Journal articles: 'ADM1'

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Groth, Dawid, Izabela Poplawska, Marlena Tynecka, Kamil Grubczak, Jordan Holl, Aleksandra Starosz, Adrian Janucik, et al. "Abdominoplasty Skin-Based Dressing for Deep Wound Treatment—Evaluation of Different Methods of Preparation on Therapeutic Potential." Pharmaceutics 13, no. 12 (December 8, 2021): 2118. http://dx.doi.org/10.3390/pharmaceutics13122118.

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The management of hard-to-heal wounds is a significant clinical challenge. Acellular dermal matrices (ADMs) have been successfully introduced to enhance the healing process. Here, we aimed to develop protocol for the preparation of novel ADMs from abdominoplasty skin. We used three different decellularization protocols for skin processing, namely, 1M NaCl and sodium dodecyl sulfate (SDS, in ADM1); 2M NaCl and sodium dodecyl sulfate (SDS, in ADM1); and a combination of recombinant trypsin and Triton X-100 (in hADM 3). We assessed the effectiveness of decellularization and ADM’s structure by using histochemical and immunochemical staining. In addition, we evaluated the therapeutic potential of novel ADMs in a murine model of wound healing. Furthermore, targeted transcriptomic profiling of genes associated with wound healing was performed. First, we found that all three proposed methods of decellularization effectively removed cellular components from abdominoplasty skin. We showed, however, significant differences in the presence of class I human leukocyte antigen (HLA class I ABC), Talin 1/2, and chondroitin sulfate proteoglycan (NG2). In addition, we found that protocols, when utilized differentially, influenced the preservation of types I, III, IV, and VII collagens. Finally, we showed that abdominoplasty skin-derived ADMs might serve as an effective and safe option for deep wound treatment. More importantly, our novel dressing (ADM1) improves the kinetics of wound closure and scar maturation in the proliferative and remodeling phases of wound healing. In conclusion, we developed a protocol for abdominoplasty skin decellularization suitable for the preparation of biological dressings. We showed that different decellularization methods affect the purity, structure, and therapeutic properties of ADMs.

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Yasui, H., K. Komatsu, R. Goel, Y. Y. Li, and T. Noike. "Evaluation of state variable interface between the Activated Sludge Models and Anaerobic Digestion Model no 1." Water Science and Technology 57, no. 6 (March 1, 2008): 901–7. http://dx.doi.org/10.2166/wst.2008.070.

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For plant wide modelling of wastewater treatment, it is necessary to develop a suitable state variables interface for integrating state of the art models of ASM and ADM1. ADM1 currently describes such an interface, however, its suitability needs to be experimentally evaluated. In this study, we characterised activated sludge under aerobic and anaerobic conditions to obtain representative state variables for both models. ASM state variables of XS, XH and XI (as obtained from aerobic tests) and ADM1 state variables of XC and XI (as obtained from anaerobic tests) were then correlated to assess the suitability of current interface. Based on the seven datasets of this study and seven datasets from literatures, it was found that in general ASM state variables were well correlated to the state variables of ADM1. The ADM1 state variable of XC could be correlated to the sum of state variables of XS and XH, while XI in both the models showed direct correspondence. It was also observed that the degradation kinetics of XC under anaerobic condition could be better described by individual degradation kinetics of XS and XH. Therefore, to establish a one to one correspondence between ASM and ADM1 state variables and better description of degradation kinetics in ADM1, replacing the composite variable of XC by the state variables of XS and XH is recommended.

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Shang, Y., B. R. Johnson, and R. Sieger. "Application of the IWA Anaerobic Digestion Model (ADM1) for simulating full-scale anaerobic sewage sludge digestion." Water Science and Technology 52, no. 1-2 (July 1, 2005): 487–92. http://dx.doi.org/10.2166/wst.2005.0557.

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A steady-state implementation of the IWA Anaerobic Digestion Model No. 1 (ADM1) has been applied to the anaerobic digesters in two wastewater treatment plants. The two plants have a wastewater treatment capacity of 76,000 and 820,000 m3/day, respectively, with approximately 12 and 205 dry metric tons sludge fed to digesters per day. The main purpose of this study is to compare the ADM1 model results with full-scale anaerobic digestion performance. For both plants, the prediction of the steady-state ADM1 implementation using the suggested physico-chemical and biochemical parameter values was able to reflect the results from the actual digester operations to a reasonable degree of accuracy on all parameters. The predicted total solids (TS) and volatile solids (VS) concentration in the digested biosolids, as well as the digester volatile solids destruction (VSD), biogas production and biogas yield are within 10% of the actual digester data. This study demonstrated that the ADM1 is a powerful tool for predicting the steady-state behaviour of anaerobic digesters treating sewage sludges. In addition, it showed that the use of a whole wastewater treatment plant simulator for fractionating the digester influent into the ADM1 input parameters was successful.

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Feng, Y., J. Behrendt, C. Wendland, and R. Otterpohl. "Parameter analysis of the IWA Anaerobic Digestion Model No. 1 for the anaerobic digestion of blackwater with kitchen refuse." Water Science and Technology 54, no. 4 (August 1, 2006): 139–47. http://dx.doi.org/10.2166/wst.2006.535.

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The IWA anaerobic digestion model No.1 (ADM1) had been successfully applied to the lab-scale mesophilic blackwater anaerobic digestion (BWAD) plant for cases of only blackwater (BW) feeding and of BW plus kitchen refuse (KR) feeding. In this paper, the simulation results of BW+KR anaerobic digestion are presented and discussed, followed by the analyses and discussion of the critical and important parameters as well as the performance of ADM1 based on these results. The raw BW can contain up to 30% short chain fatty acids (SCFA) which severely impact the performance of the model. The model proved that the disintegration/hydrolysis rate of BW is around 4.5 d−1, which is about ten times higher than that of KR (Kdis,KR=0.5 d−1). ADM1 is not sensitive to the distribution ratio among carbohydrates, proteins and lipids. For BWAD the C4 metabolism can be integrated in the uptake of LCFA. The uptake delay phenomenon was observed and cannot be simulated by ADM1, but it is tolerable. No unique KI,NH3,ac is found out for all investigated ammonia concentration ranges. Meanwhile, ADM1 is not sensitive to KLa and kp, so they can easily be set up.

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Huber, Patrick, Christophe Neyret, and Eric Fourest. "Implementation of the anaerobic digestion model (ADM1) in the PHREEQC chemistry engine." Water Science and Technology 76, no. 5 (May 26, 2017): 1090–103. http://dx.doi.org/10.2166/wst.2017.282.

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Anaerobic digestion is state-of-the-art technology to treat sludge and effluents from various industries. Modelling and optimisation of digestion operations can be advantageously performed using the anaerobic digestion model (ADM1) from the International Water Association. The ADM1, however, lacks a proper physico-chemical framework, which makes it difficult to consider wastewater of complex ionic composition and supersaturation phenomena. In this work, we present a direct implementation of the ADM1 within the PHREEQC chemistry engine. This makes it possible to handle ionic strength effects and ion-pairing. Thus, multiple mineral precipitation phenomena can be handled while resolving the ADM1. All these features can be accessed with very little programming effort, while retaining the full power and flexibility of PHREEQC. The distributed PHREEQC code can be easily interfaced with process simulation software for future plant-wide simulation of both wastewater and sludge treatment.

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Lopez-Vazquez, Carlos M., Mayank Mithaiwala, Moustafa S. Moussa, Mark C. M. van Loosdrecht, and Damir Brdjanovic. "Coupling ASM3 and ADM1 for wastewater treatment process optimisation and biogas production in a developing country: case-study Surat, India." Journal of Water, Sanitation and Hygiene for Development 3, no. 1 (March 1, 2013): 12–25. http://dx.doi.org/10.2166/washdev.2013.017.

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The overall performance of the Anjana wastewater treatment plant (WWTP) located in Surat, India, was assessed by coupling the Activated Sludge Model No. 3 (ASM3) and the Anaerobic Digestion Model No. 1 (ADM1). Guidelines developed by the Dutch Foundation for Applied Water Research (STOWA) were successfully applied for the determination of wastewater characteristics. Concerning the fractionation of primary and secondary sludge, the approach proved to be adequate for the application of ADM1. A satisfactory description of the performance of the plant was obtained in terms of effluent quality, biogas generation and sludge production. This was achieved through coupling ASM3 with ADM1 and adjusting four default values (the growth of autotrophic bacteria from 1 to 0.46 day−1, influent fraction of unbiodegradable particulate chemical oxygen demand (COD) to 0.14 gCOD/gCOD, and the anaerobic disintegration factors for soluble and particulate unbiodegradable COD in ADM1 to 0.01 and 0.29 gCOD/gCOD, respectively). The model was applied to optimise the plant performance and to assess the potential influence of the return of high strength reject effluents through the implementation of an ADM1-ASM3 interface. This study underlines the feasibility, advantages and benefits of mathematical modelling as a reliable tool for process optimisation, plant upgrade and resource recovery in developing countries.

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Rosen, C., D. Vrecko, K. V. Gernaey, M. N. Pons, and U. Jeppsson. "Implementing ADM1 for plant-wide benchmark simulations in Matlab/Simulink." Water Science and Technology 54, no. 4 (August 1, 2006): 11–19. http://dx.doi.org/10.2166/wst.2006.521.

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The IWA Anaerobic Digestion Model No.1 (ADM1) was presented in 2002 and is expected to represent the state-of-the-art model within this field in the future. Due to its complexity the implementation of the model is not a simple task and several computational aspects need to be considered, in particular if the ADM1 is to be included in dynamic simulations of plant-wide or even integrated systems. In this paper, the experiences gained from a Matlab/Simulink implementation of ADM1 into the extended COST/IWA Benchmark Simulation Model (BSM2) are presented. Aspects related to system stiffness, model interfacing with the ASM family, mass balances, acid-base equilibrium and algebraic solvers for pH and other troublesome state variables, numerical solvers and simulation time are discussed. The main conclusion is that if implemented properly, the ADM1 will also produce high-quality results in dynamic plant-wide simulations including noise, discrete sub-systems, etc. without imposing any major restrictions due to extensive computational efforts.

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Kleerebezem, R., and M. C. M. Van Loosdrecht. "Waste characterization for implementation in ADM1." Water Science and Technology 54, no. 4 (August 1, 2006): 167–74. http://dx.doi.org/10.2166/wst.2006.538.

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Wastewater characterization as required for implementation in ADM1 is based on the identification of the numerous concentrations of the specific compounds defined in ADM1. However, identification of the individual substrate concentrations requires specific analytical techniques and in most cases only general measurements like COD, TOC, and organic nitrogen are available. This paper describes a simple method for calculation of the lumped elemental composition of the organic substrates in the wastewater from a limited number of widely available analyses. Using the elemental composition of the lumped substrate and the elemental composition of the substrates defined in the model, the influent composition as required for input in ADM1 can be calculated. Furthermore, proper waste characterization allows for an initial analysis of the biogas flow rate and composition as well as the reactor pH that can be achieved upon organic substrate degradation, as will be demonstrated. It is hoped that the methods described in this paper will stimulate and simplify future application of ADM1.

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Peiris, B. R. H., P. G. Rathnasiri, J. E. Johansen, A. Kuhn, and R. Bakke. "ADM1 simulations of hydrogen production." Water Science and Technology 53, no. 8 (April 1, 2006): 129–37. http://dx.doi.org/10.2166/wst.2006.243.

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Hydrogen can be produced by fermentation of organic wastes as a renewable CO2 emission free fuel. The production potential as a function of feed composition is investigated using the ADM1 and experimental data from the literature. Lactate and ethanol are included in the model as intermediates to simulate the bio-hydrogen production processes more closely. Simulated effects of carbohydrate to protein ratio in the feed on pH, H2, biomass and fatty acid production using standard model parameters compare quite well with experimental results. The overall hydrogen and biomass production corresponds well with measurements for some feeds and less for others. The maximum theoretical yield is significantly higher than the simulated and measured values and is highest when the feed consists of only carbohydrates. The analysis suggests that the modified ADM1 is capable of simulating the main mechanisms involved in biological hydrogen production processes, implying that the model can be used to identify, and find strategies to influence limiting factors in bio-hydrogen production processes. Model weaknesses regarding the acidogenesis processes are observed and areas for further improvements discussed.

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10

Patón, Mauricio, and Jorge Rodríguez. "Integration of bioenergetics in the ADM1 and its impact on model predictions." Water Science and Technology 80, no. 2 (July 15, 2019): 339–46. http://dx.doi.org/10.2166/wst.2019.279.

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Abstract In this work, the integration of dynamic bioenergetic calculations in the IWA Anaerobic Digestion Model No. 1 (ADM1) is presented. The impact of bioenergetics on kinetics was addressed via two different approaches: a thermodynamic-based inhibition function and variable microbial growth yields based on dynamic Gibbs free energy calculations. The dynamic bioenergetic calculations indicate that the standard ADM1 predicts positive reaction rates under thermodynamically unfeasible conditions. The dissolved hydrogen inhibition approach used in ADM1 is, however, deemed as adequate, offering the trade-off of not requiring dynamic bioenergetics computation despite the need of hydrogen inhibition parameters. Simulations of the model with bioenergetics showed the low amount of energy available in butyrate and propionate oxidation, suggesting that microbial growth on these substrates must be very limited or occur via alternative mechanisms rather than dissolved hydrogen.

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Rodríguez, J., J. M. Lema, M. C. M. van Loosdrecht, and R. Kleerebezem. "Variable stoichiometry with thermodynamic control in ADM1." Water Science and Technology 54, no. 4 (August 1, 2006): 101–10. http://dx.doi.org/10.2166/wst.2006.531.

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The effect of a variable stoichiometry of the carbohydrate fermentation process in the IWA Anaerobic Digestion Model No.1 (ADM1) is investigated. Most existing anaerobic digestion models including ADM1 consider a fixed-stoichiometry for their conversion processes. The ADM1 model was first transformed into an only mol based model to remove some errors derived from the mixed COD-mol based standard model and to allow for implementation of the variable stoichiometry. Consequently, the values of the butyrate and acetate catabolic yields of carbohydrate fermentation are made dependent on the hydrogen concentration and the reactor pH according to the predictions of a recently developed mixed culture fermentation model based on thermodynamic considerations. The simulation results obtained showed no significantly different responses in terms of effluent quality and system robustness between the standard and the variable stoichiometry ADM1 under overload conditions, and for both single- and two-step anaerobic digestion configurations. This behaviour is explained by the non-limiting acetogenic activity that compensated for the changes in the acidogenic products, typical behaviour for serial processes close to equilibrium. Based on the results obtained, thermodynamic rather than kinetic control for these conversions is suggested. Depending on the objectives to be met, lumping of carbohydrate fermenters and oxidative acetogens into a single biomass group with a variable stoichiometry is proposed for further consideration.

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Morel, E., B. Tartakovsky, S. R. Guiot, and M. Perrier. "ADM1 application for tuning and performance analysis of a multi-model observer-based estimator." Water Science and Technology 54, no. 4 (August 1, 2006): 93–100. http://dx.doi.org/10.2166/wst.2006.530.

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Anaerobic digestion model no.1 (ADM1) was used for tuning and performance analysis of the multi-model observer based estimator (mmOBE). The mmOBE was based on the variable structure model (VSM) of the anaerobic digestion model, which consists of several local submodels, each of which describes a typical process state. Depending on the hydraulic retention time, ADM1 simulated the methanogenic, organic overload, and acidogenic states of the process. These simulations allowed for optimising tunable parameters of the mmOBE. Owing to relatively slow process dynamics, a data acquisition interval as large as one day was sufficient to obtain acceptable accuracy. The simulations of mmOBE performance showed excellent rate of mmOBE convergence to ADM1 outputs. Moreover, mmOBE successfully estimated key kinetic parameters, such as maximal transformation rates of CODs, VFAs, and methane. These estimations can be used in the development of the advanced knowledge-based process system, which uses both available measurements and estimations of key kinetic parameters for extended diagnosis of failures and process trend analysis.

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Freudenthal, K., J. Koglatis, R. Otterpohl, and J. Behrendt. "Prediction of sulfide formation in sewer pressure mains based on the IWA Anaerobic Digestion Model No. 1 (ADM1)." Water Science and Technology 52, no. 10-11 (November 1, 2005): 13–22. http://dx.doi.org/10.2166/wst.2005.0674.

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In this paper a new approach is presented to predict sulfide formation in sewers based on the IWA Anaerobic Digestion Model No. 1 (ADM1). Compared with existing models the ADM1 has two crucial advantages. Firstly, it simulates anaerobic digestion processes, of which sulfide formation is the final step. Secondly, it uses a more detailed description of the waste water composition. In order to obtain reliable data for calculation an experimental set-up for measuring the Oxygen Uptake Rate (OUR) is used. An implementation of sulfide formation processes into the model matrix is proposed.

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Elaiuy, Marcelo Leite Conde, Aiduan Li Borrion, Davide Poggio, Julia Anna Stegemann, and Edson Aparecido Abdul Nour. "ADM1 modelling of large-scale covered in-ground anaerobic reactor treating sugarcane vinasse." Water Science and Technology 77, no. 5 (January 11, 2018): 1397–409. http://dx.doi.org/10.2166/wst.2018.013.

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Abstract In this paper, we demonstrate in a clear procedure the application of the Anaerobic Digestion Model No. 1 (ADM1) to model a large-scale covered in-ground anaerobic reactor (Cigar), processing sugarcane vinasse from a biorefinery in Brazil. The biochemical make-up (carbohydrates, proteins, and lipids) of the substrate was analysed based on the food industry standards. Two distinct subsets of data, based on the sugarcane harvest season for bioethanol and sugar production in 2012 and 2014, were used to direct and cross validate the model, respectively. We fitted measured data by estimating two key parameters against biogas flow rate: the degradation extent (fd) and the first order hydrolysis rate coefficient (khyd). By cross validation we show that the fitted model can be generalised to represent the behaviour of the reactor under study. Therefore, motivated by practical and industrial application of ADM1, for both different reactors types and substrates, we show aspects on the implementation of ADM1 to a specific large-scale reactor for anaerobic digestion of sugarcane vinasse.

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Kleerebezem, R., and M. C. M. van Loosdrecht. "Critical analysis of some concepts proposed in ADM1." Water Science and Technology 54, no. 4 (August 1, 2006): 51–57. http://dx.doi.org/10.2166/wst.2006.525.

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The Anaerobic Digestion Model No. 1 (ADM1) has been developed by the expert task group of the IWA to establish a common platform for simulation of a wide variety of anaerobic degradation processes. It enables comparison of different methods and parameter values for description of specific sub-processes, with the methods and default values proposed by the task group. This will hopefully stimulate a more structured discussion on anaerobic digestion modelling compared to the recent past, when many different researchers developed a slightly different model and it remained largely unclear what could, and what could not be compared. In this paper we take the liberty to criticize some aspects of ADM1 and its implementation, as we think they represent concepts that are too easily extrapolated from activated sludge models. The specific subjects discussed here are the COD-based description of the reaction stoichiometry (i), the widely adopted use of a constant value for the solid retention time high-rate anaerobic bioreactors (ii), and the kinetic description of the acetogenic reactions as proposed in ADM1 (iii).

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Batstone, D. J., and J. Keller. "Industrial applications of the IWA anaerobic digestion model No. 1 (ADM1)." Water Science and Technology 47, no. 12 (June 1, 2003): 199–206. http://dx.doi.org/10.2166/wst.2003.0647.

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In this paper, the IWA anaerobic digestion model No. 1 (ADM1) is applied to two case studies from contract work on industrial treatment plants. The first was the assessment of acid addition for pH decrease and avoidance of calcium carbonate (CaCO3) precipitation in a paper mill fed UASB. The simulation work found, with a high degree of confidence, that acid dosing was neither economical for pH control, nor had any real effect on the CaCO3 levels present in the reactor. A specific calcium carbonate precipitation equation was added to the ADM1 to undertake this study. The second case study was an assessment of the benefits of thermophilic (as opposed to mesophilic operation) for reduced ammonia inhibition, improved stability and gas production in a solids digester at a gelatine production facility. Here, it was predicted that thermophilic operation could not attain either goal to a satisfactory extent. In addition to demonstrating the application of the ADM1 to the two systems, we have also assessed the predictions generated in the case studies in terms of quality and utility.

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Morales, Laura Andrea, Angel David Rodriguez, and Herbert Enrique Rojas. "Assessment of the Input Substrate Characteristics Included in the Anaerobic Digestion Model No. 1 (ADM1)." Ingeniería 22, no. 2 (May 5, 2017): 269. http://dx.doi.org/10.14483/udistrital.jour.reving.2017.2.a07.

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Context: Anaerobic Digestion (AD) is a well-established process and widely used for wastewater treatment and power generation worldwide. In engineering, the Anaerobic Digestion Model number 1 (ADM1) is the preferred tool for predicting the behavior of AD. However, this model requires a detailed characterization of the input substrate, which is often a difficult and expensive process. This paper presents an analysis of the input waste variables in the ADM1 and its effects on the biogas production, in order to identify on which variables the characterization should be centered.Method: A sensitivity analysis was performed using a simple methodology that consisted of establishing a reference case and change the value of each input concentrations one at a time leaving the other parameters equal. For this a specific range of variation was defined using the values of parameter extracted from several references. Simulations were done in MATLAB/Simulink® using a routine developed by the authors based on the ADM1 implementation proposed in the Lund University, Sweden.Results: The analysis reveals that most critical variables involved in the methane production are temperature, volumetric flow rate of substrates and the concentrations of proteins, lipids and carbohydrates. For the case analyzed, variations in concentrations of lipids and carbohydrates increase the production of methane by more than 500%.Conclusions: In the concentrations of proteins, lipids and carbohydrates should focus the characterization of waste input when the ADM1 is implemented. Also, simulations shows that the input concentrations should be carefully estimated because oversizing of these can cause erroneous results.Language: English

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Mairet, Francis, Olivier Bernard, Monique Ras, Laurent Lardon, and Jean-Philippe Steyer. "Modeling anaerobic digestion of microalgae using ADM1." Bioresource Technology 102, no. 13 (July 2011): 6823–29. http://dx.doi.org/10.1016/j.biortech.2011.04.015.

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Batstone, D. J., J. Keller, and J. P. Steyer. "A review of ADM1 extensions, applications, and analysis: 2002–2005." Water Science and Technology 54, no. 4 (August 1, 2006): 1–10. http://dx.doi.org/10.2166/wst.2006.520.

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Since publication of the Scientific and Technical Report (STR) describing the ADM1, the model has been extensively used, and analysed in both academic and practical applications. Adoption of the ADM1 in popular systems analysis tools such as the new wastewater benchmark (BSM2), and its use as a virtual industrial system can stimulate modelling of anaerobic processes by researchers and practitioners outside the core expertise of anaerobic processes. It has been used as a default structural element that allows researchers to concentrate on new extensions such as sulfate reduction, and new applications such as distributed parameter modelling of biofilms. The key limitations for anaerobic modelling originally identified in the STR were: (i) regulation of products from glucose fermentation, (ii) parameter values, and variability, and (iii) specific extensions. Parameter analysis has been widespread, and some detailed extensions have been developed (e.g., sulfate reduction). A verified extension that describes regulation of products from glucose fermentation is still limited, though there are promising fundamental approaches. This is a critical issue, given the current interest in renewable hydrogen production from carbohydrate-type waste. Critical analysis of the model has mainly focused on model structure reduction, hydrogen inhibition functions, and the default parameter set recommended in the STR. This default parameter set has largely been verified as a reasonable compromise, especially for wastewater sludge digestion. One criticism of note is that the ADM1 stoichiometry focuses on catabolism rather than anabolism. This means that inorganic carbon can be used unrealistically as a carbon source during some anabolic reactions. Advances and novel applications have also been made in the present issue, which focuses on the ADM1. These papers also explore a number of novel areas not originally envisaged in this review.

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Gaida, D., C. Wolf, C. Meyer, A. Stuhlsatz, J. Lippel, T. Bäck, M. Bongards, and S. McLoone. "State estimation for anaerobic digesters using the ADM1." Water Science and Technology 66, no. 5 (September 1, 2012): 1088–95. http://dx.doi.org/10.2166/wst.2012.286.

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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.

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Wett, B., A. Eladawy, and M. Ogurek. "Description of nitrogen incorporation and release in ADM1." Water Science and Technology 54, no. 4 (August 1, 2006): 67–76. http://dx.doi.org/10.2166/wst.2006.527.

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ADM1 represents a universally applicable biokinetic model for the mathematical description of anaerobic digestion of different types of organic substrates. Digestion of particulate composites is described as a five-stage process involving disintegration, hydrolysis, acidogenesis, acetogenesis and methanogenesis, of which the last three process steps are represented by growth kinetics of the specific degrading biomass. Decay of the produced biomass according to ADM1 is depicted by a recycle mass flux to the composite particulate substrate. Consequently two different actions are lumped into one process describing both conversion of feed substrate (depending primarily on influent characterisation) and generation of decay products (depending on digestion performance). In this presentation the introduction of a separate compound of inert decay products in analogy to ASM1 is suggested. Model calibration of separately monitored digestion of primary and secondary sludge (nitrogen content 0.030 g N/g TSS and 0.051 g N/g TSS, respectively) reveals the advantage of a clear distinction of disintegration and decay. The fate of nitrogen in the course of incorporation and release (0.016 g N/g TSS compared to 0.028 g N/g TSS) during digestion processes is comprehensible and the final ammonia concentration in the rejection water becomes predictable.

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Batstone, D. J., J. Keller, I. Angelidaki, S. V. Kalyuzhnyi, S. G. Pavlostathis, A. Rozzi, W. T. M. Sanders, H. Siegrist, and V. A. Vavilin. "The IWA Anaerobic Digestion Model No 1 (ADM1)." Water Science and Technology 45, no. 10 (May 1, 2002): 65–73. http://dx.doi.org/10.2166/wst.2002.0292.

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The IWA Anaerobic Digestion Modelling Task Group was established in 1997 at the 8th World Congress on Anaerobic Digestion (Sendai, Japan) with the goal of developing a generalised anaerobic digestion model. The structured model includes multiple steps describing biochemical as well as physico-chemical processes. The biochemical steps include disintegration from homogeneous particulates to carbohydrates, proteins and lipids; extracellular hydrolysis of these particulate substrates to sugars, amino acids, and long chain fatty acids (LCFA), respectively; acidogenesis from sugars and amino acids to volatile fatty acids (VFAs) and hydrogen; acetogenesis of LCFA and VFAs to acetate; and separate methanogenesis steps from acetate and hydrogen/CO2. The physico-chemical equations describe ion association and dissociation, and gas-liquid transfer. Implemented as a differential and algebraic equation (DAE) set, there are 26 dynamic state concentration variables, and 8 implicit algebraic variables per reactor vessel or element. Implemented as differential equations (DE) only, there are 32 dynamic concentration state variables.

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Rousseau, P., J. P. Steyer, E. I. P. Volcke, N. Bernet, and F. Béline. "Combined anaerobic digestion and biological nitrogen removal for piggery wastewater treatment: a modelling approach." Water Science and Technology 58, no. 1 (July 1, 2008): 133–41. http://dx.doi.org/10.2166/wst.2008.322.

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In order to deal with the environmental problems associated with animal production industrialization and at the same time considering energy costs increasing, a piggery wastewater treatment process consisting of combined anaerobic digestion and biological nitrogen removal by activated sludge was developed. This contribution presents a modelling framework in order to optimize this process. Modified versions of the well established ASM1 and ADM1 models have been used. The ADM1 was extended with biological denitrification. pH calculation and liquid gas-transfer were modified to take into account the effect of associated components. Finally, two interfaces (ADMtoASM and ASMtoADM) were built in order to combine both models. These interfaces set up the COD, nitrogen, alkalinity and charge fractionation between both models. However, for the mass balances between both models, some hypotheses were considered and might be evaluated.

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El-Fadel, M., R. Maroun, R. Bou Fakher Eldeen, and S. Ghanimeh. "ADM1 performance using SS-OFMSW with non-acclimated inoculums." Water Science and Technology 66, no. 9 (November 1, 2012): 1885–92. http://dx.doi.org/10.2166/wst.2012.395.

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This paper assesses the anaerobic digestion (AD) of the source-sorted organic fraction of municipal solid waste (SS-OFMSW). For this purpose, an experimental programme was implemented involving the operation and monitoring of two bench-scale anaerobic digesters, continuously fed with SS-OFMSW. The mathematical model (ADM1) was then applied to simulate the process of AD of SS-OFMSW. While start-up of the digesters was relatively slow, re-inoculation with cattle manure with effluent dilution reduced the acclimation period and achieved better stability, accommodating a feeding rate at an OLR = 2.39 kg TVS m−3 day−1. The high recorded methane gas production rate, reaching (0.1–2.5 m3 CH4/m3 reactor day), confirms the excellent biodegradability of the type of waste used (SS-OFMSW) and its suitability for AD. Satisfactory simulations of soluble chemical oxygen demand (COD), pH, and methane composition of biogas were obtained, whereas volatile fatty acid (VFA) concentrations in both reactors were over-predicted albeit capturing its general trend.

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Koch, Konrad, Manfred Lübken, Tito Gehring, Marc Wichern, and Harald Horn. "Biogas from grass silage – Measurements and modeling with ADM1." Bioresource Technology 101, no. 21 (November 2010): 8158–65. http://dx.doi.org/10.1016/j.biortech.2010.06.009.

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Yasui, H., R. Goel, Y. Y. Li, and T. Noike. "Modified ADM1 structure for modelling municipal primary sludge hydrolysis." Water Research 42, no. 1-2 (January 2008): 249–59. http://dx.doi.org/10.1016/j.watres.2007.07.004.

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Carlini, M., S. Castellucci, A. Mennuni, and S. Selli. "Poultry Manure Biomass: Energetic Characterization and ADM1-based Simulation." Journal of Physics: Conference Series 1172 (March 2019): 012063. http://dx.doi.org/10.1088/1742-6596/1172/1/012063.

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Lohani, Sunil Prasad, Shuai Wang, Susanne Lackner, Harald Horn, Sanjay Nath Khanal, and Rune Bakke. "ADM1 modeling of UASB treating domestic wastewater in Nepal." Renewable Energy 95 (September 2016): 263–68. http://dx.doi.org/10.1016/j.renene.2016.04.014.

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Montiel-Escobar, José Luis, Víctor Alcaraz-González, Hugo Oscar Méndez-Acosta, and Victor González-Álvarez. "ADM1-Based Robust Interval Observer for Anaerobic Digestion Processes." CLEAN - Soil, Air, Water 40, no. 9 (September 2012): 933–40. http://dx.doi.org/10.1002/clen.201100718.

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Parker, W. J., and G. H. Wu. "Modifying ADM1 to include formation and emission of odourants." Water Science and Technology 54, no. 4 (August 1, 2006): 111–17. http://dx.doi.org/10.2166/wst.2006.532.

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A mathematical model that is based upon the ADM1 structure has been developed to describe the formation and emission of odourous compounds in anaerobic sludge digestion. Special emphasis is given to the general mechanisms for the formation of common odorous sulfur compounds that are found in anaerobic digesters: methyl mercaptan, dimethyl sulfide and hydrogen sulfide, as well as volatile fatty acids and ammonia. The model includes multiple-reaction stoichiometry, microbial growth kinetics and conventional material balances for an ideally mixed reactor. Simulations that were performed with the model revealed that changes in common operational parameters such as temperature, HRT and sludge metal content can dramatically impact upon the gas phase concentrations of odourants. Additional research is required to reduce uncertainty in the model formulation.

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PARKER, W. "Application of the ADM1 model to advanced anaerobic digestion." Bioresource Technology 96, no. 16 (November 2005): 1832–42. http://dx.doi.org/10.1016/j.biortech.2005.01.022.

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32

Jeong, Hyeong-Seok, Chang-Won Suh, Jae-Lim Lim, Sang-Hyung Lee, and Hang-Sik Shin. "Analysis and application of ADM1 for anaerobic methane production." Bioprocess and Biosystems Engineering 27, no. 2 (December 9, 2004): 81–89. http://dx.doi.org/10.1007/s00449-004-0370-4.

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Galí, A., T. Benabdallah, S. Astals, and J. Mata-Alvarez. "Modified version of ADM1 model for agro-waste application." Bioresource Technology 100, no. 11 (June 2009): 2783–90. http://dx.doi.org/10.1016/j.biortech.2008.12.052.

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Page, D. I., K. L. Hickey, R. Narula, A. L. Main, and S. J. Grimberg. "Modeling anaerobic digestion of dairy manure using the IWA Anaerobic Digestion Model no. 1 (ADM1)." Water Science and Technology 58, no. 3 (August 1, 2008): 689–95. http://dx.doi.org/10.2166/wst.2008.678.

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The Anaerobic Digestion Model No. 1 (ADM1) can be used to describe treatment of dairy manure once manure characteristics have been incorporated in the model. In this paper a parameter set is presented that can be used with ADM1 for simulation of dairy manure digester performance. Model results have been verified with bench-scale experiments and reported data from full-scale systems. Model predictions fit experimental data best for biogas composition and digester effluent COD. Simulated biogas productions were inconsistent with measurements from three different digesters. The model overpredicted acetogenesis, resulting in higher simulated than observed acetate concentrations. However, total volatile acid concentrations were simulated reasonably well. The model consistently predicted higher inorganic nitrogen than measured or reported results, indicating a need for further research in that area. The presented model and associated parameter set can be used to simulate and optimize the performance of full-scale dairy manure digesters.

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Tugtas, A. E., U. Tezel, and S. G. Pavlostathis. "An extension of the Anaerobic Digestion Model No. 1 to include the effect of nitrate reduction processes." Water Science and Technology 54, no. 4 (August 1, 2006): 41–49. http://dx.doi.org/10.2166/wst.2006.524.

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Nitrate reduction processes were incorporated into the IWA Anaerobic Digestion Model No. 1 (ADM1) in order to account for the effect of such processes on fermentation and methanogenesis. The general structure of the ADM1 was not changed except for modifications related to disintegration and hydrolysis of complex organic matter and decayed biomass. A fraction of butyrate/valerate and propionate degraders was assumed to be the fermentative denitrifiers carrying out fermentation in the absence of N-oxides. Nitrate reduction proceeded in a stepwise manner to nitrite, nitric oxide, nitrous oxide and nitrogen gas using four substrates as electron and/or carbon source. The utilization of the four substrates and N-oxides was based on stoichiometry and kinetics. The inhibitory effect of N-oxides on the methanogens was accounted for by the use of non-competitive inhibition functions. Model simulations were compared with experimental data obtained with a batch, mixed fermenting and methanogenic culture amended with various initial nitrate concentrations.

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Straub, A. J., A. S. Q. Conklin, J. F. Ferguson, and H. D. Stensel. "Use of the ADM1 to investigate the effects of acetoclastic methanogen population dynamics on mesophilic digester stability." Water Science and Technology 54, no. 4 (August 1, 2006): 59–66. http://dx.doi.org/10.2166/wst.2006.526.

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The ADM1 was employed to assess the effect of variations in solids hydrolysis and acetoclastic methanogen process characterizations on municipal digester stability relating to excess acetate utilization capacity. First-order single- and dual-pathway hydrolysis rate functions and single and competitive acetoclastic methanogen rate functions were implemented in the ADM1. The acetate capacity number (ACN), defined as the ratio between the maximum acetate utilization rate and the average acetate production rate, was used to index digester instability. Simulations of a single CSTR at steady state indicate a similar ACN can be obtained with a 12-day SRT digester dominated by Methanosarcina sp and a 24-day SRT digester dominated by Methanosaeta sp. An increase in ACN with a decrease in SRT representing Methanosarcina sp. selection was observed for particulate feed loadings from 40 g COD/L to 90 g COD/L. Feeding frequency and dual-pathway hydrolysis were found to have less effect on the ACN than the competitive acetoclastic model structure.

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Zaher, U., M. S. Moussa, I. N. Widyatmika, P. van Der Steen, H. J. Gijzen, and P. A. Vanrolleghem. "Modelling anaerobic digestion acclimatisation to a biodegradable toxicant: application to cyanide." Water Science and Technology 54, no. 4 (August 1, 2006): 129–37. http://dx.doi.org/10.2166/wst.2006.534.

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The observed acclimatisation to biodegradable toxicants in anaerobic cassava wastewater treatment is explained by modelling anaerobic cyanide degradation. A complete degradation pathway is proposed for cyanide. Cyanide degradation is modelled as enzymatic hydrolysis to formate and ammonia. Ammonia is added to the inorganic nitrogen content of the digester while formate is degraded by the hydrogenotrophic methanogens. Cyanide irreversible enzyme inhibition is modelled as an inhibition factor to acetate uptake processes. Cyanide irreversible toxicity is modelled as a decay factor to the acetate degraders. Cyanide as well as added phosphorus buffer solution were considered in the chemical equilibrium calculations of pH. The observed reversible effect after acclimatisation of sludge is modelled by a population shift between two aceticlastic methanogens that have different tolerance to cyanide toxicity. The proposed pathway is added to the IWA Anaerobic Digestion Model no.1 (ADM1). The ADM1 model with the designed extension is validated by an experiment using three lab-scale upflow anaerobic sludge bed reactors which were exposed to different cyanide loadings.

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Rivera-Salvador, Víctor, Juan S. Aranda-Barradas, Teodoro Espinosa-Solares, Fabián Robles-Martínez, and J. Ulises Toledo. "THE ANAEROBIC DIGESTION MODEL IWA-ADM1: A REVIEW OF ITS EVOLUTION." Ingeniería Agrícola y Biosistemas 1, no. 2 (2015): 109–17. http://dx.doi.org/10.5154/r.inagbi.2010.01.001.

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Pons, Marie-Noëlle, Nouceiba Adouani, Man Luo, and Stéphane Pacaud. "Dynamic simulation of anaerobic digestion of farm residues using ADM1." IFAC Proceedings Volumes 43, no. 6 (2010): 347–52. http://dx.doi.org/10.3182/20100707-3-be-2012.0017.

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40

Stallman, Donnie, Diane Nelsen, Janelle Amador, Patrick Evans, David Parry, and H. David Stensel. "Use of ADM1 To Evaluate Anaerobic Digestion of Food Waste." Proceedings of the Water Environment Federation 2012, no. 2 (January 1, 2012): 142–63. http://dx.doi.org/10.2175/193864712811693506.

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41

Montiel-Escobar, José Luis, Víctor Alcaraz-González, Hugo Oscar Méndez-Acosta, and Victor González-Álvarez. "Erratum: ADM1-Based Robust Interval Observer for Anaerobic Digestion Processes." CLEAN - Soil, Air, Water 40, no. 10 (October 2012): 1209. http://dx.doi.org/10.1002/clen.201290012.

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42

Dewantara, Ardhyka. "Implementasi Metode Runge-Kutta-Gill pada Anaerobic Digestion Model No. 1 untuk Memodelkan Produksi Biogas." Indonesian Journal on Computing (Indo-JC) 2, no. 1 (September 14, 2017): 1. http://dx.doi.org/10.21108/indojc.2017.2.1.14.

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Penelitian ini dilakukan untuk membuat model prediksi terhadap hasil biogas yang didapatkan dengan menggunakan reaktor tipe batch. Proses simulasi tersebut dapat menggunakan Anaerobic Digestion Model (ADM1) dengan menggunakan konsentrasi awal glukosa sebesar 500 mgCOD/l dan konsentrasi awal mikroba sebesar 30 mgCOD/l selama 106 jam. Pada penelitian ini bertujuan untuk mengetahui profil kinetika reaksi yang terlibat, penentuan akurasi perhitungan, pengaruh nilai pembagi interval terhadap waktu perhitungan, dan pengaruh konsentrasi awal pada substrat glukosa dan mikroba. Metode yang digunakan untuk memodelkan produksi biogas adalah Runge Kutta Gill. Hasil simulasi menunjukkan bahwa metana yang dihasilkan dari proses tersebut sebesar 417,49250 mgCOD/l dengan jumlah pembagi interval sebanyak 197.003. Selain itu, jumlah konsentrasi mikroba glukosa merupakan yang terbesar dibanding mikroba lainnya, sebesar 77,66615 mgCOD/l. Nilai parameter yang disarankan pada ADM1 hanya cocok untuk lama produksi kurang dari 29 jam. Konsentrasi awal substrat glukosa dan mikroba berpengaruh terhadap jumlah metana yang dihasilkan. Namun pada konsentrasi awal mikroba yang lebih dari 30 mgCOD/l maka akan menghasilkan jumlah metana yang cenderung konstan.

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43

Tassew, Fasil Ayelegn, Wenche Hennie Bergland, Carlos Dinamarca, and Rune Bakke. "Influences of Temperature and Substrate Particle Content on Granular Sludge Bed Anaerobic Digestion." Applied Sciences 10, no. 1 (December 23, 2019): 136. http://dx.doi.org/10.3390/app10010136.

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Influences of temperature (25–35 °C) and substrate particulate content (3.0–9.4 g total suspended solids (TSS)/L) on granular sludge bed anaerobic digestion (AD) were analyzed in lab-scale reactors using manure as a substrate and through modeling. Two particle levels were tested using raw (RF) and centrifuged (CF) swine manure slurries, fed into a 1.3-L lab-scale up-flow anaerobic sludge bed reactor (UASB) at temperatures of 25 °C and 35 °C. Biogas production increased with temperature in both high- and low-particle-content substrates; however, the temperature effect was stronger on high-particle-content substrate. RF and CF produced a comparable amount of biogas at 25 °C, suggesting that biogas at this temperature came mainly from the digestion of small particles and soluble components present in similar quantities in both substrates. At 35 °C, RF showed significantly higher biogas production than CF, which was attributed to increased (temperature-dependent) disintegration of larger solid particulates. Anaerobic Digestion Model No.1 (ADM1) based modeling was carried out by separating particulates into fast and slow disintegrating fractions and introducing temperature-dependent disintegration constants. Simulations gave a better fit for the experimental data than the conventional ADM1 model.

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Liu, Tong, Anna Schnürer, Johanna Björkmalm, Karin Willquist, and Emma Kreuger. "Diversity and Abundance of Microbial Communities in UASB Reactors during Methane Production from Hydrolyzed Wheat Straw and Lucerne." Microorganisms 8, no. 9 (September 11, 2020): 1394. http://dx.doi.org/10.3390/microorganisms8091394.

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The use of straw for biofuel production is encouraged by the European Union. A previous study showed the feasibility of producing biomethane in upflow anaerobic sludge blanket (UASB) reactors using hydrolyzed, steam-pretreated wheat straw, before and after dark fermentation with Caldicellulosiruptor saccharolyticus, and lucerne. This study provides information on overall microbial community development in those UASB processes and changes related to acidification. The bacterial and archaeal community in granular samples was analyzed using high-throughput amplicon sequencing. Anaerobic digestion model no. 1 (ADM1) was used to predict the abundance of microbial functional groups. The sequencing results showed decreased richness and diversity in the microbial community, and decreased relative abundance of bacteria in relation to archaea, after process acidification. Canonical correspondence analysis showed significant negative correlations between the concentration of organic acids and three phyla, and positive correlations with seven phyla. Organic loading rate and total COD fed also showed significant correlations with microbial community structure, which changed over time. ADM1 predicted a decrease in acetate degraders after a decrease to pH ≤ 6.5. Acidification had a sustained effect on the microbial community and process performance.

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45

Gernaey, K. V., C. Rosen, D. J. Batstone, and J. Alex. "Efficient modelling necessitates standards for model documentation and exchange." Water Science and Technology 53, no. 1 (January 1, 2006): 277–85. http://dx.doi.org/10.2166/wst.2006.030.

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In this paper, problems related to simulation model documentation and model exchange between users are discussed. Complex simulation models have gained popularity in the environmental field, but require extensive documentation to allow independent implementation. The existence of different simulation platforms puts high demands on the quality of the original documentation. Recent experiences from cross-platform implementations with the ASM2d and ADM1 models reveal that error-free model documentation is difficult to obtain, and as a consequence, considerable time is spent on searching for documentation and implementation errors of various sources. As such, the list of errors and coding pitfalls provided for ASM2d and ADM1 in this paper is vital information for any future implementation of both models. The time needed to obtain an error-free model implementation can be significantly reduced if a standard language for model documentation and exchange is adopted. The extensible markup language (XML) and languages based on this format may provide a remedy to the problem of platform independent model documentation and exchange. In this paper the possibility to apply this to environmental models is discussed, whereas the practical model implementation examples corroborate the necessity for a standardised approach.

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Huete, E., M. de Gracia, E. Ayesa, and J. L. Garcia-Heras. "ADM1-based methodology for the characterisation of the influent sludge in anaerobic reactors." Water Science and Technology 54, no. 4 (August 1, 2006): 157–66. http://dx.doi.org/10.2166/wst.2006.537.

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This paper presents a systematic methodology to characterise the influent sludge in terms of the ADM1 components from the experimental measurements traditionally used in wastewater engineering. For this purpose, a complete characterisation of the model components in their elemental mass fractions and charge has been used, making a rigorous mass balance for all the process transformations and enabling the future connection with other unit-process models. It also makes possible the application of mathematical algorithms for the optimal characterisation of several components poorly defined in the ADM1 report. Additionally, decay and disintegration have been necessarily uncoupled so that the decay proceeds directly to hydrolysis instead of producing intermediate composites. The proposed methodology has been applied to the particular experimental work of a pilot-scale CSTR treating real sewage sludge, a mixture of primary and secondary sludge. The results obtained have shown a good characterisation of the influent reflected in good model predictions. However, its limitations for an appropriate prediction of alkalinity and carbon percentages in biogas suggest the convenience of including the elemental characterisation of the process in terms of carbon in the analytical program.

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Dittmer, Celina, Johannes Krümpel, and Andreas Lemmer. "Modeling and Simulation of Biogas Production in Full Scale with Time Series Analysis." Microorganisms 9, no. 2 (February 5, 2021): 324. http://dx.doi.org/10.3390/microorganisms9020324.

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Future biogas plants must be able to produce biogas according to demand, which requires proactive feeding management. Therefore, the simulation of biogas production depending on the substrate supply is assumed. Most simulation models are based on the complex Anaerobic Digestion Model No. 1 (ADM1). The ADM1 includes a large number of parameters for all biochemical and physicochemical process steps, which have to be carefully adjusted to represent the conditions of a respective full-scale biogas plant. Due to a deficiency of reliable measurement technology and process monitoring, nearly none of these parameters are available for full-scale plants. The present research investigation shows a simulation model, which is based on the principle of time series analysis and uses only historical data of biogas formation and solid substrate supply, without differentiation of individual substrates. The results of an extensive evaluation of the model over 366 simulations with 48-h horizon show a mean absolute percentage error (MAPE) of 14–18%. The evaluation is based on two different digesters and demonstrated that the model is self-learning and automatically adaptable to the respective application, independent of the substrate’s composition.

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Otuzaltı, Murat Mert, and Nuriye Altınay Perendeci. "Models and ADM1 for stabilized sewage sludge by anaerobic digestion process." Pamukkale University Journal of Engineering Sciences 25, no. 6 (2019): 718–33. http://dx.doi.org/10.5505/pajes.2018.53011.

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Girault, R., G. Bridoux, F. Nauleau, C. Poullain, J. Buffet, J. P. Steyer, A. G. Sadowski, and F. Béline. "A waste characterisation procedure for ADM1 implementation based on degradation kinetics." Water Research 46, no. 13 (September 2012): 4099–110. http://dx.doi.org/10.1016/j.watres.2012.04.028.

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Ramirez, Ivan, Eveline I. P. Volcke, Rajagopal Rajinikanth, and Jean-Philippe Steyer. "Modeling microbial diversity in anaerobic digestion through an extended ADM1 model." Water Research 43, no. 11 (June 2009): 2787–800. http://dx.doi.org/10.1016/j.watres.2009.03.034.

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Journal articles on the topic 'ADM1'

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