Observability and Identifiability Analyses of Process Models for Agricultural Anaerobic Digestion Plants

Dynamic operation of anaerobic digestion plants requires advanced process monitoring and control. Different simplifications of the Anaerobic Digestion Model No. 1 (ADM1) have been proposed recently, which appear promising for model-based process automation and state estimation. As a fundamental requirement, observability and identifiability of these models are analyzed in this work, which was pursued through algebraic and geometric analysis. Manual algebraic assessment was successfull for small models such as the ADM1-R4 and simplified versions of the ADM1-R3, which were derived in this context. However, for larger model classes the algebraic approach showed to be insufficient. By contrast, the geometric approach, implemented in the STRIKE_GOLDD toolbox, allowed to show observability for more complex models (including ADM1-R4 and ADM1-R3), employing two independent algorithms. The present study lays the groundwork for state observer design, parameter estimation and advanced control resting upon ADM1-based models.Comment: 34 pages, 3 figures. Extended version. A shortened version was submitted to and accepted for the 24th International Conference on Process Control on April 4, 202

Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity

The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species’ metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques

Evaluation of common supermarket products as positive controls in biochemical methane potential (BMP) tests

Biochemical methane potential (BMP) tests are commonly applied to evaluate the recoverable amount of methane from a substrate. Standardized protocols require inclusion of a positive control with a known BMP to check the experimental setup and execution, as well as the performance of the inoculum. Only if the BMP of the positive control is within the expected range is the entire test validated. Besides ignorance of this requirement, limited availability of the standard positive control microcrystalline cellulose might be the main reason for neglecting a positive control. To address this limitation, eight widely available grocery store products have been tested as alternative positive controls (APC) to demonstrate their suitability. Among them, Tic Tacs and gummi bears were very promising, although they are dominated by easily degradable sugars and so do not test for hydrolytic performance. Coffee filters exhibited a similar performance to microcrystalline cellulose, while whole milk might be chosen when a more balanced carbohydrate:protein:lipid ratio is important. Overall, the approach of predicting the BMP of a substrate based on the nutritional composition provided on the product packaging worked surprisingly well: BMP of the eight tested products was 81-91% of theoretical maximum BMP based on nutritional information and generic chemical formulas for carbohydrates, proteins, and lipids

Optimizing power-to-H2 participation in the Nord Pool electricity market: effects of different bidding strategies on plant operation

The operation of power-to-X systems requires measures to control the cost and sustainability of electricity purchased from spot markets. This study investigated different bidding strategies for the dayahead market with a special focus on Sweden. A price independent order (PIO) strategy was developed assisted by forecasting electricity prices with an artificial neural network. For comparison, a price dependent order (PDO) with fixed bid price was used. The bidding strategies were used to simulate H2 production with both alkaline and proton exchange membrane electrolysers in different years and technological scenarios. Results showed that using PIO to control H2 production helped to avoid the purchase of expensive and carbon intense electricity during peak loads, but it also reduced the total number of operating hours compared to PDO. For this reason, under optimal conditions for both bidding strategies, PDO resulted in an average of 10.9% lower levelised cost of H2, and more attractive cash flows and net present values than PIO. Nevertheless, PIO showed to be a useful strategy to control costs in years with unexpected hourly price behaviour such as 2018. Furthermore, PIO could be successfully demonstrated in a practical case study to fulfil the on-demand requirement of an industrial captive customer

Power and limitations of biochemical methane potential (BMP) tests

As energy systems transition toward renewable sources, anaerobic digestion (AD), which can be used to recover energy from organic substrates, is receiving growing attention. AD research and practice both rely on biochemical methane potential (BMP) tests to determine the methane potential of sewage sludge, energy crops and organic wastes (Pearse et al., 2018). In contrast to continuous reactor experiments, BMP tests are batch, and can be conducted without a major investment of equipment, labor and time. However, this and other differences limit the applicability of results from a BMP test to full-scale plant operation. Yet even in the peer-reviewed literature, BMP test results are not always used appropriately. An example is the determination of synergistic or antagonistic effects during anaerobic co-digestion in substrate mixtures. A BMP test is a powerful and useful tool, but it is important to recognize the type of questions that can and cannot be answered with this experimental setup. Clarification of these issues is the objective of the present contribution

Impact of Storage Conditions on the Methanogenic Activity of Anaerobic Digestion Inocula

The impact of storage temperature (4, 22 and 37 ◦C) and storage time (7, 14 and 21 days) on anaerobic digestion inocula was investigated through specific methanogenic activity assays. Experimental results showed that methanogenic activity decreased over time with storage, regardless of storage temperature. However, the rate at which the methanogenic activity decreased was two and five times slower at 4 ◦C than at 22 and 37 ◦C, respectively. The inoculum stored at 4 ◦C and room temperature (22 ◦C) maintained methanogenic activity close to that of fresh inoculum for 14 days (<10% difference). However, a storage temperature of 4 ◦C is preferred because of the slower decrease in activity with lengthier storage time. From this research, it was concluded that inoculum storage time should generally be kept to a minimum, but that storage at 4 ◦C could help maintain methanogenic activity for longe

Methane emissions from the storage of liquid dairy manure: Influences of season, temperature and storage duration

Methane emissions from livestock manure are primary contributors to GHG emissions from agriculture and options for their mitigation must be found. This paper presents the results of a study on methane emissions from stored liquid dairy cow manure during summer and winter storage periods. Manure from the summer and winter season was stored under controlled conditions in barrels at ambient temperature to simulate manure storage conditions. Methane emissions from the manure samples from the winter season were measured in two time periods: 0 to 69 and 0 to 139 days. For the summer storage period, the experiments covered four time periods: from 0 to 70, 0 to 138, 0 to 209, and 0 to 279 continuous days, with probing every 10 weeks. Additionally, at the end of all storage experiments, samples were placed into eudiometer batch digesters, and their methane emissions were measured at 20 degrees C for another 60 days to investigate the potential effect of the aging of the liquid manure on its methane emissions. The experiment showed that the methane emissions from manure stored in summer were considerably higher than those from manure stored in winter. CH4 production started after approximately one month, reaching values of 0.061 kg CH4 kg(-1) Volatile Solid (VS) and achieving high total emissions of 0.148 kg CH4 kg(-1) VS (40 weeks). In winter, the highest emissions level was 0.0011 kg CH4 kg(-1) VS (20 weeks). The out comes of these experimental measurements can be used to suggest strategies for mitigating methane emissions from manure storage

Development and Validation of a Low-Cost Gas Density Method for Measuring Biochemical Methane Potential (BMP)

Accurate determination of biochemical methane potential (BMP) is important for both biogas research and practice. However, access to laboratory equipment limits the capacity of small laboratories or biogas plants to conduct reliable BMP assays, especially in low- and middle-income countries. This paper describes the development and validation of a new gas density-based method for measuring BMP (GD-BMP). In the GD-BMP method, biogas composition is determined from biogas density. Biogas density is based on bottle mass loss and biogas volume, and these can be accurately measured using only a standard laboratory scale, inexpensive syringes, and a simple manometer. Results from four experiments carried out in three different laboratories showed that the GD-BMP method is both accurate (no significant bias compared to gravimetric or volumetric methods with biogas analysis by gas chromatography) and precise (<3% relative standard deviation is possible). BMP values from the GD-BMP method were also comparable to those measured for the same substrates with an industry standard automated system (AMPTS II) in two independent laboratories (maximum difference 10%). Additionally, the GD-BMP method was shown to be accurate even in the presence of leakage by excluding leakage from mass loss measurements. The proposed GD-BMP method represents a significant breakthrough for both biogas research and the industry. With it, accurate BMP measurement is possible with only a minimal investment in supplies and equipment

Ammonia Inhibition of Anaerobic Volatile Fatty Acid Degrading Microbial Communities

Ammonia inhibition is an important reason for reactor failures and economic losses in anaerobic digestion. Its impact on acetic acid degradation is well-studied, while its effect on propionic and butyric acid degradation has received little attention and is consequently not considered in the Anaerobic Digestion Model No. 1 (ADM1). To compare ammonia inhibition of the degradation of these three volatile fatty acids (VFAs), we fed a mixture of them as sole carbon source to three continuous stirred tank reactors (CSTRs) and increased ammonium bicarbonate concentrations in the influent from 52 to 277 mM. The use of this synthetic substrate allowed for the determination of degradation efficiencies for the individual acids. While butyric acid degradation was hardly affected by the increase of ammonia concentration, propionic acid degradation turned out to be even more inhibited than acetic acid degradation with degradation efficiencies dropping to 31 and 65% for propionic and acetic acid, respectively. The inhibited reactors acclimatized and approximated pre-disturbance degradation efficiencies toward the end of the experiment, which was accompanied by strong microbial community shifts, as observed by amplicon sequencing of 16S rRNA genes and terminal restriction fragment length polymorphism (T-RFLP) of mcrA genes. The acetoclastic methanogen Methanosaeta was completely replaced by Methanosarcina. The propionic acid degrading genus Syntrophobacter was replaced by yet unknown propionic acid degraders. The butyric acid degrading genus Syntrophomonas and hydrogenotrophic Methanomicrobiaceae were hardly affected. We hypothesized that the ammonia sensitivity of the initially dominating taxa Methanosaeta and Syntrophobacter led to a stronger inhibition of the acetic and propionic acid degradation compared to butyric acid degradation and hydrogenotrophic methanogenesis, which were facilitated by the ammonia tolerant taxa Syntrophomonas and Methanomicrobiaceae. We implemented this hypothesis into a multi-taxa extension of ADM1, which was able to simulate the dynamics of both microbial community composition and VFA concentration in the experiment. It is thus plausible that the effect of ammonia on VFA degradation strongly depends on the ammonia sensitivity of the dominating taxa, for syntrophic propionate degraders as much as for acetoclastic methanogens

Determination of Microbial Maintenance in Acetogenesis and Methanogenesis by Experimental and Modeling Techniques

For biogas-producing continuous stirred tank reactors, an increase in dilution rate increases the methane production rate as long as substrate input can be converted fully. However, higher dilution rates necessitate higher specific microbial growth rates, which are assumed to have a strong impact on the apparent microbial biomass yield due to cellular maintenance. To test this, we operated two reactors at 37°C in parallel at dilution rates of 0.18 and 0.07 days-1 (hydraulic retention times of 5.5 and 14 days, doubling times of 3.9 and 9.9 days in steady state) with identical inoculum and a mixture of volatile fatty acids as sole carbon sources. We evaluated the performance of the Anaerobic Digestion Model No. 1 (ADM1), a thermodynamic black box approach (TBA), and dynamic flux balance analysis (dFBA), to describe the experimental observations. All models overestimated the impact of dilution rate on the apparent microbial biomass yield when using default parameter values. Based on our analysis, a maintenance coefficient value below 0.2 kJ per carbon mole of microbial biomass per hour should be used for the TBA, corresponding to 0.12 mmol ATP per gram dry weight per hour for dFBA, which strongly deviates from the value of 9.8 kJ Cmol h-1 that has been suggested to apply to all anaerobic microorganisms at 37°C. We hypothesized that a decrease in dilution rate might select taxa with minimized maintenance expenditure. However, no major differences in the dominating taxa between the reactors were observed based on amplicon sequencing of 16S rRNA genes and terminal restriction fragment length polymorphism analysis of mcrA genes. Surprisingly, Methanosaeta dominated over Methanosarcina even at a dilution rate of 0.18 days-1, which contradicts previous model expectations. Furthermore, only 23–49% of the bacterial reads could be assigned to known syntrophic fatty acid oxidizers, indicating that unknown members of this functional group remain to be discovered. In conclusion, microbial maintenance was found to be much lower for acetogenesis and methanogenesis than previously assumed, likely due to the exceptionally low growth rates in anaerobic digestion. This finding might also be relevant for other microbial systems operating at similarly low growth rates