IWA Anaerobic Digestion Model Research Articles

Upgrading ADM1 by Addition of Lag Phase Sub-model to Simulate Acidic Inhibition of Methanogenic Reactor

This study is aimed at improving calculation quality for IWA Anaerobic Digestion Model No.1 (ADM1) to simulate acidic failure of the methane fermentation systems and its performance recovery. The methanogen collected from digestate at a municipal wastewater treatment plant was cultivated in a lab-scale continuous reactor receiving acetate as a sole organic source. By varying the influent concentration during 400 days of operation, 6 datasets of acidification events were obtained to simulate the concentrations of acetate, VSS, pH, and the methane production rate. The ADM1 equipped with either pH sub-model or undissociated acetate sub-model could reproduce the deterioration of reactor performance in the acidic failure but totally failed to simulate the recovery in the subsequent lowered volumetric loading rate. The statistical analysis revealed both ADM1 models had relatively low correlation coefficient (Nash-Sutcliffe model efficiency coefficient (NSE)) of 0.31–0.38 although these were considerably improved from that without parameter calibration (NSE = −0.04). To cope with the mismatch, a lag phase sub-model was developed. The sub-model is composed of the remaining relative activity of the microorganism at which the inhibition peaked, and the half-saturation coefficient to express the specific length of lag phase. By adding the sub-model into the calibrated ADM1, NSE was significantly improved to 0.49–0.53.

Feeding control of anaerobic co-digestion of waste activated sludge and corn silage performed by rule-based PID control with ADM1

Anaerobic co-digestion (AcoD) of corn silage (CS) and waste activated sludge (WAS) co-substrates, compared with anaerobic digestion (AD) of mono-substrate WAS, was simulated under mesophilic conditions with the adapted IWA Anaerobic Digestion Model No. 1 (ADM1), and a rule-based PID control system for control of the AcoD of CS and WAS, through control of their ratios in the feed, was developed, implemented with the model as a test platform. Tests on AcoD of co-substrates were conducted at the COD mass-based feeding ratios of CS to WAS 1:2.5, 1:2.0 and 1:1.2. The maximal biogas production was 0.94 m3/kgVS·d at the feeding ratio 1:1.2. The ADM1 was adapted, and the high-sensitivity kinetic parameters were calibrated and optimised using the data from the tests of steady state mono-digestion of WAS and AcoD of CS and WAS. The simulated data of biogas and methane production, methane content, VFA and pH agreed well with the test data. The rule-based PID control was developed with an additional expert system, in which the lower level controller operated the level of VFA/TIC and the upper level controller manipulated the setpoints of methane production. The feeding ratio of CS to WAS was used as a manipulated variable. With the constraint boundaries, the test on the control system showed that it could keep methane production stable to the setpoint and maximise methane production while resisting the disturbances to AcoD by adjusting the feeding ratios of CS to WAS.

Integration of bioenergetics in the ADM1 and its impact on model predictions.

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.

Application of IWA Anaerobic Digestion Model No. 1 to simulate butyric acid, propionic acid, mixed acid, and ethanol type fermentative systems using a variable acidogenic stoichiometric approach

IWA Anaerobic Digestion Model No. 1 (ADM1) is the most widely recognised and popular mathematical model for anaerobic digestion processes. However, the application of ADM1 to acidogenic fermentation is limited by its use of constant stoichiometry to describe the formation of products via carbohydrate fermentation. This study presents a modification of ADM1 using a variable acidogenic stoichiometric approach in which the hydrogen partial pressure (pH2) and pH are used to predict and regulate the acidogenic process. The fermentation of ethanol and its kinetics were introduced into the model structure. Experimental data from mixed acid-type fermentation in a 28.4 L anaerobic baffled reactor (ABR) fed with a sucrose solution with a chemical oxygen demand of 4000 mg L−1 were used to calibrate the model parameters. Two case studies involving continuous ethanol-type fermentation in an ABR and a continuous stirring tank reactor (CSTR) were used to validate the approach. The modified model achieved good predictions of the experimental data collected from butyric acid, propionic acid, mixed acid, and ethanol-type fermentation in the ABR and CSTR using the standard ADM1 parameter values without any parameter fitting beyond implementation of the variable acidogenic stoichiometry. The pH2 and pH thresholds in butyric acid, propionic acid, mixed acid, and ethanol-type fermentation could be predicted using this model, which was shown to be a valid mathematical tool for the regulation of fermentation type.

A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion

A compilation and analysis of experimentally determined microbial growth yields for syntrophic volatile fatty acid (VFA), lactate oxidisers and methanogens in anaerobic digestion (AD) systems is presented. Only studies based on experimental determinations or sound model-to-data fitting that specifically address parameter identifiability, have been considered. The experimentally determined values are compared and discussed with estimations based on bioenergetic correlations. Only for acetoclastic methanogens the experimentally determined microbial yields appear in good consistency with bioenergetic estimations. For syntrophic microbial groups, the experimetal yield values reported appear much higher than those expected from the low amount of metabolic energy available. These large deviations imply either inaccuracy on the microbial biomass quantification methods or that the syntrophic interspecies electron transfer occurs under mechanisms, or hydrogen equivalent intermediate activities, much below those ever observed in methanogenic environments. In addition, the microbial growth yield values most widely adopted in AD model applications (those reported in the IWA Anaerobic Digestion Model No. 1 (ADM1)) are even higher than the experimental determinations from literature. It is therefore proposed that microbial growth yield values should be restricted by the maximum harvestable ATP calculated through a detailed bioenergetic pathway analysis. Model simulations with different parameter configurations for different yield sources (default ADM1, experimentally determined and bioenergetically estimated values) displayed low sensitivity of the simulations with respect to the yield values as long as the maximum specific microbial growth rate (μmax) remain the same. This suggests that model calibrations could target the accuracy of μmax maintaining the bioenergetic upper limit for microbial growth yields.

Modeling methane production in anaerobic forward osmosis bioreactor using a modified anaerobic digestion model No. 1

Anaerobic membrane bioreactor (AnMBR) using microfiltration (MF) or ultrafiltration (UF) membranes was introduced to enhance poor biomass retention of conventional anaerobic digestion (CAD). Recently, forward osmosis (FO) membrane have been applied to AnMBR, which is called AnFOMBR. FO membrane assures not only high biomass retention but also high removal efficiency for low molecular weight (LMW) matters. Methane production rates in CAD, AnMBR, and AnFOMBR were compared using a modified IWA anaerobic digestion model No. 1 (ADM1) in this work. Accumulation of biomass in AnMBR/AnFOMBR results in enhanced biochemical reaction and gains more methane production. AnFOMBR may experience a significant inhibition by accumulated free ammonia and cations, although concentrated soluble substrates rejected by FO membrane are favorable for more methane production. Rejection rate of inorganic nitrogen is a key parameter to determine the inhibition in methane production of AnFOMBR.

Generalized parameter estimation and calibration for biokinetic models using correlation and single variable optimisations: Application to sulfate reduction modelling in anaerobic digestion

In this work, a generalized method for the estimation of biokinetic parameters in anaerobic digestion (AD) models is proposed. The method consists of a correlation-based approach to estimate specific groups of parameters mechanistically, followed by a sensitivity-based hierarchical and sequential single parameter optimisation (SHSSPO) calibration method for the remaining groups of parameters. The method was evaluated to estimate and calibrate the parameter values for sulfate reduction processes when included into the IWA Anaerobic Digestion Model No. 1 (ADM1) and simulations were compared with experimental data from literature. Under the proposed method, a large number of biokinetic parameters, namely biomass yields, maximum specific uptake rates, and half saturation constants, can first be estimated using mechanistic correlations. This achieves a significant reduction in the number of parameters to be fitted to data. For the remaining parameters, a method is proposed based on the overall sensitivity and degree of ubiquity of each parameter to establish a hierarchy in a sequential single parameter optimisation against the experimental data. This approach aims at eliminating the uncertainty on optimality (and therefore parameter identification) associated to multivariable parameter calibration problems. The method was applied to the sulfate reduction related parameters and led to the hydrogen sulfide inhibition parameters as the only ones requiring optimisation against experimental data. Comparison of the proposed SHSSPO performance with that of multi-dimensional parameter optimisation methods shows a superior performance in terms of overall error and computation times. Also, final simulation results led to model predictions of similar, if not better, quality than those achieved by multivariable parameter optimisation methods. The experimental variables optimized for included liquid effluent concentrations of sulfur species and volatile fatty acids as well as effluent methane gas flow. Overall, the proposed parameter estimation and calibration method provides a deterministic step-by-step approach to parameter estimation that decreases identifiability uncertainty at a very low computational effort. The results obtained suggest that the method could be generically applied with similar success to other biokinetic models frequently used in wastewater treatment.

MODELING THE TWO-STAGE ANAEROBIC DIGESTION OF DOMESTIC WASTEWATER WITH THE DEVELOPMENT OF A MONITORING APPLICATION

Abstract The IWA Anaerobic Digestion Model No. 1 (ADM1) was chosen to simulate a two-stage anaerobic digestion lab-scale plant treating domestic wastewater. Initially, the model was preliminary tested using synthetic wastewater. The simulation results were satisfactorily compared to NH4+ and chemical oxygen demand (COD) data for the first and second stages, respectively. A transformation method was then applied to estimate from the domestic wastewater composition the input variables to the ADM1. After proper calibration and further validation, the model was able to successfully predict the COD degradation from a varying influent, showing its practical applicability. Finally, a standalone application based on the validated model was developed to be used for monitoring purposes at the treatment plant. The developed application is suitable for direct implementation at a full-scale plant without the need of additional software or specialized assistance.

Biomethane potential of food waste: modeling the effects of mild thermal pretreatment and digestion temperature

ABSTRACTIn order to enhance anaerobic biodegradability of food waste (FW), thermal pretreatment was applied. The effectiveness in terms of biodegradability extent and process rate improvement was investigated. To this aim, Biomethane Potential tests were carried out under mesophilic and thermophilic conditions. The IWA anaerobic digestion Model 1 (ADM1), a powerful tool for modeling the anaerobic digestion (AD) of different substrates, was implemented to predict the methane production. Disintegration constant (k_dis) and maximum acetate uptake rate (km_ac) were identified as the most sensitive parameters and were calibrated over the observed methane production. Pretreatment improvement was more evident in enhancing parameters related to the process rate, such as solubilization extent (+153%) and disintegration constant (+18%), rather than increasing substrate biodegradability. Thermophilic conditions proved to be effective in speeding up the whole AD process, since all the kinetics were significantly improved (disintegration rate increased up to fivefold). Furthermore, it was demonstrated that, after k_dis and km_ac calibration, default thermophilic ADM1 parameters can be suitable to model FW digestion.

Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes

This paper proposes a series of extensions to functionally upgrade the IWA Anaerobic Digestion Model No. 1 (ADM1) to allow for plant-wide phosphorus (P) simulation. The close interplay between the P, sulfur (S) and iron (Fe) cycles requires a substantial (and unavoidable) increase in model complexity due to the involved three-phase physico-chemical and biological transformations. The ADM1 version, implemented in the plant-wide context provided by the Benchmark Simulation Model No. 2 (BSM2), is used as the basic platform (A0). Three different model extensions (A1, A2, A3) are implemented, simulated and evaluated. The first extension (A1) considers P transformations by accounting for the kinetic decay of polyphosphates (XPP) and potential uptake of volatile fatty acids (VFA) to produce polyhydroxyalkanoates (XPHA) by phosphorus accumulating organisms (XPAO). Two variant extensions (A2,1/A2,2) describe biological production of sulfides (SIS) by means of sulfate reducing bacteria (XSRB) utilising hydrogen only (autolithotrophically) or hydrogen plus organic acids (heterorganotrophically) as electron sources, respectively. These two approaches also consider a potential hydrogen sulfide (ZH2S) inhibition effect and stripping to the gas phase (GH2S). The third extension (A3) accounts for chemical iron (III) (SFe3+) reduction to iron (II) (SFe2+) using hydrogen (SH2) and sulfides (SIS) as electron donors. A set of pre/post interfaces between the Activated Sludge Model No. 2d (ASM2d) and ADM1 are furthermore proposed in order to allow for plant-wide (model-based) analysis and study of the interactions between the water and sludge lines. Simulation (A1 – A3) results show that the ratio between soluble/particulate P compounds strongly depends on the pH and cationic load, which determines the capacity to form (or not) precipitation products. Implementations A1 and A2,1/A2,2 lead to a reduction in the predicted methane/biogas production (and potential energy recovery) compared to reference ADM1 predictions (A0). This reduction is attributed to two factors: (1) loss of electron equivalents due to sulfate (SSO4) reduction by XSRB and storage of XPHA by XPAO; and, (2) decrease of acetoclastic and hydrogenotrophic methanogenesis due to ZH2S inhibition. Model A3 shows the potential for iron to remove free SIS (and consequently inhibition) and instead promote iron sulfide (XFeS) precipitation. It also reduces the quantities of struvite (XMgNH4PO4) and calcium phosphate (XCa3(PO4)2) that are formed due to its higher affinity for phosphate anions. This study provides a detailed analysis of the different model assumptions, the effect that operational/design conditions have on the model predictions and the practical implications of the proposed model extensions in view of plant-wide modelling/development of resource recovery strategies.

Microbial Internal Storage Alters the Carbon Transformation in Dynamic Anaerobic Fermentation.

Microbial internal storage processes have been demonstrated to occur and play an important role in activated sludge systems under both aerobic and anoxic conditions when operating under dynamic conditions. High-rate anaerobic reactors are often operated at a high volumetric organic loading and a relatively dynamic profile, with large amounts of fermentable substrates. These dynamic operating conditions and high catabolic energy availability might also facilitate the formation of internal storage polymers by anaerobic microorganisms. However, so far information about storage under anaerobic conditions (e.g., anaerobic fermentation) as well as its consideration in anaerobic process modeling (e.g., IWA Anaerobic Digestion Model No. 1, ADM1) is still sparse. In this work, the accumulation of storage polymers during anaerobic fermentation was evaluated by batch experiments using anaerobic methanogenic sludge and based on mass balance analysis of carbon transformation. A new mathematical model was developed to describe microbial storage in anaerobic systems. The model was calibrated and validated by using independent data sets from two different anaerobic systems, with significant storage observed, and effectively simulated in both systems. The inclusion of the new anaerobic storage processes in the developed model allows for more successful simulation of transients due to lower accumulation of volatile fatty acids (correction for the overestimation of volatile fatty acids), which mitigates pH fluctuations. Current models such as the ADM1 cannot effectively simulate these dynamics due to a lack of anaerobic storage mechanisms.

EL MODELO DE DIGESTIÓN ANAERÓBICA IWA-ADM1: UNA REVISIÓN DE SU EVOLUCIÓN

The IWA-Anaerobic Digestion Model No. 1 (ADM1) is a structured model that represents complex substrates by their main components; it includes multiple steps to describe biochemical and physicochemical processes involved in anaerobic digestion of complex organic compounds biodegradability. The aim of ADM1 is to create a common framework to develop the simulations of a widely rank of specific processes. Many extensions and modifications of the ADM1 model have been proposed to improve the outputs of the model and to enlarge its capability to handle different substrates exposed to fermentation and not included in the original ADM1. The objective of this review is to provide a general panorama about Anaerobic Digestion Model No. 1 its importance like a common framework to develop a widely specific processes simulations and its development since it was published in 2002. Diverse model applications, original framework modifications and the use of novel methods to increase the predictive capability of the model are discussed. The number of published references about ADM1 has increased in the last years, mainly since 2006. Applications vary from model implementations in wide-plant treatment systems, anaerobic treatment of diverse substrates, kinetic parameters and variables distribution for a more realistic description of the system. The generic model and the relativity easy way to handle the model allow including inhibition phenomena, to consider microbial diversity or an ADM1-ASM coupled, to get key indicators for digester stability and to introduce novel techniques to increase the model performance, quality and advantages.

Application of Anaerobic Digestion Model No. 1 to describe the syntrophic acetate oxidation of poultry litter in thermophilic anaerobic digestion

A molecular analysis found that poultry litter anaerobic digestion was dominated by hydrogenotrophic methanogens which suggests that bacterial acetate oxidation is the primary pathway in the thermophilic digestion of poultry litter. IWA Anaerobic Digestion Model No. 1 (ADM1) was modified to include the bacterial acetate oxidation process in the thermophilic anaerobic digestion (TAD). Two methods for ADM1 parameter estimation were applied: manual calibration with non-linear least squares (MC-NLLS) and an automatic calibration using differential evolution algorithms (DEA). In terms of kinetic parameters for acetate oxidizing bacteria, estimation by MC-NLLS and DEA were, respectively, km 1.12 and 3.25±0.56kgCODkgCOD−1d−1, KS 0.20 and 0.29±0.018kgCODm−3 and Yac-st 0.14 and 0.10±0.016kgCODkgCOD−1. Experimental and predicted volatile fatty acids and biogas composition were in good agreement. Values of BIAS, MSE or INDEX demonstrate that both methods (MC-NLLS and DEA) increased ADM1 accuracy.

Modeling of the methane production and pH value during the anaerobic co-digestion of dairy manure and spent mushroom substrate

A dynamic mathematical model, based on the IWA Anaerobic Digestion Model No. 1 (ADM1), was used to predict the methane production and pH value during anaerobic co-digestion of dairy manure (DM) and spent mushroom substrate (SMS) under different hydraulic retention times (HRT). In this model the degradation of DM was modeled according to classical ADM1, while SMS was divided into inert part as well as biodegradation parts of slowly hydrolysable fraction (SHF) and readily hydrolysable fraction (RHF). The data from lab-scale experiment was used to calibrate and validate this model. The results showed that the model was able to predict reasonably well the steady-state results of methane production and pH value at HRT of 12, 20 and 28 d. The results also indicated that the model suitability to assess the combined effects of HRT and substrate ratio on the methane production and pH value.

Generalised modelling approach for anaerobic co-digestion of fermentable substrates

A general methodology to implement fermentable soluble substrates in the IWA Anaerobic Digestion Model No. 1 (ADM1) that extends its application to anaerobic co-digestion of multiple substrates is presented. The approach considers the fermentation of new soluble substrates, not originally described in ADM1, as channelled through mass- and electron-balanced sugar fermentation equivalent reactions, and that fermentable substrates are degraded by a generic group of fermenters instead of the original ADM1 sugar fermenters. Therefore, no additional microbial group state is required. An additional term that modifies the ADM1 sugar fermentation kinetics equation was included to account for the competition among multiple substrates to be degraded by a particular biomass group. The model was validated at pilot scale treating a blend of pig manure (soluble fraction), wine and gelatine at mesophilic conditions. Only the ADM1 acetoclastic ammonia inhibition parameter was calibrated to obtain consistent model prediction of gas and liquid composition.

New fractionation for a better bioaccessibility description of particulate organic matter in a modified ADM1 model

A new model structure for the hydrolysis step is introduced in the IWA anaerobic digestion model no 1 (ADM1) in order to better represent the bioaccessibility of particulate organic matter. Two particulate organic matter fractions for waste activated sludge (WAS) samples were defined: a readily hydrolysable fraction (Xcr) and a slowly hydrolysable fraction (Xcs). These fractions were hydrolyzed according to a surface-limiting reaction. Batch anaerobic digestion test of untreated WAS was used to develop the model and calibrate the kinetic parameters and biomass concentrations. The validation was carried out with a similar substrate than the calibration but a thermal pretreatment was applied at two different conditions (110°C and 220°C). The behavior of thermophilic anaerobic digestion of WAS samples was effectively represented by the proposed model. No changes among kinetic parameter sets were done and the model is able to represent produced methane volume following the intrinsic changes of the WAS composition through the different thermal pretreatment conditions. Moreover, estimated parameters in 20days of batch anaerobic digestion test were representative of continuous anaerobic digestion in a full-scale digester.

ADM1‐Based Robust Interval Observer for Anaerobic Digestion Processes

AbstractA robust state estimation scheme is proposed for anaerobic digestion (AD) processes to estimate key variables under the most uncertain scenarios (namely, uncertainties on the process inputs and unknown reaction and specific growth rates). This scheme combines the use of the IWA Anaerobic Digestion Model No. 1 (ADM1), the interval observer theory and a minimum number of measurements to reconstruct the unmeasured process variables within guaranteed lower and upper bounds in which they evolve. The performance of this robust estimation scheme is evaluated via numerical simulations that are carried out under actual operating conditions. It is shown that under some structural and operational conditions, the proposed robust interval observer (RIO) has the property of remaining stable in the face of uncertain process inputs, badly known kinetics and load disturbances. It is also shown that the RIO is indeed a powerful tool for the estimation of biomass (composed of seven different species) from a minimum number of measurements in a system with a total of 32 variables from which 24 correspond to state variables.

Anaerobic digestion of different organic wastes for biogas production and its operational control performed by the modified ADM1

Anaerobic digestion (AD) of different organic wastes for biogas production under variable operating conditions was simulated with a steady-state implementation of the modified IWA Anaerobic Digestion Model No. 1 (ADM1), and an input-output feedback control system using the model as a test platform was developed. The main aim of this study was to compare the characteristics of organic wastes in the AD processes and manage to keep the processes stable based on the results of simulation. The two important operating factors, solid retention time (SRT) and organic loading rate (OLR) (or the ratio of input flows for co-digestion), were investigated. Anaerobic digestion of biowaste was characterized with lower biogas production and instability of the processes, especially at OLR 2.5 kgCOD/m3·d or more, although longer SRT could increase the biogas production. Moreover, the co-substrate composed of biowaste and corn silage would lead to instability of the processes and much lower biogas production. Biowaste was, however, preferable to be co-digested with manures of living stock or sewage sludge. Manure could contribute to the stability of the AD processes, and its co-substrates with organic wastes rich in carbohydrates such as biowaste and corn silage would improve the biogas production and the proportion of methane. Longer SRTs would improve the biogas production from manure as well as its co-substrates except the co-substrate with biowaste as the production was not distinctly raised. The test of the developed input-output feedback control system showed that the control system could reject a realistic set of random disturbances and keep the AD processes stable under the desired operational conditions with a minimal use of measurement facilities.

Syntrophic acetate oxidation in two-phase (acid–methane) anaerobic digesters

The microbial processes involved in two-phase anaerobic digestion were investigated by operating a laboratory-scale acid-phase (AP) reactor and analyzing two full-scale, two-phase anaerobic digesters operated under mesophilic (35 °C) conditions. The digesters received a blend of primary sludge and waste activated sludge (WAS). Methane levels of 20% in the laboratory-scale reactor indicated the presence of methanogenic activity in the AP. A phylogenetic analysis of an archaeal 16S rRNA gene clone library of one of the full-scale AP digesters showed that 82% and 5% of the clones were affiliated with the orders Methanobacteriales and Methanosarcinales, respectively. These results indicate that substantial levels of aceticlastic methanogens (order Methanosarcinales) were not maintained at the low solids retention times and acidic conditions (pH 5.2-5.5) of the AP, and that methanogenesis was carried out by hydrogen-utilizing methanogens of the order Methanobacteriales. Approximately 43, 31, and 9% of the archaeal clones from the methanogenic phase (MP) digester were affiliated with the orders Methanosarcinales, Methanomicrobiales, and Methanobacteriales, respectively. A phylogenetic analysis of a bacterial 16S rRNA gene clone library suggested the presence of acetate-oxidizing bacteria (close relatives of Thermacetogenium phaeum, 'Syntrophaceticus schinkii,' and Clostridium ultunense). The high abundance of hydrogen consuming methanogens and the presence of known acetate-oxidizing bacteria suggest that acetate utilization by acetate oxidizing bacteria in syntrophic interaction with hydrogen-utilizing methanogens was an important pathway in the second-stage of the two-phase digestion, which was operated at high ammonium-N concentrations (1.0 and 1.4 g/L). A modified version of the IWA Anaerobic Digestion Model No. 1 (ADM1) with extensions for syntrophic acetate oxidation and weak-acid inhibition adequately described the dynamic profiles of volatile acid production/degradation and methane generation observed in the laboratory-scale AP reactor. The model was validated with historical data from the full-scale digesters.

Modelling the effect of the OLR and OFMSW particle size on the performances of an anaerobic co-digestion reactor

A dynamic mathematical model capable to predict the methane production in an anaerobic completely stirred tank reactor (CSTR), performing the co-digestion of the organic fraction of municipal solid waste (OFMSW) and sewage sludge, is used to assess the effect of the organic loading rate (OLR) and OFMSW particle size on the reactor performances.The model is based on the approach proposed by the IWA Anaerobic Digestion Model no. 1 (ADM1), which has been modified to take into account the peculiarities of a co-digestion process. The main distinctiveness of the proposed model consists in considering two separate influent substrates (i.e. sewage sludge and OFMSW), which are modelled with different biodegradation kinetics. The sewage sludge degradation is modelled according to the ADM1 while a surface based kinetics is used to simulate the OFMSW disintegration process, which depends on particle size distribution (PSD) of the solid waste to be disintegrated. The methane production of a full scale municipal wastewater treatment plant (MWWTP) digester has been evaluated to assess the model capability to estimate the potential energy production under different process conditions. In particular, a sensitivity analysis on two key operational parameters of the CSTR co-digestion process, i.e. OLR and OFMSW particle size, has been carried out. This analysis shows the model suitability to assess the combined effect of such parameters on the digester performances, predicting the process failure occurrence.