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

Arghavan Panahi, Vahid Bakhtiari, Farzad Piadeh, Kourosh Behzadian

Research output: Contribution to journalArticlepeer-review

Abstract

Sustainable sludge management in wastewater treatment plants is a critical challenge that demands strategic planning and holistic evaluation tools. This study presents a novel data-driven framework for sustainable, multifunctional circular sludge management. Unlike conventional models, the framework integrates circular planning, scenario-based foresight, a data-driven approach, and sustainability assessment to identify optimal sludge reuse pathways and treatment alternatives. A dynamic 3D SWOT methodology is employed to prioritise circular actions. We also introduce a modified decision support system incorporating 15 new criteria across 39 parameters, supported by uncertainty analysis. To demonstrate the framework, we applied it to a wastewater treatment plant in Iran. Seven circular reuse strategies were assessed: sanitised landfill, compost for agriculture, incineration for bricks, road pavement, concrete paving blocks, incineration for ceramics, and clay-based pipelines. These were evaluated across 24,000 potential future scenarios. The model was run over 500 times to perform a comprehensive sensitivity analysis on strategic and assessment outcomes. Results identified composting use as the most optimal strategy. The most sustainable treatment configuration included dissolved air flotation, anaerobic digestion, and pressurised strip filters. Sensitivity analysis revealed key external and internal drivers, highlighted the importance of temporal attributes, and showed the influence of expert judgment. The framework delivers resilient, adaptive, and context-sensitive solutions for sustainable sludge management. It serves as a robust decision-making tool for infrastructure planners, policymakers, and environmental engineers. However, the approach has limitations, including dependence on data availability, equal probability for all scenarios, and assumptions in scenario modelling, which should be considered in broader applications.

Original languageEnglish
Article number126615
Number of pages21
JournalJournal of Environmental Management
Volume392
Early online date23 Jul 2025
DOIs
Publication statusPublished - 30 Sept 2025

Keywords

  • Data-driven framework
  • Multi-function alternatives
  • Scenarios analysis
  • Sludge management
  • Strategic planning
  • Sustainable assessment

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