Kinetics of propionate conversion in anaerobic continuously stirred tank reactors

Intrinsic gas production kinetics of selected intermediates in anaerobic filters for demand-orientated energy supply

As a consequence of a growing share of solar and wind power, recent research on biogas production highlighted a need for demand-orientated, flexible gas production to provide grid services and enable a decentralized stabilization of the electricity infrastructure. Two-staged anaerobic digestion is particularly suitable for shifting the methane production into times of higher demand due to the spatio-temporal separation of hydrolysis and methanogenesis. To provide a basis for predicting gas production in an anaerobic filter, kinetic parameters of gas production have been determined experimentally in this study. A new methodology is used, enabling their determination during continuous operation. An order in methane production rate could be established by comparing the half lives of methane production. The order was beginning with the fastest: acetic acid>ethanol>butyric acid>iso-butyric acid>valeric acid>propionic acid>1,2propanediol>lactic acid. However, the mixture of a natural hydrolysate from the acidification tank appeared to produce methane faster than all single components tested.

Kinetics of biogas production in Anaerobic Filters

This study investigates methane production kinetics from individual volatile fatty acids (VFA) in an Upflow Anaerobic Filter (AF). 1gCOD in the form of acetic (HAc), propionic (HPr) or butyric acid (HBu) was injected into the AF while operating at an organic loading rate (OLRCOD) of 3.5gL(-1)d(-1). A new method is introduced to separate gas production of the baseload from the product formation of VFA degradation after the injection. The lag phase, fractional rate of gas production and half-life has been determined for the methane production of the three VFAs. The half-lives were in the order HAc<HBu<HPr showing a slower gas production from the C3 acid than from the C4 acid. The results can be used for prediction models for on-demand biogas production, a vital approach that provides the transforming energy market with balancing power.

Biokinetics and bacterial communities of propionate oxidizing bacteria in phased anaerobic sludge digestion systems

Phased anaerobic digestion is a promising technology and may be a potential source of bio-energy production. Anaerobic digesters are widely used for sewage sludge stabilization and thus a better understanding of the microbial process and kinetics may allow increased volatile solids reduction and methane production through robust process operation. In this study, we analyzed the impact of phase separation and operational conditions on the bio-kinetic characteristics and communities of bacteria associated with four phased anaerobic digestion systems. In addition to significant differences between bacterial communities associated with different digester operating temperatures, our results also revealed that bacterial communities in the phased anaerobic digestion systems differed between the 1st and 2nd phase digesters and we identified strong community composition correlations with several measured physicochemical parameters. The maximum specific growth rates of propionate oxidizing bacteria (POB) in the mesophilic and thermophilic 1st phases were 11 and 23.7 mgCOD mgCOD(-1) d(-1), respectively, while those of the mesophilic and thermophilic 2nd-phase digesters were 6.7 and 18.6 mgCOD mgCOD(-1) d(-1), respectively. Hence, the biokinetic characteristics of the POB population were dependent on the digester loading. In addition, we observed that the temperature dependency factor (θ) values were higher for the less heavily loaded digesters as compared to the values obtained for the 1st-phase digesters. Our results suggested the appropriate application of two sets of POB bio-kinetic that reflect the differing growth responses as a function of propionate concentration (and/or organic loading rates). Also, modeling acetogenesis in phased anaerobic sludge digestion systems will be improved considering a population shift in separate phases. On the basis of the bio-kinetic values estimated in various digesters, high levels of propionate in the thermophilic digesters may be best explained by the establishment of POB with low affinities (high K(s)) for propionate. Achieving low levels of propionate with either thermophilic or short HRT digesters is challenging and a relatively long HRT mesophilic digester should be employed for this purpose.

In-storage psychrophilic anaerobic digestion: acclimated microbial kinetics

In-storage psychrophilic anaerobic digestion develops by microbial acclimation in covered swine-manure storage tanks, producing CH4 and stabilizing organic matter. To optimize the system's performance, the process kinetics must be understood. The objective of this study was to evaluate kinetic parameters describing the major stages in the digestion process, and to investigate the effect of temperature acclimation on these parameters. Specific activity tests were performed using manure inocula and five substrates at three incubation temperatures. Extant substrate activities were determined analytically for each case, and intrinsic kinetic parameters for glucose uptake were estimated by grid search fitting to the Monod model. The results demonstrate that this acclimated microbial community exhibits different kinetic parameters to those of the mesophilic communities currently modelled in the literature, with increased activity at low temperatures, varying with substrate and temperature. For glucose, the higher uptake is accompanied by lower microbial yield and half-saturation constant. Decomposing these values suggests that active psychrophilic and mesophilic microbial populations co-exist within the community. This work also confirms that a new method of assessing microbial substrate kinetics must be developed for manure microbial communities, separating microbial mass from other suspended organics.

An explicit solution for progress curve analysis in systems characterized by endogenous substrate production

The Lambert W function was used to explicitly relate substrate concentration S, to time t, and the kinetic parameters V (m), K (m), and R in the modified Michaelis-Menten equation that accounts for endogenous substrate production. The applicability of this explicit formulation for kinetic parameter estimation by progress curve analysis was demonstrated using a combination of synthetic and experimental substrate depletion data. Synthetic substrate depletion data were generated using S (0) values of 1, 2, and 3 μM and V (m), K (m), and R values of 1.0 μM h(-1), 1.0 μM, and 0.1 μM h(-1), respectively, and contained 5% normally distributed error. Experimental data were obtained from two previously published studies on hydrogen depletion in four experimental systems. In all instances, experimental data were well described by the explicit solution presented in this study. Differential equation solution and iterative S estimation are eliminated with the explicit solution approach, thereby simplifying progress curve analysis in systems characterized by endogenous substrate production.

Accurate kinetic parameter estimation during progress curve analysis of systems with endogenous substrate production

We have identified an error in the published integral form of the modified Michaelis-Menten equation that accounts for endogenous substrate production. The correct solution is presented and the error in both the substrate concentration, S, and the kinetic parameters Vm , Km , and R resulting from the incorrect solution was characterized. The incorrect integral form resulted in substrate concentration errors as high as 50% resulting in 7-50% error in kinetic parameter estimates. To better reflect experimental scenarios, noise containing substrate depletion data were analyzed by both the incorrect and correct integral equations. While both equations resulted in identical fits to substrate depletion data, the final estimates of Vm , Km , and R were different and Km and R estimates from the incorrect integral equation deviated substantially from the actual values. Another observation was that at R = 0, the incorrect integral equation reduced to the correct form of the Michaelis-Menten equation. We believe this combination of excellent fits to experimental data, albeit with incorrect kinetic parameter estimates, and the reduction to the Michaelis-Menten equation at R = 0 is primarily responsible for the incorrectness to go unnoticed. However, the resulting error in kinetic parameter estimates will lead to incorrect biological interpretation and we urge the use of the correct integral form presented in this study.