Performance of a predictive model for conventional and THP treated sewage sludge anaerobic digestion: PRESENTATION ONLY

Oxtoby, S.1,2, Winter, P.1, Smith, S.R.2, 1Thames Water, 2Imperial College London


Anaerobic digestion (AD) is the preferred technology for the treatment of sewage sludge in the UK. Several interactive operational factors influence the performance of the digestion process. Consequently, optimisation of the process during normal operation is challenging and operators have few optimisation tools available to improve digester performance, in terms of biogas yield or throughput. Giacalone (2017) developed a stochastic and mechanistic model of the conventional, mesophilic AD process to predict key sewage sludge AD performance variables at steady state, based on a dynamic experimental programme using large, bench-scale, autofed digesters to identify critical process indicators and interactions. The model uses inputs such as feed dry and volatile solids, digester conditions and feed composition as well as more complex elemental compositional measurements. The model is significantly less computationally complex, with a single rate equation to predict biogas yield, compared to Anaerobic Digestion Model 1 (ADM1), the most cited existing sludge AD model, which has up to 100 process parameters (Weinrich & Nells, 2015) depending on the mode of usage. Model validation at 6 full scale sewage treatment works has been completed and the predictive envelope has also been expanded and validated for the performance of advanced digestion sites including the thermal hydrolysis process (THP). Validation across four THP sites showed the biogas yield prediction explained 93% of the total variation in operational data (which was carefully tested for quality assurance) and was within a 10% margin of error. Across the conventional and advanced AD sites, the model was also able to distinguish between sites with a low and high risk of inhibitory ammonium accumulation. The model has the potential to provide a powerful tool to operations on site for the prediction of digester performance and optimisation of digester conditions.



Giacalone, S., 2017. Optimising the Process of Anaerobic Digestion through Improved Understanding of Fundamental Operational Parameters. PhD Dissertation, Department of Civil and Environmental Engineering, Imperial College London. PQDT – UK & Ireland: ProQuest Dissertations Publishing 2017.

Ozgun, H., 2019. Anaerobic Digestion Model No. 1 (ADM1) for mathematical modelling of full-scale sludge digester performance in a municipal wastewater treatment plant. Biodegradation, 30, 27-36.

Weinrich, S. & Nells, M., 2015. Critical comparison of different model structures for the applied simulation of the anaerobic digestion of agricultural energy crops. Bioresource Technology, 178, 306-312.

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