Evaluation of co-substrate alternatives for co-digestion of sewage sludge: Coupling plant-wide modelling with life cycle analysis

Abstract

Sewage sludge is an inevitable byproduct produced during the wastewater treatment process in wastewater treatment plants (WWTPs). As wastewater flows through the various treatment stages, solids settle out and accumulate as sludge. When this sludge undergoes stabilization through anaerobic digestion, biogas—a mixture primarily composed of methane and carbon dioxide—is produced as a valuable byproduct. Biogas can be harnessed as a renewable energy source, contributing to the energy needs of the WWTP and potentially supplying excess energy to the grid. Enhancing biogas production through the co-digestion of sewage sludge with organic waste is a promising strategy, as it can significantly boost the efficiency of anaerobic digestion. Co-digestion involves the addition of organic wastes, such as fat, oil, grease (FOG), and food waste (FW), to the sewage sludge. These organic wastes typically have high methane potential due to their rich organic content, thus increasing the overall biogas yield. However, the co-digestion process is complex and multifaceted. It affects various aspects of WWTP operations, including effluent quality, energy consumption, and greenhouse gas (GHG) emissions. Therefore, selecting the optimal co-digestion scenario for sewage sludge involves careful consideration of multiple factors to ensure a balance between enhanced biogas production and the operational and environmental impacts. Life cycle assessment (LCA) is a widely used method to evaluate the environmental impacts of co-digestion processes comprehensively. Various studies have examined the LCA of co-digesting sewage sludge with different organic wastes. Nevertheless, the LCA approach demands extensive and consistent data, making it challenging to compare different management strategies with high accuracy. This thesis introduces a novel approach by coupling plant-wide modeling with LCA to create a robust tool for comparing the environmental impacts of different anaerobic digestion scenarios. A calibrated mathematical model for a WWTP can generate standardized data outputs for various operational scenarios, thus enhancing the reliability of LCA results in terms of data consistency. Additionally, this thesis offers a unique comparison of the environmental impacts of mono-digestion of sewage sludge versus co-digestion with FOG and FW. This integrated approach will provide decision-makers with a comprehensive tool, combining plant-wide modeling and LCA, to facilitate informed decision-making. The comparison aims to identify the most environmentally sustainable and operationally efficient strategy for WWTPs. In WWTPs, the sewage sludge produced during wastewater treatment is stabilized by anaerobic digesters, generating biogas. This biogas can be used in co-generators to produce energy, which in turn reduces the carbon footprint of WWTPs by decreasing fossil fuel consumption. By co-digesting sewage sludge with organic waste, biogas production can be significantly increased. This not only boosts energy recovery but also reduces the amount of organic waste that ends up in sanitary landfills. Diverting organic waste from landfills is beneficial as it reduces the production of landfill gases, primarily methane, which is a potent GHG. However, the co-digestion process is not without its challenges. The pollutant load of the supernatant resulting from co-digestion is likely higher than that from mono-digestion. This higher pollutant load can negatively impact the discharge quality of the WWTP, requiring additional treatment processes to meet regulatory standards. Additionally, increasing the substrate amount in the anaerobic digester elevates the cost of the stabilization process and influences the GHG emissions from WWTPs. Therefore, there is a delicate balance between effluent quality, energy production, and GHG emissions when choosing between mono-digestion and co-digestion of sewage sludge. LCA is a powerful tool to estimate the environmental impacts of WWTPs and is particularly useful for decision-making, as it allows for the comprehensive evaluation of different scenarios. Despite its advantages, LCA's main drawback is its intense data requirement. Plant-wide modeling, on the other hand, is employed to determine the effects of various scenarios, such as changes in wastewater characteristics and operational conditions, on wastewater treatment performance. By coupling LCA with plant-wide modeling, this thesis aims to address the data intensity and consistency issues associated with LCA, providing a more reliable and holistic assessment tool