives in waste management.
• The model provides valuable insights for policymakers in resource allocation for organic waste management.