Plant-wide process analysis targeting reliable estimation of biogas production from anaerobic sludge digestion

Abstract

Anaerobic sludge digestion is a critical and widely used technology employed in wastewater treatment plants for the stabilization of solids generated during the treatment process and for the production of biogas as a renewable energy source. This process typically involves the treatment of mixed primary and biological sludge in digesters. Primary sludge comprises inorganic solids and organic matter, whereas biological sludge is rich in active biomass and residues from biochemical reactions. The process faces challenges, such as the lower organic degradation efficiency of waste activated sludge (WAS) under both aerobic and anaerobic conditions, necessitating extended sludge retention times. Hydrolysis, identified as the rate-limiting step in microbial degradation across various environmental conditions, significantly influences the efficiency of the anaerobic digestion process. Therefore, the nature of the degradation of the hydrolysable matter directly influences the efficiency of the anaerobic digestion process. Traditional activated sludge models, which conceptualize COD turnover through a single hydrolysable matter component (XB), do not adequately account for the range of hydrolysis kinetics observed in practice. Despite a plethora of parameter values proposed for anaerobic hydrolysis, research into the kinetic analysis of anaerobic sludge digestion, particularly considering varying mixes of primary and waste activated sludge, remains sparse. The appropriate selection of wastewater treatment and sludge disposal methods depends on specific aspects, including the organic matter components in the influent wastewater and the kinetic parameters specific to the biomass. Therefore, the integration of experimental studies with plant-wide modeling tools is becoming an important strategy for selecting suitable treatment systems and executing reliable process calculations. In this study, seven large-scale wastewater treatment plants were analyzed for operational parameters and dynamic modeling was combined with plant-focused batch experiments to uncover deviations from the calculated data during the design phase. The long-term performance of three full-scale carbon and biological nutrient removal plants with anaerobic sludge digestion systems was rigorously monitored. This approach aimed to improve the understanding of process kinetics for carbon removal, nutrient removal, and anaerobic digestion. It involved COD fractionation, nitrification and denitrification kinetics, and anaerobic batch experiments. Plant-specific kinetic parameters were determined experimentally and integrated with plant-wide SUMO model simulations. The research revealed that anaerobic hydrolysis rates are significantly lower than the available literature values. The study identified this stage as a critical point in optimizing biogas production. Anaerobic digestion batch experiments and plant-wide model calibration showed that anaerobic hydrolysis rate is the critical parameter for biogas production. In parallel, anaerobic digestion performance and modeling studies in full-scale plants showed low biogas production efficiency. The innovative use of plant-wide model calibration, in conjuction with anaerobic digestion tests in the study, illuminated the significant challenges posed by low anaerobic hydrolysis rates for efficient biogas production. This was demonstrated by the poor performance and low biogas yields in full-scale plants. The study also discovered that the degradation rate of primary sludge through anaerobic hydrolysis is significantly higher compared to the hydrolysis rate of biological sludge, shedding light on areas for process improvement. In the second stage of the study, the effect of anaerobic hydrolysis rate on biogas production was investigated with mesophilic digesters in seven large-scale wastewater treatment plants. This phase was critical in understanding how the process parameters underpinning anaerobic digestion could be optimized to enhance biogas production.