Dry anaerobic digestion modelling: Parameter sensitivity

Abstract

A model dedicated to dry anaerobic digestion process was previously developed. This model was based on the ADM1 model and modified to take into account the specificity of dry anaerobic media. The objective of the work presented here was to study the sensitivity to the model of 2 parameters. The first parameter (k L a) was related to mass transfer of the biodegradation products (CH 4 , CO 2 , H 2 ) from liquid phase to gas phase. Two gas production behaviours were pointed out, depending on k L a value and corresponding to limiting or non-limiting transfer rate. A k L a value of 5 d À1 marked the transition. The second parameter (k m X) was linked to biological kinetic reactions. The sensitivity of k m X was important: a variation of AE10 % of its value affected clearly the kinetic consumption of the substrate. A method to determine those parameters was presented. This method was then used to determine both biological kinetic parameter and mass transfer coefficient from batch experimental data of methane production with acetate as organic substrate at two different moisture contents.

Sensitivity Analysis and Anaerobic Digestion Modeling: A Scoping Review

“…There was a high degree of precision in the regression model fitted to the experimental data, indicating that small reactors were as sensitive to changes in loading, retention time, and temperature as full-scale digesters. Benbelkacem et al [47] performed a sensitivity analysis on ADM1 to investigate how biogas production was affected by K L a and K m X. Atallah et al [51] conducted an LSA on ADM1 based on the two sets of digester data to optimize parameters based on five performance indicators: methane generation, pH, acetate, total COD, and ammonia. It was concluded that at one end of the simulated range, some parameters are highly sensitive.…”

“…ADM1 and single-component feedstock digestion model with substrate inhibition model parameters on the feedstock variation (22 parameters) [45] Structured model for high-solids AD the practical identifiability of 35 structural/biochemical parameters and 32 initial conditions [60] ADM1 model outputs on key model parameters [43] BSM2 model outputs on key model parameters [54] Economic study different factors including the sensitivity of profitability of the process (IRR) to model's economic parameters [57] Simplified AD bioprocess state variables of the bioprocess to the dilution rate, and the influent substrate concentration [42] ADM1 methane concentration to the key model parameter (16 parameters) [46] Experiment-based model digester performance indicators to the operating conditions [59] ADM1 model outputs to the mass transfer coefficient (k L a) and the maximum substrate consumption rate (k m X) [47] ADM1 to calculate sensitivity functions for the dynamic simulations [48] ADM1 studying the influent waste composition and model parameters to estimate how the predicted biogas production [49] ADM1 model outputs to the kinetic parameters Anaerobic batch system biogas production and pH to key model parameter [62] ADM1 to define the most sensitive ADM1 parameters to be calibrated using data from BMP tests. [52] BSM influent variations to generate dynamic wastewater treatment plant (WWTP) influent disturbance scenarios [58] BSM2 to provide a parameter sensitivity ranking and predict key plant performance criteria, including methane production and effluent water quality index [39] BSM2 model outputs to key model parameter (68 parameters) [40] ADM1 model outputs to 17 kinetic and stoichiometric parameters [53] 1-D reactor model with 6 parabolic partial differential equations model variables (W-waste, B-biomass, VFA, CH 4 ) to key model parameters (eleven parameter values within the ±50% range) [41] A mathematical AD model methane production to the key model parameter (seven parameters) [64] A mathematical AD model the sensitivity of methane production and degree of volatile solids degradation to the key model parameter (19 parameters) [65]…”