Comprehensive ADM1 Extensions to Tackle Some Operational and Metabolic Aspects in Anaerobic Digestion.

Modelling in anaerobic digestion will play a crucial role as a tool for smart monitoring and supervision of the process performance and stability. By far, the Anaerobic Digestion Model No. 1 (ADM1) has been the most recognized and exploited model to represent this process. This study aims to propose simple extensions for the ADM1 model to tackle some overlooked operational and metabolic aspects. Extensions for the discontinuous feeding process, the reduction of the active working volume, the transport of the soluble compound from the bulk to the cell interior, and biomass acclimation are presented in this study. The model extensions are included by a change in the mass balance of the process in batch and continuous operation, the incorporation of a transfer equation governed by the gradient between the extra- and intra- cellular concentration, and a saturation-type function where the time has an explicit influence on the kinetic parameters, respectively. By adding minimal complexity to the existing ADM1, the incorporation of these phenomena may help to understand some underlying process issues that remain unexplained by the current model structure, broadening the scope of the model for control and monitoring industrial applications.

New findings on the anaerobic co-digestion of thermally pretreated sludge and food waste: laboratory and pilot-scale studies.

Co-digestion of thermally pretreated sewage sludge with food waste is an innovative strategy that could improve the balance and availability of nutrients needed to increase the efficiency of anaerobic digestion in terms of biogas production. In this context, the aim of this research was to evaluate the impact of different proportions of sewage sludge/food waste in laboratory- and pilot-scale reactors. Special focus was placed on the impact of the variability of food waste composition on the behaviour of the pilot digester. Our results show that by adding 40% of co-substrate, a higher biogas production was possible during laboratory operation. Interestingly, using a co-substrate of variable composition had no negative impact on the reactor's stability at pilot-scale, promoting an increase in biogas production through a more efficient use of organic matter. In both the lab and pilot experiences there was an impact on the amount of nitrogen in the digestate compared to digester operating in monodigestion. This impact is more significant as the proportion of co-substrate rises. Overall, our results show that co-digestion of thermally pretreated sewage sludge with food waste allows better management of food waste, especially when their composition is variable.

Exploitation of the ADM1 in a XXI century wastewater resource recovery facility (WRRF): The case of codigestion and thermal hydrolysis.

The aim of this study is to test the capability of the anaerobic digestion model n1 (ADM1) to reproduce data from full-scale digesters operated in a wastewater resource recovery facility (WRRF) where both thermal hydrolysis and codigestion with industrial waste are carried out. Furthermore, the potential uses of the model in a WRRF are also described, with particular relevance for plant engineers/operators. The model capability was calibrated and validated with data from full-scale digesters from the Mapocho-Trebal WRRF (Biofactoría) in Santiago, Chile. A success simulation rate, defined as the percentage of experimental values of a certain variable that lies within the simulation band given by a simulation tolerance established by the user/operator, was established to test the capability of the model as objectively as possible. Regarding the full-scale digester fed with thermally pretreated mixed sludge, success rates of 65% for biogas production and 60-100% for other variables were achieved. Regarding the full-scale digester in codigestion mode, the model had a success rate of approximately 60% for predicting the biogas flow for the whole evaluation period, while for the other variables, values between 70 and 100% were attained. The lowest success rates were observed for the volatile fatty acid (VFA) concentration in the digestate. Despite the lack of available data and the number of assumptions that had to be made, the model was demonstrated to be capable of reproducing the behavior of the full-scale reactors. A proper, up-to-date, calibrated and validated model can aid in the decision-making process in a WRRF, for instance, in determining some unmeasured inlet conditions, in improving the resilience of the process and in managing the incorporation of a new cosubstrate into the plant, among others.

Making sense of parameter estimation and model simulation in bioprocesses.

Most articles that report fitted parameters for kinetic models do not include meaningful statistical information. This study demonstrates the importance of reporting a complete statistical analysis and shows a methodology to perform it, using functionalities implemented in computational tools. As an example, alginate production is studied in a batch stirred-tank fermenter and modeled using the kinetic model proposed by Klimek and Ollis (1980). The model parameters and their 95% confidence intervals are estimated by nonlinear regression. The significance of the parameters value is checked using a hypothesis test. The uncertainty of the parameters is propagated to the output model variables through prediction intervals, showing that the kinetic model of Klimek and Ollis (1980) can simulate with high certainty the dynamic of the alginate production process. Finally, the results obtained in other studies are compared to show how the lack of statistical analysis can hold back a deeper understanding about bioprocesses.

Addressing the synergy determination in anaerobic co-digestion and the inoculum activity impact on BMP test.

Anaerobic mono-digestion and co-digestion are nowadays widely used in wastewater treatment plants (WWTP). However, the data processing of the conventional biochemical potential test (BMP) carried out to assess potential substrates should be enhanced to reduce the uncertainty of the results. In this study, two methodologies aiming to improve the data processing in anaerobic digestion studies were proposed. The methodologies aimed at the estimation of synergy in anaerobic co-digestion of organic waste and the standardization of the BMP test results by considering the activity of the inoculums under mono-digestion conditions. Both methodologies comprise the application of the Gompertz equation. For the first methodology, four cosubstrates and two types of substrates were used. Regarding synergy estimation, the cosubstrates dairy whey and grease sludge had an impact on the degradation kinetic. In regard to the second methodology, the results indicate that the activity of the inoculums exerts an influence on the BMP analysis, and it should be considered. This can be meaningful when comparing results among studies when different inoculums are used or even for studies where the same inoculum is used but it is taken at different reactor operational moments.

Assessing the stability of anaerobic co-digestion in the context of a WWTP with thermal pre-treatment of sewage sludge. Case study in Chile.

In this study, beverage wastewater (BW) and extended aeration sewage sludge were assessed as co-substrates with both mixed sludge and thermally hydrolyzed sludge as substrates in an anaerobic codigestion (AcoD) process. The methodology is an integrated methodology that comprises a batch test (BMP) and semicontinuous reactor along with microbial diversity analysis. The results showed that in batch conditions, neither significant synergistic nor antagonistic effects were observed on the maximum potential (P) due to the cosubstrates presence. However, synergistic effects on a kinetic parameter (Rm) were observed when BW was used as cosubstrate. Process instability was observed in semi-continuous mode with cosubstrate BW, which was not predicted by the BMP test. As demonstrated in this study, the BMP approach is also not suitable for predicting continuous performance in real systems; however, it can be used to screen an array of substrates. In semi-continuous mode, one can expect to reach values between 50 and 60% of the biogas potential and 20-40% of the maximum production rate achieved in batch tests. The agreement between batch and semi-continuous results is also dependent on the type of inoculum used. The microbial diversity of the system was more influenced by the reactor stability than the presence of cosubstrates. To predict the performance (and stability) of real anaerobic digesters, dynamic models should be employed.

Comparison of performance in an anaerobic digestion process: one-reactor vs two-reactor configurations.

The present work compares two types of configurations for a two-reaction (acidogenesis and methanogenesis) anaerobic digestion model. These configurations are as follows: (i) a single bioreactor, where the acidogenesis and methanogenesis reactions occur inside and, (ii) two bioreactors connected sequentially, where each reaction occurs separately in each reactor. The mathematical models that describe the mentioned configurations are analyzed at steady state, comparing the following criteria: the stability of the processes (stability properties of desired equilibria) and soluble organic matter removal performance (substrate levels at steady states), concluding that separation of the reactions in two bioreactors does not improve the stability of the process nor the soluble organic matter removal capacity, unless the improvement of the growth functions of both microorganism populations is considerably important at the moment of separating them into two reactors.

Mathematical modelling of in-situ microaerobic desulfurization of biogas from sewage sludge digestion.

Microaeration can be used to cost-effectively remove in-situ H2S from the biogas generated in anaerobic digesters. This study is aimed at developing and validating an extension of the Anaerobic Digestion Model n°1 capable of incorporating the main phenomena which occurs during microaeration. This innovative model was implemented and tested with data from a pilot scale digester microaerated for ∼ 200 d. The results showed that despite the model's initial ability to predict the digester's behavior, its predicted performance was improved by calibrating the most influential parameters. The model's prediction potential was largely enhanced by adding retention parameters that account for the activity of sulfide oxidizing bacteria retained inside the anaerobic digester, which have been consistently shown to be responsible for a large share of the H2S removed.

A need for a standardization in anaerobic digestion experiments? Let's get some insight from meta-analysis and multivariate analysis.

An important variability in the experimental results in anaerobic digestion lab test has been reported. This study presents a meta-analysis coupled with multivariate analysis aiming to assess the impact of this experimental variability in batch and continuous operation at mesophilic and thermophilic anaerobic digestion of waste activated sludge. An analysis of variance showed that there was no significant difference between mesophilic and thermophilic conditions in both continuous and batch conditions. Concerning the operation mode, the values of methane yield were significantly higher in batch experiment than in continuous reactors. According to the PCA, for both cases, the methane yield is positive correlated to the temperature rises. Interestingly, in the batch experiments, the higher the volatile solids in the substrate was, the lowest was the methane production, which is correlated to experimental flaws when setting up those tests. In continuous mode, unlike the batch test, the methane yield is strongly (positively) correlated to the organic content of the substrate. Experimental standardization, above all, in batch conditions are urgently necessary or move to continuous experiments for reporting results. The modeling can also be a source of disturbance in batch test.

Modelling of an anaerobic plug-flow reactor. Process analysis and evaluation approaches with non-ideal mixing considerations.

This study shows the implementation of the Anaerobic Digestion Model (ADM1) in an anaerobic plug-flow reactor (PFR) with two approaches based on the use of consecutive continuous stirred tank reactors (CSTR) connected in serie for considering non-ideal mixing. The two-region (TR) model splits each CSTR into two regions, while the particulate retention (PR) model adds a retention parameter. The models were calibrated and validated based on experimental data from a bench-scale reactor treating cow manure. The PFR conventional model slightly outperformed the non-ideal mixing approaches. However, the PR model showed an increase in biomass retention time treating high solid content substrate. Biogas production was not sensitive to variations of the mixing parameters. The liquid fraction content was better represented by the PR model than the PFR and TR models. The study shows how reactor modelling is useful for monitoring and supervising biogas plants.

Effect of inoculum on the anaerobic digestion of food waste accounting for the concentration of trace elements.

The production of renewable energy in the form of methane from the anaerobic digestion (AD) of food waste (FW) varies depending on factors such as the quantity and quality of the inoculum. This research evaluated the influence of trace elements (Ca, K, Fe, Zn, Al, Mg, Co, Ni, and Mo) present in inoculum from different sources (wastewater treatment plants (WWTPs): 2 agro-industrial WWTPs and 1 municipal WWTP) on the AD of FW. This study found that the source of the inoculum determines the content of macronutrients and trace elements, which can alter the requirements of the AD process and therefore affect methane production. The inoculum obtained from municipal WWTPs contain potentially inhibitory concentrations of Zn and Al that negatively affect methane production (<70 mL CH4·gVS-1), the hydrolysis constant (<0.19 d-1), and the lag-phase (>7 days). It was also found that high concentrations of trace elements such as Ni (35.2 mg kg-1) and Mo (15.4 mg kg-1) in the inoculum increase methane production (140.7 mL CH4·gVS-1) and hydrolysis constant (>0.18d-1) in addition to presenting short lag-phase (<1 day) in the AD of food waste.

Thermochemical pretreatment and anaerobic digestion of dairy cow manure: Experimental and economic evaluation.

The aim of this study was to assess technically and economically the application thermochemical pretreatment in the anaerobic digestion of dairy cow manure. After selecting the optimum substrate to inoculum (S/I) ratio in a preliminary BMP test, the following tests compared 20 different pretreatment conditions varying temperature (100 and 37°C), exposure time (5 and 30min and 12 and 24h) and chemical doses (0.5, 2, 6 and 10% of HCl or NaOH). The highest value of maximum production rate was achieved at an S/I ratio of 0.25gVSsgVSi-1. The major improvements of the methane potential were 23.6% with 10% of NaOH at 100°C for 5min and 20.6% with 2% of HCl at 37°C. The technical-economic analysis showed that the implementation of neither thermal alkali nor thermal-acid pretreatment would be feasible and the conventional one-step anaerobic digestion outperforms both alternatives.

Assessment of microalgae and nitrifiers activity in a consortium in a continuous operation and the effect of oxygen depletion

Background: Industrial wastewaters with a high content of nitrogen are a relevant environmental problem. Currently, treatments to remove nitrogen are not efficient, so is necessary to develop alternative methods. The objective of this study is to investigate a consortium of microalgae - nitrifying, that due to the symbiosis between them could be an interesting alternative. Results: In this study, it was possible to obtain a consortium of nitrifying bacteria (NB) and microalgae (MA) capable of operating with low requirements of dissolved oxygen, using aerobic sludge from wastewater treatment plants. During the operation, this consortium presents removal percentages above 98% of ammonia, even at concentrations of DO of 0.5 mg O2 L-1. It is estimated that the removal was caused both by the action of nitrifying bacteria and microalgae. It was determined that approximately 60% of the ammonia feed was oxidized to nitrate by nitrifying bacteria, while the algae assimilated 40% of the nitrogen feed at steady state. A methodology for measuring the specific activities of nitrifying bacteria and microalgae by comparing the rates in the variation inorganic nitrogen compounds was established with satisfactory results. An average specific activity of 0.05 and 0.02 g NH4 + gVSS-1 d-1 for nitrifying bacteria and microalgae was determined, respectively. Conclusions: The consortium it can be obtained in a single continuous operation, and has a high capacity for nitrogen removal with low oxygen content. The consortium could prove to be a more economical method compared to traditional.

From pre-treatment toward inter-treatment. Getting some clues from sewage sludge biomethanation.

The conventional application of thermal pretreatment of sewage sludge has been to apply it prior to the anaerobic digestion. In this study, the thermal treatment of the digestate was assessed at lab-scale under several temperature and time conditions. Biochemical methane potential (BMP) tests were set up to evaluate the methane production kinetic by using the Gompertz modified and the first order equation. A full-scale digester evaluation was done by using the ADM1 model under different scenarios and by using the parameters drawn from the BMP tests. The best results were obtained at 180°C and 200°C both at 30min where an improvement of 50% in the methane yield in regards to raw digestate. Full-scale simulations show that a scenario with two anaerobic reactors with thermal inter-treatment would improve the methane production by 45% and 20% compared to conventional anaerobic digestion and pretreatments followed by anaerobic digestion, respectively.

Impact of milling, enzyme addition, and steam explosion on the solid waste biomethanation of an olive oil production plant.

Anaerobic digestion is a consolidated bioprocess which can be further enhanced by incorporating an upstream pretreatment unit. The olive oil production produces a large amount of solid waste which needs to be properly managed and disposed. Three different pretreatment techniques were evaluated in regard to their impact on the anaerobic biodegradability: manual milling of olive pomace (OP), enzyme maceration, direct enzyme addition, and thermal hydrolysis of two-phase olive mill waste. The Gompertz equation was used to obtain parameters for comparison purposes. A substrate/inoculum ratio 0.5 was found to be the best to be used in anaerobic batch test with olive pomace as substrate. Mechanical pretreatment of OP by milling increases the methane production rate while keeping the maximum methane yield. The enzymatic pretreatment showed different results depending on the chosen pretreatment strategies. After the enzymatic maceration pretreatment, a methane production of 274 ml CH4 g VS added (-1) was achieved, which represents an improvement of 32 and 71 % compared to the blank and control, respectively. The direct enzyme addition pretreatment showed no improvement in both the rate and the maximum methane production. Steam explosion showed no improvement on the anaerobic degradability of two-phase olive mill waste; however, thermal hydrolysis with no rapid depressurization enhanced notoriously both the maximum rate (50 %) and methane yield (70 %).

Anaerobic biodegradability of fish remains: experimental investigation and parameter estimation.

The generation of organic waste associated with aquaculture fish processing has increased significantly in recent decades. The objective of this study is to evaluate the anaerobic biodegradability of several fish processing fractions, as well as water treatment sludge, for tilapia and sturgeon species cultured in recirculated aquaculture systems. After substrate characterization, the ultimate biodegradability and the hydrolytic rate were estimated by fitting a first-order kinetic model with the biogas production profiles. In general, the first-order model was able to reproduce the biogas profiles properly with a high correlation coefficient. In the case of tilapia, the skin/fin, viscera, head and flesh presented a high level of biodegradability, above 310 mLCH4gCOD⁻¹, whereas the head and bones showed a low hydrolytic rate. For sturgeon, the results for all fractions were quite similar in terms of both parameters, although viscera presented the lowest values. Both the substrate characterization and the kinetic analysis of the anaerobic degradation may be used as design criteria for implementing anaerobic digestion in a recirculating aquaculture system.

Simplified mechanistic model for the two-stage anaerobic degradation of sewage sludge.

Two-phase anaerobic systems are being increasingly implemented for the treatment of both sewage sludge and organic fraction of municipal solid waste. Despite the good amount of mathematical models in anaerobic digestion, few have been applied in two-phase systems. In this study, a three-reaction mechanistic model has been developed, implemented and validated by using experimental data from a long-term anaerobic two-phase (TPAD) digester treating sewage sludge. A sensitivity analysis shows that the most influential parameters of the model are the ones related to the hydrolysis reaction and the activity of methanogens in the thermophilic reactor. The calibration procedure highlights a noticeable growth rate of the thermophilic methanogens throughout the evaluation period. Overall, all the measured variables are properly predicted by the model during both the calibration and the cross-validation periods. The model's representation of the organic matter behaviour is quite good. The most important disagreements are observed for the biogas production especially during the validation period. The whole application procedure underlines the ability of the model to properly predict the behaviour of this bioprocess.

A methodology for a quantitative interpretation of DGGE with the help of mathematical modelling: application in biohydrogen production.

Molecular biology techniques provide valuable insights in the investigation of microbial dynamics and evolution. Denaturing gradient gel electrophoresis (DGGE) analysis is one of the most popular methods which have been used in bioprocess assessment. Most of the anaerobic digestion models consider several microbial populations as state variables. However, the difficulty of measuring individual species concentrations may cause inaccurate model predictions. The integration of microbial data and ecosystem modelling is currently a challenging issue for improved system control. A novel procedure that combines common experimental measurements, DGGE, and image analysis is presented in this study in order to provide a preliminary estimation of the actual concentration of the dominant bacterial ribotypes in a bioreactor, for further use as a variable in mathematical modelling of the bioprocess. This approach was applied during the start-up of a continuous anaerobic bioreactor for hydrogen production. The experimental concentration data were used for determining the kinetic parameters of each species, by using a multi-species chemostat-model. The model was able to reproduce the global trend of substrate and biomass concentrations during the reactor start-up, and predicted in an acceptable way the evolution of each ribotype concentration, depicting properly specific ribotype selection and extinction.

ADM1 calibration using BMP tests for modeling the effect of autohydrolysis pretreatment on the performance of continuous sludge digesters.

Improving anaerobic digestion of sewage sludge through pretreatment techniques is a suitable solution for better sludge management. In this sense, modeling may present itself as an important tool to assess and predict process performance and pretreatment effects. In this study, the feasibility of using biochemical methane potential (BMP) tests data for calibrating the Anaerobic Digestion Model No. 1 (ADM1) was evaluated, in order to simulate the operation of continuous digesters fed, at different HRTs, with raw and autohydrolysis-pretreated waste activated sludge. This was achieved using a simplified COD fractioning methodology proposed to define ADM1 inputs. Hydrolysis constant rates were determined as the most sensitive parameters, and estimated using BMP tests. The calibrated model was then cross-validated with continuous digesters data sets. Good model performance was attained employing these techniques. The ADM1 was able to successfully represent the consumption of slowly biodegradable organic matter in BMP tests, the changes in hydrolytic limiting steps due to the autohydrolysis pretreatment and the behavior of the continuous digesters in overall. The COD fractioning methodology and the Xc variable manipulation proposed seemed to be crucial for proper model predictions. Results indicate that BMP tests are a suitable data source for ADM1 calibration, and that the model can be a powerful tool to assess the effect of the autohydrolysis pretreatment on the anaerobic digestion of sewage waste activated sludge.

Identification in an anaerobic batch system: global sensitivity analysis, multi-start strategy and optimization criterion selection.

Several mathematical models have been developed in anaerobic digestion systems and a variety of methods have been used for parameter estimation and model validation. However, structural and parametric identifiability questions are relatively seldom addressed in the reported AD modeling studies. This paper presents a 3-step procedure for the reliable estimation of a set of kinetic and stoichiometric parameters in a simplified model of the anaerobic digestion process. This procedure includes the application of global sensitivity analysis, which allows to evaluate the interaction among the identified parameters, multi-start strategy that gives a picture of the possible local minima and the selection of optimization criteria or cost functions. This procedure is applied to the experimental data collected from a lab-scale sequencing batch reactor. Two kinetic parameters and two stoichiometric coefficients are estimated and their accuracy was also determined. The classical least-squares cost function appears to be the best choice in this case study.