Tito Gehring

Biogas from grass silage – Measurements and modeling with ADM1

Mono fermentation of grass silage without the addition of manure was performed over a period of 345days under mesophilic conditions (38 degrees C). A simulation study based on the IWA Anaerobic Digestion Model No. 1 (ADM1) was done in order to show its applicability to lignocellulosic biomass. Therefore, the influent was fractioned by established fodder analysis (Weender analysis and van Soest method). ADM1 was modified with a separate compound of inert decay products similar to the approach of Activated Sludge Model No. 1 (ASM1). Furthermore, a function, which described the influence of solids on the process of hydrolysis, has been integrated to reproduce reliable ammonium concentrations. The model was calibrated by using the modified Nash-Sutcliffe coefficient to evaluate simulation quality. It was possible to fit observed data by changing only hydrogen inhibition constants and the maximum acetate uptake rate. The extended ADM1 model showed good agreement with measurements and was suitable for modeling anaerobic digestion of grass silage.

Monofermentation of grass silage under mesophilic conditions: Measurements and mathematical modeling with ADM 1

In this paper experimental data from grass fermentation and simulation results with the Anaerobic Digestion Model (ADM) No. 1 are described. Two laboratory reactors were operated under mesophilic conditions with volumetric loading rates in between 0.3 and 2.5 kg(VS)/(m(3) x d). Two different kinds of grass silage were used as substrates, resulting in an average specific biogas production of 600 L/kg(VS). The ADM 1 was calibrated both manually and with the help of a Genetic Algorithm in Matlab/Simulink. Results from calibration indicate that the NH3 inhibition constant used to model the inhibition of acetate uptake is three to five times higher compared with digested activated sludge. The hydrogen inhibition constants applied for propionate and valerate/butyrate uptake are around two orders of magnitude lower than for sludge digestion.

Microbiological fermentation of lignocellulosic biomass: current state and prospects of mathematical modeling

The anaerobic fermentation process has achieved growing importance in practice in recent years. Anaerobic fermentation is especially valuable because its end product is methane, a renewable energy source. While the use of renewable energy sources has accelerated substantially in recent years, their potential has not yet been sufficiently exploited. This is especially true for biogas technology. Biogas is created in a multistage process in which different microorganisms use the energy stored in carbohydrates, fats, and proteins for their metabolism. In order to produce biogas, any organic substrate that is microbiologically accessible can be used. The microbiological process in itself is extremely complex and still requires substantial research in order to be fully understood. Technical facilities for the production of biogas are thus generally scaled in a purely empirical manner. The efficiency of the process, therefore, corresponds to the optimum only in the rarest cases. An optimal production of biogas, as well as a stable plant operation requires detailed knowledge of the biochemical processes in the fermenter. The use of mathematical models can help to achieve the necessary deeper understanding of the process. This paper reviews both the history of model development and current state of the art in modeling anaerobic digestion processes.

Determination of Methanogenic Pathways through Carbon Isotope (δ13C) Analysis for the Two-Stage Anaerobic Digestion of High-Solids Substrates

This study used carbon isotope (δ(13)C)-based calculations to quantify the specific methanogenic pathways in a two-stage experimental biogas plant composed of three thermophilic leach bed reactors (51-56 °C) followed by a mesophilic (36.5 °C) anaerobic filter. Despite the continuous dominance of the acetoclastic Methanosaeta in the anaerobic filter, the methane (CH4) fraction derived from carbon dioxide reduction (CO2), fmc, varied significantly over the investigation period of 200 days. At organic loading rates (OLRs) below 6.0 gCOD L(-1) d(-1), the average fmc value was 33%, whereas at higher OLRs, with a maximum level of 17.0 gCOD L(-1) d(-1), the fmc values reached 47%. The experiments allowed for a clear differentiation of the isotope fractionation related to the formation and consumption of acetate in both stages of the plant. Our data indicate constant carbon isotope fractionation for acetate formation at different OLRs within the thermophilic leach bed reactors as well as a negligible contribution of homoacetogenesis. These results present the first quantification of methanogenic pathway (fmc values) dynamics for a continually operated mesophilic bioreactor and highlight the enormous potential of δ(13)C analysis for a more comprehensive understanding of the anaerobic degradation processes in CH4-producing biogas plants.

Influent Fractionation for Modeling Continuous Anaerobic Digestion Processes.

The first dynamic model developed to describe anaerobic digestion processes dates back to 1969. Since then, considerable improvements in identifying the underlying biochemical processes and associated microorganisms have been achieved. These have led to an increasing complexity of both model structure and the standard set of stoichiometric and kinetic parameters. Literature has always paid attention to kinetic parameter estimation, as this determines model accuracy with respect to predicting the dynamic behavior of biogas systems. As sufficient computing power is easily available nowadays, sophisticated linear and nonlinear parameter estimation techniques are applied to evaluate parameter uncertainty. However, the uncertainty of influent fractionation in these parameter optimization procedures is generally neglected. As anaerobic digestion systems are currently increasingly used to convert a broad variety of organic biomass to methane, the lack of generally accepted guidelines for input characterization adapted to the simulation models characteristics is a considerable limitation of model application to these substrates. Directly after the introduction of the standardized Anaerobic Digestion Model No. 1 (ADM1), several publications pointed out that the models requirement of a detailed influent characterization can hardly be fulfilled. The main shortcoming of the model application was addressed in the reliable and practical identification of the models input state variables for particulate and soluble carbohydrates, proteins and lipids, as well as for the inerts. Several authors derived biomass characterization procedures, most of them dedicated to a particular substrate, and some of them being of general nature, but none of these approaches have resulted in a practical standard protocol so far. This review provides an overview of existing approaches that improve substrate influent characterization to be used for state of the art anaerobic digestion models.

Modeling of Biological Systems in Wastewater Treatment

Sanitary engineering is an extremely complex field of work. Practical experience and understanding of basic principles of engineering sciences, biology, hydrology, and computer science, as well as of social science and economics are necessary to deal with water issues in an efficient and sustainable manner. Sanitary engineering covers the specific fields of drinking water, water supply, sewage disposal, waste water treatment and river water quality. In many cases, there are overlaps and intersections between individual areas of expertise. With following pages we are giving an introduction for mathematical modeling of biochemical processes for wastewater treatment. After a step by step introduction in modeling principles, procedures and results for different systems like activated sludge, wetlands, waste stabilization ponds and anaerobic systems are given.