Integrated digital framework for wastewater treatment performance and sustainability assessment in low-income countries

Modelling and simulation are widely used to optimise biological wastewater treatment processes, while life cycle assessment (LCA) is well established for evaluating environmental impacts. However, integrated modelling-LCA approaches have largely been developed for data-rich and well-resourced settings, limiting their practical application in developing countries where reliable operational data, technical capacity, and resources are often constrained. Moreover, few studies have demonstrated such integrated approaches using field-measured data and validated their recommendations through full-scale implementation. To address these gaps, an integrated digital framework linking metabolic activated sludge model (META-ASM) with LCA was developed and applied to optimise the Santa Catarina wastewater treatment plant (WWTP) in Cape Verde. The framework integrates systematic data collection and reconciliation, field-data-driven dynamic simulation, scenario-based optimisation, sensitivity analysis, and sustainability assessment. Model predictions were evaluated against observed plant performance, and operational and structural scenarios were sequentially assessed to identify improvements across individual treatment units. The recommended operational strategies were subsequently implemented at full scale, with field monitoring confirming reductions in effluent total chemical oxygen demand (COD Tot ), total suspended solids (TSS), total phosphorus (P Tot ), and total nitrogen (N Tot ) of 51.4%, 58.7%, 44.4%, and 21.5%, respectively, compared with baseline operation. LCA further demonstrated reductions of approximately 30% in human toxicity, freshwater ecotoxicity, and marine ecotoxicity, and 36% in eutrophication potential. Beyond improving treatment and environmental performance, the framework incorporates practical data-management tools, capacity building, and context-specific operational considerations. This field-validated, data-adaptive approach provides a scalable and transferable pathway for applying digital process modelling and sustainability assessment to WWTP optimisation in resource-constrained developing country contexts.