Anaerobic digestion has great potential as an energy source. Not only does it provide an effective method for waste mitigation, but it has the potential to generate significant quantities of fuel and electricity. In order to ensure efficient digestion and biomass utilization, however, the system must be continuously maintained at elevated temperatures. It is technically feasible to supplement such a system with outside energy, but it is more cost effective to heat the system using only the produced biogas. While there is considerable literature covering the theory of anaerobic digestion, there are very few practical studies to show how heat utilization affects system operation. This study considers the effect of major design variables (i.e. heat exchanger efficiencies and biogas conditioning) on promoting a completely self-sustaining digestion system. The thesis considers a real world system and analyzes how it can be improved to avoid the need of an external energy source.

The Western Dairy Center at Utah State University had recognized through traiing of cheesemaking that a challenge that can exist for farmstead and artisan cheese manufacturing operations is disposal or utilization of the whey that is produced when milk is converted into cheese. Land application of whey is limited and can cause odor problems which would be detrimental to a cheesemaking operation located at the rual-urban interface. The project provided information in support of a research grant from the Western Sustainable Agribulture Research and Education program that was investigating economics and feasiblity of using anaerobic digestion for treatment of whey and cow manure mixtures. We performed initial trials to determine the level of whey that could be mixed with manure and have satisfactory operation of the digester to produce methane and a biomass. A continuous digester was used to produce biomass material for microbiological and physical testing for its suitability for use as a renewable potting mix or soil conditioner. The benefits from this research are that we have shown how a value-added product can be made by converting whey and manure into a deodorized biomass that could replace the use of peat moss, which is a non-renewable resource. This can improve the economics of using a bioreactor for whey disposal.

As production of ethanol climbs, nonood feedstocks need to be utilized such as lignocellulosic biomass. The sugars present in bio-oil produced by fast pyrolysis can potentially be fermented by microbial organisms to produce cellulosic ethanol. This study shows the potential for microbial digestion of the aqueous fraction of bio-oil in an enrichment medium to consume glucose and produce ethanol. In addition to glucose, inhibitors such as furans and phenols are present in the bio-oil. A pure glucose enrichment medium of 20 g/L was used as a standard to compare with glucose and aqueous fraction mixtures for digestion. 30% by volume of aqueous fraction in media was the most that could be consumed and yielded 0.4 g of ethanol per g of glucose. Inhibitor removal tests by extraction, activated carbon, air stripping, and microbial means were also mildly successful. Ethanol could potentially be produced for $14 per gallon using these methods.

There is growing interest in the use of high performance anaerobic digestion (AD) processes for the production of biogas at wastewater treatment facilities to offset the energy demands associated with wastewater treatment. Recuperative thickening (RT) is a promising technique which involves recycling a portion of the digested solids back to the incoming feed. In general there exists a significant number of knowledge gaps in the field of RT because the studies that have been conducted to date have almost exclusively occurred in pilot or full scale trials; this approach greatly limits the amount of process optimization that can be done in a given trial. In this work, a detailed and comprehensive study of RT processes was conducted at the lab scale; a demonstration of the optimization of polymer assisted dewatering is given and biogas production and quality monitored. Two custom designed digesters (capacity = 1.5 L) were operated in parallel with one acting as a ‘control’ digester and the other operating under a semi-batch RT mode; both digesters were also operated in parallel under RT with alternative polymer flocculants. There were no significant changes in the overall biogas methane composition; however the RT digester had an average biogas productivity over two times higher than the control one. It was found that the recycling of the polymer flocculant back into the RT digester resulted in a significant improvement in dewatering performance. At the highest polymer concentration tested, all polymer flocculants demonstrated equivalent dewatering performance achieving over 6 times lower CST’s than the control; at lower polymer concentrations the 4516 polymer flocculant had superior dewatering performance. Thus, there exists an opportunity to decrease the overall consumption of polymer flocculants through judicious selection of the flocculant and the dose that is used both for the thickening and end-stage dewatering processes in RT digesters. / Thesis / Master of Applied Science (MASc) / In wastewater treatment (WWT), solid wastes are treated using a technique called anaerobic digestion (AD) which involves the conversion of solids in biogas by anaerobic bacteria. Biogas is a mixture of mostly methane and carbon dioxide and can be used as a fuel source for energy production. There’s growing interest in the use of high performance AD processes for the production of biogas at WWT facilities to offset the energy demands associated with WWT. Recuperative thickening (RT) is a promising technique which involves recycling a portion of the digested solids back to the digester. In this work, a detailed and comprehensive study of RT processes was conducted at the lab scale; a demonstration of the optimization of polymer assisted dewatering is given and biogas production and quality monitored. Two 1.5 L custom designed digesters were operated in parallel one as a ‘control’ and the other operating under a semi-batch RT.

A Thesis Submitted to the School of Graduate Studies in Partial Fulfilment of the Requirements for the Degree of Master of Science. / Onsite wastewater treatment systems may be improved by altering the design and environmental variables that affect microbial community composition. However, the two most common methods of examining microbial composition through metagenomic sequencing (16S and shotgun sequencing) produce different taxonomic identification results according to microbial community composition and the analytical methods in use. To identify discrepancies between these two sequencing methods, we analyzed the effect of environmental and tank design variables on onsite-wastewater treatment system microbial communities sequenced using both 16S and shotgun sequencing. Shotgun and 16S sequencing produced different results when examining genera-level taxonomic richness, quantifying the effect of system design and environmental variables on community similarity, and identifying differentially abundant taxa between system types. Results were consistent when subjectively examining patterns of community similarity and when examining genera-level taxonomic diversity above 0.1% relative abundance. Identifying methods that produce similar results between 16S and shotgun sequencing supports the reliable analysis of and optimization of OWTS processes. / Thesis / Master of Science (MSc) / Onsite-wastewater treatments systems such as household septic tanks are vital tools for managing wastewater. However, the microbial ecosystem which digests waste within septic tanks contains unknown interactions that can alter the rate of waste digestion. We used two DNA sequencing methods to assess how microbial communities within septic tanks responded to the tank design and surrounding environment. We then compared results produced by the two sequencing methods. The response of microbial communities to tank design and the environment differed between the two methods. However, the two methods both indicated that one system design produced a more variable microbial community.

As societies around the world become increasingly more dependent on fossil based fuels, the need to investigate alternative fuel sources becomes more pressing. Renewable, biomass-based carbon sources obtained from the biosphere can be gasified to produce synthesis gas, which can in turn be fermented to produce fuel-grade ethanol. A byproduct of ethanol production via fermentation is acetic acid. An optimized ethanol fermentation process should produce a wastewater stream containing less than 2 g/L of acetic acid. This is not enough acid to justify recovery of the acid; however it is a high enough concentration that treatment of the stream is required before it can be discharged. The purpose of this research was to convert the acetic acid into biogas, producing a twoold result: removal of the acid from the wastewater stream and the production of methane, which is a valuable source of energy. Microorganisms known as methanogens will consume acetic acid to produce methane and carbon dioxide under anaerobic conditions. The goal of this research was to optimize methane production from the wastewater stream discharged from an ethanol to syngas facility. Sludge containing methanogenic organisms was obtained from the anaerobic digester of a wastewater treatment facility and used as inoculum in batch reactors containing a synthetic acetic acid solution. Variables such as the type and amount of supplied nutrients, acid concentration, pH, cell acclimation, oxygen exposure, headspace gas composition, and agitation rate were examined. The effects of these parameters on the amount of biogas produced and acetic acid degraded were used to evaluate and optimize reactor performance. Additional experimentation further evaluating methanogenesis at low pH was also conducted using a laboratory scale semi-continuous fermentor. Finally, advanced analytical techniques were used to evaluate changes in organism population with respect to changes in reactor operational parameters. The results of this research were used to estimate kinetic parameters, develop different full-scale reactor design models, and estimate the both the cost of wastewater treatment as well as the value of the methane produced.

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The objectives of this research were to: 1) evaluate the accuracy of the Molly cow model predictions of ruminal metabolism and nutrient digestion when simulating dairy and beef cattle diets, 2) advance representations of N recycling between blood and the gut and urinary N excretion in the model, 3) improve the representation of pH and to refit parameters related to ruminal metabolism and nutrient digestion in the model, 4) investigate how ruminal pH affects the microbial community, expression of carbohydrate-active enzyme transcripts (CAZymes), fiber degradation, and short chain fatty acid (SCFA) concentrations. To achieve the first objective, a total of 229 studies (n = 938 treatments) including dairy and beef cattle data, published from 1972 through 2016, were collected from the literature and used to assess the model accuracy and precision based on root mean squared errors (RMSE) and concordance correlation coefficients (CCC). Only slight mean and slope bias were exhibited for ruminal outflow of NDF, starch, lipid, total N, and non-ammonia N, and for fecal output of protein, NDF, lipid, and starch. However, ruminal pH was poorly simulated and contributed to problems in ruminal nutrient degradation and VFA production predictions. To achieve the second objective, representations including ruminal ammonia outflow, intestinal urea entry, microbial protein synthesis in the hindgut, and fecal urea N excretion, were added in the model. Total urea entry, gut urea entry, and urinary urea elimination rates collected from 15 published urea kinetics studies were used to derive related parameters. Significant improvements in predictions of variables describing ruminal N metabolism, blood urea metabolism and urinary N secretion were exhibited after the modifications. To achieve the third objective, a dataset assembled from the literature containing 284 peer reviewed studies with 1223 treatment means was used to derive parameter estimates for ruminal metabolism and nutrient digestions. After refitting the parameters, the model is even more robust in representing ruminal nutrient degradation compared to the initial model. Adding ammonia concentration as a driver to the pH equation increased the precision of predicted ruminal pH, and thereby, the precision of predicted VFA concentrations due to an improved representation of pH regulation of VFA production rates. To achieve the fourth objective, six cannulated Holstein heifers with an initial BW of 362 ± 22 kg (mean ± SD) were subjected to 2 treatments in a cross-over design. The treatments were 10 days of intraruminal infusions of both 1) distilled water (Control), and 2) a dilute blend of hydrochloric and phosphoric acids to achieve a pH reduction of 0.5 units (LpH). Statistical analyses indicated 19 bacterial genera and 4 protozoal genera were affected by low ruminal pH. We observed significant correlations between 54 microbes (43 bacterial and 11 protozoal genera) and 25 enzymes, of which 8 key enzymes participated in reactions leading to SCFA production, suggesting that the ruminal microbial community alters fiber catalysis and fermentation in response to altered pH through a shift in carbohydrate-active enzyme transcripts (CAZymes) expression. Overall, after the modifications and reparameterizations, 19.7 to 37.5% of RMSE with essentially no slope bias and minor mean bias were exhibited for of ruminal and fecal outflow of ADF, NDF, fat, and protein, suggesting the model is properly to represent nutrient degradation and digestion in the bovine. Considering ruminal microbes and CAZymes in predicting ruminal volatile fatty acid concentrations could explain more variance of observations. / Ph. D. / The purpose of this research was to improve ruminal nutrient metabolism and nutrient digestion representations in the Molly cow model. First, the model accuracy and precision were assessed using a dataset including 229 studies (n = 938 treatments) conducted with dairy and beef cattle. The model evaluation results indicated the mechanisms encoded in the model relative to ruminal and total tract nutrient digestion are properly represented. However, ruminal pH was very poorly represented in the model with a RMSE of 4.6% and a concordance correlation coefficient (CCC) of 0.0. Although VFA concentrations had negligible mean (2.5% of MSE) and slope (6.8% of MSE) bias, the CCC was 0.28 implying that further modifications with respect to VFA production and absorption are required to improve model precision. As identified by the residual analyses, the representations of N recycling between blood and the gut were improved by considering ruminal ammonia outflow, intestinal urea entry, microbial protein synthesis in the hindgut, and fecal urea N excretion in the model. Observations of total urea entry, gut urea entry, and urinary urea elimination rates were collected from 15 published urea kinetics studies were used to derive related parameters. After the modifications, prediction errors for ruminal outflows of total N, microbial N, and non-ammonia non-microbial N were 39.5, 27.8 and 35.9% of the respective observed mean values. Prediction errors of each were approximately 10% units less than the corresponding values before model modifications and fitting due primarily to decreased slope bias. The revised model predicted ruminal ammonia and blood urea concentrations with substantially decreased overall error and reductions in slope and mean bias. After that, ammonia concentration as a driver was added to the pH equation, and a dataset assembled from the literature containing 284 peer reviewed studies with 1223 treatment means was used to derive parameter estimates for ruminal metabolism and nutrient digestions. Refitting the parameters significantly improved the accuracy and precision of the model predictions for ruminal nutrient outflow (ADF, NDF, total N, microbial N, non-ammonia N, and non-ammonia, non-microbial N), ammonia concentrations, and fecal nutrient outflow (protein, ADF, and NDF). Therefore, the improved model can be used to simulate nutrient degradation and digestion in the bovine. Although minor mean and slope bias were observed for ruminal pH and VFA concentrations, the small values for concordance correlations indicated much of the observed variation in these variables remains unexplained. To further explain variance in ruminal metabolism and understand how ruminal pH affects the microbial community, expression of carbohydrate-active enzyme transcripts (CAZymes), fiber degradation, and short chain fatty acid (SCFA) concentrations, six cannulated Holstein heifers with an initial BW of 362 ± 22 kg (mean ± SD) were subjected to 2 treatments in a cross-over design. We observed 19 bacterial genera and 4 protozoal genera were affected by low ruminal pH, and significant correlations between 54 microbes (43 bacterial and 11 protozoal genera) and 25 enzymes, of which 8 key enzymes participated in reactions leading to SCFA production. In summary, after the modifications and reparameterizations, the model is even more robust to represent nutrient degradation and digestion in bovine compared to the initial model. More variance of observations of ruminal volatile fatty acid concentrations could be explained by considering ruminal microbes and CAZymes expressions in further study.

Yes / To date, mixing design practice in anaerobic digestion has focussed on biogas production, but no adequate consideration has been given to energy efficiency. A coherent, comprehensive and generalized strategy based on computational fluid dynamics (CFD) modelling is proposed to improve mixing efficiency of a full-scale, unconfined gas-mixed digester for wastewater treatment. The model consists of an Euler-Lagrange (EL) model where biogas bubbles are modelled as the Eulerian dispersed phase, and non-Newtonian sludge as the Lagrangian continuous phase. Robustness tests show that mixing predictions are independent of bubble size. The CFD strategy comprises the assessment of different mixing geometries and a range of input gas flow rates. Quantitative results show that simple retrofitting measures are able to achieve a significant improvement in the degree of mixing with reduced mixing times, and consequently recommendations for best mixing geometry and gas flow rate are given. A generalization to a generic digester is discussed in a form that is readily usable by professionals and consultants.