Exponential model describing methane production kinetics in batch anaerobic digestion: a tool for evaluation of biochemical methane potential assays

Abstract

Biochemical methane potential assays, usually run in batch mode, are performed by numerous laboratories to characterize the anaerobic degradability of biogas substrates such as energy crops, agricultural residues, and organic wastes. Unfortunately, the data obtained from these assays lacks common, universal bases for comparison, because standard protocols did not diffuse to the entire scientific community. Results are usually provided as final values of the methane yields of substrates. However, methane production curves generated in these assays also provide useful information about substrate degradation kinetics, which is rarely exploited. A basic understanding of the kinetics of the biogas process may be a first step towards a convergence of the assay methodologies on an international level. Following this assumption, a modeling toolbox containing an exponential model adjusted with a simple data-fitting method has been developed. This model should allow (a) quality control of the assays according to the goodness of fit of the model onto data series generated from the digestion of standard substrates, (b) interpretation of substrate degradation kinetics, and (c) estimate of the ultimate methane yield at infinite time. The exponential model is based on two assumptions: (a) the biogas process is a two-step reaction yielding VFA as intermediate products, and methane as the final product, and (b) the digestible substrate can be divided into a rapidly degradable and a slowly degradable fraction.

Changing Feeding Regimes To Demonstrate Flexible Biogas Production: Effects on Process Performance, Microbial Community Structure, and Methanogenesis Pathways

“…This means that for substrate containing both slowly and rapidly degradable fractions, there was a high probability that the slowly degradable fraction of the substrate would be partially removed before degradation was completed in the reactor fed every 2 h, whereas the slowly degradable fraction had more time before it was taken out of the reactors fed daily and every second day, which could give a considerable time for the substrate to be degraded further. This is a possible explanation based on the fact that the chemical compositions of particulate substrates, such as DDGS, maize silage, and other solid agricultural waste materials, are generally heterogeneous and such substrates contain rapidly degradable as well as slowly degradable fractions (28)(29)(30). Nevertheless, further work is needed to determine the rate of hydrolysis of DDGS in batch reactors and the composition of rapidly and slowly degradable fractions.…”

Impact of trace element additives on anaerobic digestion of sewage sludge with in-situ carbon dioxide sequestration

“…First-order reaction kinetics were assumed [22,24,41] for fitting the methane production rate curves ( Figure 2B) because sewage sludge is a heterogeneous substrate. Methane production volume data fitted appropriately into a simple exponential equation (R 2 > 0.88 for all conditions).…”

“…With two response variables (content and volume) that are dependent on the same inputs (olivine dosage, trace elements dosage and digestion time), a multi-objective optimization (MO) was performed to find the maximum content and volume using Matlab® version 7.4.0 (R2015b) Optimization Toolbox [23]. The model equations and boundary conditions produce the Pareto front.…”

“…The synergistic effect of olivine and trace element addition was determined by evaluating a combination of these factors to achieve a highly efficient and sustainable treatment process. First-order reaction kinetics are often used to describe complex biological reactions in batch AD systems [22][23][24] while response surface methodology (RSM) has been applied for evaluation and optimization of multiple variables affecting the studied parameters. Previous studies have applied RSM for optimization of parameters during various types co-digestion [23,[25][26][27].…”

Introducing Temperature as Variable Parameter into Kinetic Models for Anaerobic Fermentation of Coffee Husk, Pulp and Mucilage

“…Models describing the kinetics of batch anaerobic digestion have been reviewed by researchers dealing with animal nutrition, biogas and landfill gas production [30]. In bio-methane potential (BMP) assays, biogas production is influenced mainly by the substrate degradation rate, as well as by the growth of microorganism populations, subsequently showing a lag-, growth-and asymptotic phase [31].…”