Critical assessment and optimisation of sewage sludge mesophilic anaerobic digestion processes at operational wastewater treatment plant

Abstract

Anaerobic digestion (AD) is a long-established method for treating wastewater sludge and has been extensively researched, but there is still a lack of generic or practical modelling tools available to guide operators to optimise the process at full industrial scale. Detailed kinetic models, incorporating fundamental AD mechanisms, such as the Anaerobic Digestion Model No.1 (ADM1), are available, but are considered to be too complex as a practical tool for full-scale process management. The Water Industry collects extensive data records on operational mesophilic anaerobic digestion (MAD) process variables, but there has been no attempt to integrate this information into a comprehensive and systematic process optimisation strategy. A novel, multiple regression analysis approach was applied to operational data from 84 full-scale MAD sites (including 66 conventional, 8 thermal hydrolysis process (THP) and 10 enzymic) in five major UK Water Utility companies, demonstrating a wide range of AD performance, to construct a universal, operationally based MAD model. The model incorporated a categorical site or process type factor, and specific calibration methods were used, to account for inter-site variation. This approach to modelling the full-scale AD process explained the variation caused by local data measurement and other unrecorded factors at specific sites, and the major operational factors influencing the process were quantified based on relative changes in digester performance, using a centred predictors approach. Digestion process performance was modelled using biogas yield (BY) or electricity yield (EY) as the dependent variable, and two sub-models were also developed on volatile solids reduction (VSR) and digested sludge dewaterability. The BY of the conventional and THP MAD processes was positively correlated to the main effects of temperature and HRT, and negatively correlated to the dry solids (DS) content in feed sludge. The effect of HRT on BY also depended on the concentration of the DS feed and increasing HRT, and had a stronger effect on BY at higher DS concentrations. The EY of the enzymic MAD process also decreased with increasing DS, and increased in relation to both temperature and volatile fatty acid (VFA) feed. The magnitude of the response in EY to temperature increased at higher VFA feed concentrations. Eight MAD sites were selected for sludge sample collection on 6 sampling events, over a period of approximately one year, to examine the effects of detailed fat, protein, carbohydrate and fibre (cellulose, hemicellulose and lignin) composition on BY. However, no significant relation was detected between BY and the major organic energy constituents (such as protein and fat) in feed sludge, but the compositional derived BYc, which is based on the proportions of substrates destroyed during AD, was significantly correlated to the observed BY. The models can be applied universally to any full-scale, stable, MAD process, including THP and enzymic pretreatment, by adopting one or more calibration options, to account for site specific conditions, by using local site: (a) biogas data, (b) electricity generation, or (c) sludge composition results. The results showed that full-scale digester performance was controlled by the combined and interactive effects of multiple process parameters; therefore, it is necessary to balance all the principal operational parameters to optimise the AD performance. Furthermore, the highest BY or EY does not necessarily correspond to the optimum AD performance in terms of the maximum biogas volume or net energy output. Thus, to ensure a positive energy balance, a conventional process should only be operated in the high mesophilic range >39 oC, when the DS of the feed sludge is ≥3.0%. A greater energy surplus is obtained with increasing feed DS content, which is a major advantage of THP pretreatment. Conventional MAD processes have an average DS feed of 4.5% and there is considerable potential to modify current operational practices to improve the overall energy balance of the system. The model provides AD operators with a practical management tool to aid decision support to balance the principal operational parameters and improve the efficiency and net energy output of industrial scale sewage sludge AD.