Sewage sludge management in wastewater treatment plants: Integrated treatment, resource recovery, and AI-enabled optimization

Sewage sludge generation is rising globally, straining wastewater treatment systems, land resources, and climate targets while simultaneously offering recoverable energy, nutrients, and materials within a circular economy. This review examines how the field is moving beyond disposal along three converging directions: coupling complementary processes into integrated treatment trains, widening the slate of products those trains can recover, and using data-driven tools to operate them reliably at scale. It critically assesses how coupling anaerobic digestion with hydrothermal, thermochemical, advanced-oxidation, and membrane-based processes improves resource efficiency, energy balance, and contaminant control relative to standalone units, and weighs the techno-economic and life-cycle trade-offs of integration. On the recovery side, it synthesizes integrated pathways for phosphorus, nitrogen, bioenergy, carbon materials, and solid recovered fuel, together with emerging high-value products such as medium-chain fatty acids and plant biostimulants. It further evaluates artificial intelligence and machine learning for process prediction, optimization, mechanistic interpretation, and model selection, and the barriers to their full-scale deployment. Conventional mechanical, biological, and thermal treatments, sludge properties, and policy are set out as the context that frames these advances rather than as the focus of the review. Overall, sustainable sludge management will depend on integrated, risk-aware, and data-enabled recovery systems that treat sewage sludge as a secondary resource rather than a residual waste.