Modelling the anaerobic digestion of solid organic waste – Substrate characterisation method for ADM1 using a combined biochemical and kinetic parameter estimation approach

Abstract

This work proposes a novel and rigorous substrate characterisation methodology to be used with ADM1 to simulate the anaerobic digestion of solid organic waste. The proposed method uses data from both direct substrate analysis and the methane production from laboratory scale anaerobic digestion experiments and involves assessment of four substrate fractionation models. The models partition the organic matter into a mixture of particulate and soluble fractions with the decision on the most suitable model being made on quality of fit between experimental and simulated data and the uncertainty of the calibrated parameters. The method was tested using samples of domestic green and food waste and using experimental data from both short batch tests and longer semi-continuous trials. The results showed that in general an increased fractionation model complexity led to better fit but with increased uncertainty. When using batch test data the most suitable model for green waste included one particulate and one soluble fraction, whereas for food waste two particulate fractions were needed. With richer semi-continuous datasets, the parameter estimation resulted in less uncertainty therefore allowing the description of the substrate with a more complex model. The resulting substrate characterisations and fractionation models obtained from batch test data, for both waste samples, were used to validate the method using semi-continuous experimental data and showed good prediction of methane production, biogas composition, total and volatile solids, ammonia and alkalinity.

ADM1 modelling of large-scale covered in-ground anaerobic reactor treating sugarcane vinasse

“…This study confirms that default ADM1 values of 10 d -1 for hydrolysis constants are high as suggested in (Lübken et al 2007, Vavilin et al 2008 degradability fd of 50% estimated is consistent with the characteristics of SV, which is composed by easily degradable organic material, mostly in the form of acetate and reducing sugars. In addition, as shown in Poggio et al (2016) khyd and fd are correlated parameters, which leads to increased uncertainty as observed in khyd. However, their correlation can offset possible adjustments between both parameters (Jensen et al 2011).…”

“…Stoichiometric and kinetic parameters were based on the work of Rosén & Jeppsson (2006). The ADM1 composite material Xc, which describes the substrate, was discarded as suggested in Poggio et al (2016), avoiding a two-step solubilisation processes; instead the substrate was described directly in terms of its carbohydrates, proteins, lipids and inerts fraction. The ash fraction was included in the loadings to predict the accumulation of the non-biodegradable fraction of the substrate in the Cigar.…”

“…In our case, the pH values of the influent stream were used (setting -values, OH -, and H + ) to remove a degree of freedom. The other degree of freedom was removed when SCAT exceeded SAN, then SAN was set to zero and vice versa to close the charge balance (Poggio et al 2016).…”

“…To date, the Anaerobic Digestion Model No. 1 (ADM1) (Batstone et al 2002) is commonly regarded as the most realistic and generic model to describe the main biochemical and physicochemical processes, and gas-liquid mass transfer in anaerobic digestion (Poggio et al 2016).…”

Biomethane Production from Anaerobic Codigestion of Palm Oil Mill Effluent with Cattle Manure: A Review

“…For the system imbalance and methane yields reduction, inappropriate choice of substrates, arrangements and working conditions are responsible. Therefore, a comprehensive scientific model for ACoD technology is required for the experimental based study and full-scale strategy and action which can forecast effects of mixing proportion of substrates, organic loading rates and appropriate system for wastewaters treatment [11]. Recently, researchers are investigating and experimenting with the ACoD method because it has greater feasibility and appropriateness for the development of biogas production and environmental sustainability [12].…”