Cellulosic waste degradation by rumen-enhanced anaerobic digestion

Anaerobic digestion of lignocellulosic material is carried out effectively in many natural microbial ecosystems including the rumen. A rumen-enhanced anaerobic sequencing batch reactor was used to investigate cellulose degradation to give analysis of overall process stoichiometry and rates of hydrolysis. The reactor achieved VFA production rates of 207-236 mg COD/L/h at a loading rate of 10 g/L/d. Overloading of the reactor resulted in elevated production of propionic acid, and on occasion, the presence of succinic acid. With improvements in mixing and solids wasting, the anaerobic sequencing batch reactor system could enable full-scale application of the process for treatment of cellulosic waste material.

Anaerobic digestion process for biogas and biomolecules production: microflora identification and characterization

The anaerobic process was efficient in organic matter removal. During the process, an interesting compound as quercetin was produced inside of reactor. Phylogenetic analysis showed the presence of phylotypes affiliated with gamma-Proteobacteria, Choroflexi, and Bacteroidetes. Archaea were represented by phylotypes belonging to the genus Methanosarcina and Methanosaeta.

Bioactive compounds through anaerobic digestion of heterotrophic microalgae residues

Several important biomolecules are available into anaerobically digested effluents that were obtained from the biodiesel production process using heterotrophically grown microalga Chlorella protothecoides. Defatted microalgae residues and crude glycerol may undergo anaerobic digestion, separately and in admixture, providing methane/hydrogen and a digestate exploitable for agriculture applications. Furthermore, industrial interesting bioactive compounds such as polyphenols provided with antioxidant activity can be obtained. Anaerobic process offers a promising chance and can be advantageously combined with algae lipid-extraction techniques in order to make it more sustainable.

Ecology, physiology and performance in high-rate anaerobic digestion

The design demands on water and sanitation engineers are rapidly changing. The global population is set to rise from 7 billion to 10 billion by 2083. Urbanisation in developing regions is increasing at such a rate that a predicted 56% of the global population will live in an urban setting by 2025. Compounding these problems, the global water and energy crises are impacting the Global North and South alike. High-rate anaerobic digestion offers a low-cost, low-energy treatment alternative to the energy intensive aerobic technologies used today. Widespread implementation however is hindered by the lack of capacity to engineer high-rate anaerobic digestion for the treatment of complex wastes such as sewage. This thesis utilises the Expanded Granular Sludge Bed bioreactor (EGSB) as a model system in which to study the ecology, physiology and performance of high-rate anaerobic digestion of complex wastes. The impacts of a range of engineered parameters including reactor geometry, wastewater type, operating temperature and organic loading rate are systematically investigated using lab-scale EGSB bioreactors. Next generation sequencing of 16S amplicons is utilised as a means of monitoring microbial ecology. Microbial community physiology is monitored by means of specific methanogenic activity testing and a range of physical and chemical methods are applied to assess reactor performance. Finally, the limit state approach is trialled as a method for testing the EGSB and is proposed as a standard method for biotechnology testing enabling improved process control at full-scale. The arising data is assessed both qualitatively and quantitatively. Lab-scale reactor design is demonstrated to significantly influence the spatial distribution of the underlying ecology and community physiology in lab-scale reactors, a vital finding for both researchers and full-scale plant operators responsible for monitoring EGSB reactors. Recurrent trends in the data indicate that hydrogenotrophic methanogenesis dominates in high-rate anaerobic digestion at both full- and lab-scale when subject to engineered or operational stresses including low-temperature and variable feeding regimes. This is of relevance for those seeking to define new directions in fundamental understanding of syntrophic and competitive relations in methanogenic communities and also to design engineers in determining operating parameters for full-scale digesters. The adoption of the limit state approach enabled identification of biological indicators providing early warning of failure under high-solids loading, a vital insight for those currently working empirically towards the development of new biotechnologies at lab-scale.

Dynamical modeling of biogas production supported by an experimental anaerobic digestion process

This paper presents the development of a combined experimental and numerical approach to study the anaerobic digestion of both the wastes produced in a biorefinery using yeast for biodiesel production and the wastes generated in the preceding microbial biomass production. The experimental results show that it is possible to valorise through anaerobic digestion all the tested residues. In the implementation of the numerical model for anaerobic digestion, a procedure for the identification of its parameters needs to be developed. A hybrid search Genetic Algorithm was used, followed by a direct search method. In order to test the procedure for estimation of parameters, first noise-free data was considered and a critical analysis of the results obtain so far was undertaken. As a demonstration of its application, the procedure was applied to experimental data.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

投加溶胞菌群对剩余污泥消化影响的初步研究

活性污泥法是目前世界上普遍应用的污水生物处理工艺，其在运行过程中产生大量的剩余污泥。由于剩余污泥处理费用巨大及污泥最终处置对环境具有潜在危害问题，污泥的处理和处置已经成为水处理领域关注的焦点。本文利用实验室筛选的溶胞菌群，在好氧消化的同时对污泥进行前处理，促进剩余污泥的破解与溶胞，再通过两相厌氧处理对污泥进行进一步消化，以研究投加溶胞菌对剩余污泥消化的影响。 本研究中溶胞菌污泥减量化技术分为两个部分，第一，污泥在溶胞菌作用下的好氧消化与污泥传统好氧消化的对比研究，利用取自成都三瓦窑污水处理厂剩余污泥，向好氧污泥消化反应器中投加溶胞菌，检测各项污泥指标，并通过同传统好氧污泥消化对比，以研究溶胞菌对污泥好氧消化的影响。第二， 经过溶胞菌处理后好氧消化的剩余污泥进行两相厌氧处理研究。通过建立好氧溶胞联合两相厌氧消化系统的来处理剩余污泥，并与相同条件运行的两相厌氧消化系统做对比，检测运行过程中系统中物质成分变化，研究了其处理能力和运行稳定性，探索了两相厌氧消化系统中的发酵类型差别，验证了好氧溶胞对剩余污泥的破解效果。 研究结果表明：污泥在溶胞菌作用下的好氧消化效果和消化效率均优于传统好氧消化。在溶胞菌群存在的情况下，剩余污泥的TSS和VSS去除率达到40%和53%，远高于传统好氧消化的12%和20%。污泥经过溶胞及好氧消化后，TCOD去除率达到54.4%。经过溶胞菌处理后的剩余污泥再进入两相厌氧处理系统，进入厌氧处理系统的剩余污泥的VSS／TSS比值约为0.62。在两相厌氧处理水力停留时间(HRT)为8d时，溶胞处理污泥厌氧消化后VSS去除率达到55.17%，对照组两相厌氧系统的VSS去除率平均值为18.53%。经过溶胞处理的两相厌氧系统的污泥减量了能力远高于对照组。两相厌氧系统的pH值和碱度说明系统运行较为稳定。产酸相的有机酸中乙酸含量高于丙酸和丁酸，说明发酵末端产物以乙酸为主。在20天的试验周期内，污泥溶胞处理后、两相厌氧系统产甲烷相产气量累积产气量为1.2L，对照组只有375ml。气体中甲烷含量都在55%左右。该研究结果表明，好氧溶胞对污泥有破解能力，溶胞处理对两相厌氧中产酸相水解污泥细胞有明显的促进作用，提高了产酸相的水解酸化能力和效率。该研究对于利用生物溶胞途径提高污泥消化效率具有重要意义。 The actived sludge process has been used more and more extensively, but the procedure will lead to a large quantity of excess sludge. The treatment of Excess activated sludge has becomes a focuses not only for it is a seriously negative effect on environment but also for the costly disposal comes subsequently. The cell lysing bacterium was keeped in our lab to joined in the digestion of the excess activated sludge which was carrying at the same time with pre-processing of sludge to investigated the influence of cell lysing bacterium on excess sludge. There are two part in the method of cell lysing bacterium digesting sludge technology, the first, comparison of excess sludge digestion between anaerobic Cell-lysing Pretreatment and Conventional Aerobic Process. The sludge which was collected from San Wanyao disposal plant in Chengdu was thrown into the aerobic process system with cell-lysing bacterium, then, the indexes were detected to compare the difference between the cell-lysing bacterium in aerobic process and the traditional method to determine the influence of cell-lysing bacterium on aerobic process ; The second, the research on the sludge which was pro-treated with cell-lysing and aerobic digestion in the diphase of anaerobic digestion system. The system of cell-lysing combined with diphase of anaerobic digesting was created to compare to the diphase of anaerobic digested system, the changes of mass constituent was detected to study the ability and steady of disposal. Moreover, the research explored the difference among the types of fermentation. The efficacious of aerobic process was been proved. The result shows that the digesting rate of aerobic process with cell-lysing bacterium was higher than the traditional process. The ratio of sludge is reach to 40%~53%, which was far more effectively than the traditional process rate of 12%~20%. The TCOD of sludge which was treated with cell lysing bacterium and Aerobic Process is reach to 54.4%. Then, the sludge was thrown into the diphase of anaerobic digesting system. VSS／TSS of sludge is 0.62, HRT is 6d, the reduction of VSS is reach to 40.8%. The pH and alkalinity indicate the steady running of the diphase anaerobic digest system. In the acerbity phasing, the content of acetic acid was more than butanoic acid and propanoic acid in organic acid, it is demonstrated that the main composition of final production of fermentation was Acetic Acid. During the 20d of experiment, methylhydride phasing of diphase anaerobic digest system produced 1.2L methylhydride, however, there is only 375ml in CK, the content of methylhydride in all gas phase was around the rate of 55%. The average ratio of VSS was 18.53% in CK diphase anaerobic digest system which was far more unavailable than the mass sludge rate of 55.17%. Results demonstrated that aerobic cell-lysing digested the sludge, the treat of cell-lysing could obviously promoted the hydrolyzeing of sludge cell in the acerbity phasing, which improved the ability and rate of hydrolization and acidification. This study is significant in inhenceing the rate of sludge digestion in the method of cell-lysing bacterium.

Thermodynamic efficiency of carbon capture and utilisation in anaerobic batch digestion process

Carbon capture and storage (CCS) in the oil and water industries is becoming common and a significant consumer of energy typically requiring 150–450 °C and or several hundred bar pressure [1] particularly in geological deposition. A biological carbon capture and conversion has been considered in conventional anaerobic digestion processes. The process has been utilised in biological mixed culture, where acetoclastic bacteria and hydrogenophilic methanogens play a major key role in the utilisation of carbon dioxide. However, the bio catalytic microorganisms, hydrogenophilic methanogens are reported to be unstable with acetoclastic bacteria. In this work the biochemical thermodynamic efficiency was investigated for the stabilisation of the microbial process in carbon capture and utilisation. The authors observed that a thermodynamic efficiency of biological carbon capture and utilisation (BCCU) had 32% of overall reduction in yield of carbon dioxide with complimentary increase of 30% in yield of methane, while the process was overall endothermic. Total consumption of energy (≈0.33 MJ l−1) was estimated for the carbonate solubility (0.1 mol l−1) in batched BCCU. This has a major influence on microbial composition in the bioreactor. This thermodynamic study is an essential tool to aid the understanding of the interactions between operating parameters and the mixed microbial culture.

Anaerobic retting of banana and arecanut wastes in a plug flow digester for recovery of fiber, biogas and compost

Leaves and leaf sheath of banana and areca husk (Areca catechu) constitute an important component of urban solid waste (USW) in India which are difficult to degrade under normal windrow composting conditions. A successful method of anaerobic digestion built around the fermentation properties of these feedstock has been evolved which uses no moving parts, pretreatment or energy input while enabling recovery of four products: fiber, biogas, compost and pest repellent. An SRT of 27 d and 35 d was found to be optimum for fiber recovery for banana leaf and areca husk, respectively. Banana leaf showed a degradation pattern different from other leaves with slow pectin-1 degradation (80%) and 40% lignin removal in 27 d SRT. Areca husk however, showed a degradation pattern similar to other plant biomass. Mass recovery levels for banana leaf were fiber-20%, biogas-70% (400 ml/g TS) and compost-10%. For areca husk recovery was fiber-50%, biogas-45% (250 ml/g TS) and compost-5%. (C) 2012 Elsevier Inc. All rights reserved.

State Estimation for Anaerobic Digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.