Linear optimization of sludge transportation and treatment pathways in a semi-centralized wastewater treatment system in Metro Manila, Philippines

Abstract

This study explores the optimization of sludge transportation and treatment pathways within a semi-centralized wastewater treatment system in Metro Manila, Philippines, aiming to minimize greenhouse gas (GHG) emissions. Linear optimization was employed to analyze sludge management alternatives, focusing on transportation, treatment processes, biogas production, energy recovery, and emissions. The study evaluates sludge management scenarios, incorporating environmental impacts such as CO₂, CH₄, and N₂O emissions. Results indicate that centralized sludge treatment facilities equipped with anaerobic digesters and combined heat and power (CHP) systems significantly reduce net GHG emissions, achieving a net sequestration of −67.1 tons CO2e/day. Transportation emissions were found to be negligible compared to treatment processes. North Metro Manila Water Treatment Facility (NWTF)’s integrated sludge treatment facility, designed for energy recovery, presented the most environmentally favorable option, whereas facilities relying simply on flaring biogas without energy recovery demonstrated higher emissions. The disposal emissions also contributed greatly to carbon emissions representing 88.8% of the total system emissions. Key findings suggest that enhancing biogas recovery systems and reducing emissions from combustion processes are critical for further sustainability improvements. This provides an insight that disposal emissions should be highly considered when choosing a method rather than its proximity to the treatment facilities. This study highlights the potential of linear optimization in informing sustainable sludge management strategies aligned with environmental and operational goals. While the study provides valuable insights for sustainable sludge management, it is limited by the exclusion of the wastewater treatment emission from which the sludge was derived from. Emission estimates were also based on assumptions and IPCC emission factors in the absence of primary local data. These findings highlight the role of linear optimization in supporting environmentally sound and operationally efficient decision-making in sludge management.