A systems-based approach to circular sludge management: Data-driven foresight, sustainability assessment, and...

Area of Science:

• Environmental Engineering
• Circular Economy
• Data Science

Background:

• Sustainable sludge management is crucial for wastewater treatment plants.
• Conventional models lack holistic evaluation for optimal sludge reuse.
• A novel framework is needed to integrate circular planning and sustainability assessment.

Purpose of the Study:

• To present a novel data-driven framework for multifunctional circular sludge management.
• To identify optimal sludge reuse pathways and treatment alternatives.
• To provide a decision-making tool for infrastructure planners and policymakers.

Main Methods:

• Integrated circular planning, scenario-based foresight, and sustainability assessment.
• Employed dynamic 3D SWOT methodology and a modified decision support system.
• Assessed seven circular reuse strategies across 24,000 scenarios with sensitivity analysis.

Main Results:

• Composting for agriculture identified as the most optimal sludge reuse strategy.
• Recommended sustainable treatment configuration: dissolved air flotation, anaerobic digestion, and pressurised strip filters.
• Sensitivity analysis highlighted key drivers, temporal attributes, and expert judgment influence.

Conclusions:

• The framework offers resilient, adaptive, and context-sensitive solutions for sustainable sludge management.
• It serves as a robust decision-making tool for environmental professionals.
• Limitations include data dependency and scenario modeling assumptions.