Anaerobic co-digestion: A critical review of mathematical modelling for performance optimization

Evaluation of traditional and machine learning approaches for modeling volatile fatty acid concentrations in anaerobic digestion of sludge: potential and challenges

This study evaluates models for predicting volatile fatty acid (VFA) concentrations in sludge processing, ranging from classical statistical methods (Gaussian and Surge) to diverse machine learning algorithms (MLAs) such as Decision Tree, XGBoost, CatBoost, LightGBM, Multiple linear regression (MLR), Support vector regression (SVR), AdaBoost, and GradientBoosting. Anaerobic bio-methane potential tests were carried out using domestic wastewater treatment primary and secondary sludge. The tests were monitored over 40 days for variations in pH and VFA concentrations under different experimental conditions. The data observed was compared to predictions from the Gaussian and Surge models, and the MLAs. Based on correlation analysis using basic statistics and regression, the Gaussian model appears to be a consistent performer, with high R2 values and low RMSE, favoring precision in forecasting VFA concentrations. The Surge model, on the other hand, albeit having a high R2, has high prediction errors, especially in dynamic VFA concentration settings. Among the MLAs, Decision Tree and XGBoost excel at predicting complicated patterns, albeit with overfitting issues. This study provides insights underlining the need for context-specific considerations when selecting models for accurate VFA forecasts. Real-time data monitoring and collaborative data sharing are required to improve the reliability of VFA prediction models in AD processes, opening the way for breakthroughs in environmental sustainability and bioprocessing applications.

Applying machine learning to anaerobic fermentation of waste sludge using two targeted modeling strategies

Anaerobic fermentation is an effective method to harvest volatile fatty acids (VFAs) from waste activated sludge (WAS). Accurately predicting and optimizing VFAs production is crucial for anaerobic fermentation engineering. In this study, we developed machine learning models using two innovative strategies to precisely predict the daily yield of VFAs in a laboratory anaerobic fermenter. Strategy-1 focuses on model interpretability to comprehend the influence of variables of interest on VFAs production, while Strategy-2 takes into account the cost of variable acquisition, making it more suitable for practical applications in prediction and optimization. The results showed that Support Vector Regression emerged as the most effective model in this study, with testing R2 values of 0.949 and 0.939 for the two strategies, respectively. We conducted feature importance analysis to identify the critical factors that influence VFAs production. Detailed explanations were provided using partial dependence plots and Shepley Additive Explanations analyses. To optimize VFAs production, we integrated the developed model with optimization algorithms, resulting in a maximum yield of 2997.282 mg/L. This value was 45.2 % higher than the average VFAs level in the operated fermenter. Our study offers valuable insights for predicting and optimizing VFAs production in sludge anaerobic fermentation, and it facilitates engineering practice in VFAs harvesting from WAS.

Determination of the optimal feed recipe of anaerobic digesters using a mathematical model and a genetic algorithm

Recently, numerous experimental studies have been undertaken to understand the interactions between different feedstocks in anaerobic digestion. They have unveiled the potential of blending substrates in the process. Nevertheless, these experiments are time-intensive, prompting the exploration of various optimization approaches. Notably, genetic algorithms have gained interest due to their population-based structures allowing them to efficiently yield multiple Pareto-optimal solutions in a single run. This study uses a simplified static anaerobic co-digestion model as the fitness function for a multi-objective optimization. The optimization aims to achieve a methane production set-point while reducing the output ammonia nitrogen and increasing the recipe' profitability. Thus, the study employs genetic algorithms to identify Pareto fronts and constraints confined the solution space within feasible boundaries. It also underscores the influence of economic considerations on the viable solution space. Ultimately, the optimal feed recipe not only ensures stable operations within the digester but also enhances associated profits.

Applications of artificial intelligence in anaerobic co-digestion: Recent advances and prospects

Anaerobic co-digestion (AcoD) offers several merits such as better digestibility and process stability while enhancing methane yield due to synergistic effects. Operation of an efficient AcoD system, however, requires full comprehension of important operational parameters, such as co-substrates ratio, their composition, volatile fatty acids/alkalinity ratio, organic loading rate, and solids/hydraulic retention time. AcoD process optimization, prediction and control, and early detection of system instability are often difficult to achieve through tedious manual monitoring processes. Recently, artificial intelligence (AI) has emerged as an innovative approach to computational modeling and optimization of the AcoD process. This review discusses AI applications in AcoD process optimization, control, prediction of unknown input/output parameters, and real-time monitoring. Furthermore, the review also compares standalone and hybrid AI algorithms as applied to AcoD. The review highlights future research directions for data preprocessing, model interpretation and validation, and grey-box modeling in AcoD process.

Techno-economic and carbon footprint evaluation of anaerobic digestion plants treating agro-industrial and municipal wastes in North African countries

The agro-industrial activity, which is regarded as a pillar of the North-African economy, is responsible for generating considerable waste quantities. These byproducts can be treated through anaerobic digestion (AD), which offers various financial and ecological benefits over traditional waste disposal methods. However, the transition to this sustainable process is faced with several challenges due to the heterogeneity and seasonality of agro-industrial wastes. In this study, we proposed and evaluated three waste management strategies for treating agro-industrial wastes in large-scale AD plants conceived in specific North-African countries. These strategies involve co-digesting seasonal agro-industrial wastes, i.e., three-phase olive pomace (3POP), grape pomace, and orange peel, with the organic fraction of municipal solid waste (OFMSW) throughout the year (MS1); co-digesting the dominant agro-industrial waste (3POP) with OFMSW during the olive harvest season and mono-digesting OFMSW during the rest of the year (MS2); and co-digesting 3POP and OFMSW year-round by storing 3POP in cold storage facilities (MS3). The techno-economic findings show that the proposed AD plants would be profitable in Morocco and Algeria under both MS1 and MS2, with internal rate of return (IRR) values respectively reaching 10.8% and 18.4% under MS1 and 12.4% and 20.1% under MS2. In contrast, the conceived Tunisian plants would be financially feasible only if MS2 is adopted (IRR of 10.7%). Furthermore, the sensitivity analysis indicates that the economic performance of the proposed plants would mostly be affected by the biomethane selling price and capital cost. Additionally, the carbon footprint analysis suggests that the AD plants could, during their lifetime, reduce the CO2-eq emissions by 411, 208, and 26 Mt (under respectively MS1, MS2, and MS3) compared to the currently used waste disposal practices in the North African region.

Research trends and strategies for the improvement of anaerobic digestion of food waste in psychrophilic temperatures conditions

The organic fraction of municipal solid waste is mainly composed of food waste (FW), and traditional disposal practices for this fraction are generally considered to have negative environmental and economic impacts. However, the organic characteristics of this fraction could also be exploited through the anaerobic digestion of FW (FW-AD), which represents unique advantages, including the reduction of the area required for final disposal and environmental pollution and the same time the generation of renewable energy (mainly methane gas), and a by-product for agricultural use (digestate) due to its high nutrient content. Although approximately 88% of the world's population resides in areas with temperatures below 8 °C, psychrophilic conditions (temperatures below 20 °C) have hardly been studied, while mesophilic (66%) and thermophilic (27%) ranges were found to be more common than psychrophilic FW-AD (7%). The latter condition could decrease microbial activity and organic matter removal, which could affect biogas production and even make AD unfeasible. To improve the efficiency of the psychrophilic FW-AD process, there are strategies such as: measurement of physical properties as particle size, rheological characteristics (viscosity, consistency index and substrate behavior index), density and humidity, bioaugmentation and co-digestion with other substrates, use of inocula with psychrophilic methanogenic communities, reactor heating and modification of reactor configurations. However, these variables have hardly been studied in the context of psychrophilic conditions and future research should focus on evaluating the influence of these variables on FW-AD under psychrophilic conditions. Through a bibliometric analysis, this paper has described and analyzed the FW-AD process, with a focus on the psychrophilic conditions (<20 °C) so as to identify advances and future research trends, as well as determine strategies toward improving the anaerobic process under low temperature conditions.

•

Temperature has a great influence on anaerobic digestion of food waste (FW-AD).

•

Studies on the psychrophilic condition are limited, warranting further research.

•

Physical properties of the substrate and inoculum influence psychrophilic FW-AD.

•

The use of inocula adapted to low temperatures could increase biogas production.

•

Changes in reactor configurations could improve biogas yield at low temperature.

Exploration of machine learning algorithms for predicting the changes in abundance of antibiotic resistance genes in anaerobic digestion

The land application of digestate from anaerobic digestion (AD) is considered a significant route for transmitting antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) to ecosystems. To date, efforts towards understanding complex non-linear interactions between AD operating parameters with ARG/MGE abundances rely on experimental investigations due to a lack of mechanistic models. Herein, three different machine learning (ML) algorithms, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN), were compared for their predictive capacities in simulating ARG/MGE abundance changes during AD. The models were trained and cross-validated using experimental data collected from 33 published literature. The comparison of model performance using coefficients of determination (R²) and root mean squared errors (RMSE) indicated that ANN was more reliable than RF and XGBoost. The mode of operation (batch/semi-continuous), co-digestion of food waste and sewage sludge, and residence time were identified as the three most critical features in predicting ARG/MGE abundance changes. Moreover, the trained ANN model could simulate non-linear interactions between operational parameters and ARG/MGE abundance changes that could be interpreted intuitively based on existing knowledge. Overall, this study demonstrates that machine learning can enable a reliable predictive model that can provide a holistic optimization tool for mitigating the ARG/MGE transmission potential of AD.

Kinetic model discrimination on the biogas production in thermophilic co-digestion of sugarcane vinasse and water hyacinth

Co-digestion between sugarcane vinasse (Vn) and water hyacinth (WH) at various mixing ratios of 0:1, 1:0, 1:3, 3:1, and 1:1 was carried out under thermophilic conditions (55 °C) for 60 days. The effect of various mixing ratios on the pH changes, soluble chemical oxygen demand (sCOD) reduction, and cumulative biogas production was investigated. The first order, modified Gompertz, and logistic function kinetic models were selected to fit the experimental data. Model discrimination was conducted through the Akaike Information Criterion (AIC). The study revealed that co-digestion shows better performance compared to the mono-digestion of both substrates. Vn:WH mixing ratio 1:1 with inoculum to substrate ratio (ISR) of 0.38 g VS_inoculum/g VS_substrate is the most favorable ratio, achieving sCOD reduction efficiency and cumulative biogas production of 71.6% and 1229 mL, respectively. Model selection through AIC revealed that ratio 1:1 was best fitted to the logistic function kinetic model (R² = 0.9897) with Y_m and K values of 1232 mL and 31 mL/day, respectively.

Impacts of food waste to sludge ratios on microbial dynamics and functional traits in thermophilic digesters

A self-stabilizing microbial community lays the foundation of the efficient biochemical reactions of the anaerobic digestion (AD) process. Despite extensive profiling of microbial community dynamics under varying operating parameters, the effects of food waste (FW) to feeding sewage sludge (FSS) ratios on the microbial assembly, functional traits, and syntrophic interspecies interactions in thermophilic microbial consortia remain poorly understood. Here, we investigated the long-term impacts of the FW: FSS ratio on the thermophilic AD microbiome using genome-centric metagenomics. Both the short reads (SRs) assembly, and the iterative hybrid assembly (IHA) of SRs and nanopore long reads (LRs) were used to reconstruct metagenome-assembled genomes (MAGs) and four microbial clusters were identified, demonstrating different microbial dynamics patterns in response to varying FW:FSS ratios. Cluster C1-C3 were comprised of full functional members with genetic potentials in fulfilling empirical AD biochemical reactions, wherein, syntrophic decarboxylating acetogens could interact with methanogens, and some microbes could be energized by the electron bifurcation mechanism to drive thermodynamics unfavorable reactions. We found the co-existence of both acetogenic and hydrogenotrophic methanogens in the AD microbiome, and they altered their trophic groups to scavenge the methanogenic substrates in ensuring the methane generation in digesters with different FW:FSS ratios. Another interesting observation was that two phylogenetically close Thermotogota species showed a possible strong competition on carbon source inferred by the nearly complete genetic overlap of their relevant pathways.

Performance Monitoring of Anaerobic Digestion at Various Organic Loading Rates of Commercial Malaysian Food Waste

Application of anaerobic digestion (AD) has become common in treating palm oil mill effluent in Malaysia; however, employing AD in treating the organic fraction of municipal solid waste (OFMSW), especially food waste, is still scarce. This study aims to characterize the commercial Malaysian food waste (CMFW) and determine its potential as sustainable bioenergy feedstock through biogas production. The sample was digested via the biomethane potential (BMP) test with the variation of organic loading rates (OLRs), ranging from 0.38 to 3.83 gCOD/L. day, under mesophilic conditions. The digestion process was further evaluated in continuous operation using a 6-L continuous stirred-tank reactor (CSTR). The kinetic properties of the process were also determined. It was found that the CMFW had a significant amount of chemical oxygen demand of 230 g/L and an acidic pH of 4.5 with the carbon to nitrogen (C/N) ratio at 121:1. A maximum methane composition of 81% was obtained at 1.92 gCOD/L in the BMP test with specific methane production (SMP) at 0.952 L. CH₄/L.COD fed. The biogas production was well-fitted with the modified Gompertz model with R² at 0.9983 and the maximum biogas potential production rate at R_m 0.1573 L/day, whereas in the CSTR operation, a maximum methane composition of 85% was produced at OLR 6 gCOD/L. day with the SMP of 1.13 L. CH₄/L.COD fed. The CSTR system was in high stability as the pH was maintained in a range of 6.6–6.7, with an alkalinity ratio of 0.28. This study indicates the CMFW is a sustainable feedstock for biogas production in Malaysia. Toward a circular economy approach, the authorities shall introduce commercial scale CMFW AD as part of managing municipal solid waste issues in Malaysia.

Potential of anaerobic co-fermentation in wastewater treatments plants: A review

Fermentation (not anaerobic digestion) is an emerging biotechnology to transform waste into easily assimilable organic compounds such as volatile fatty acids, lactic acid and alcohols. Co-fermentation, the simultaneous fermentation of two or more waste, is an opportunity for wastewater treatment plants (WWTPs) to increase the yields of sludge mono-fermentation. Most publications have studied waste activated sludge co-fermentation with food waste or agri-industrial waste. Mixing ratio, pH and temperature are the most studied variables. The highest fermentation yields have been generally achieved in mixtures dominated by the most biodegradable substrate at circumneutral pH and mesophilic conditions. Nonetheless, most experiments have been performed in batch assays which results are driven by the capabilities of the starting microbial community and do not allow evaluating the microbial acclimation that occurs under continuous conditions. Temperature, pH, hydraulic retention time and organic load are variables that can be controlled to optimise the performance of continuous co-fermenters (i.e., favour waste hydrolysis and fermentation and limit the proliferation of methanogens). This review also discusses the integration of co-fermentation with other biotechnologies in WWTPs. Overall, this review presents a comprehensive and critical review of the achievements on co-fermentation research and lays the foundation for future research.

Using the Mixed Culture of Fodder Mallow (Malva verticillata L.) and White Sweet Clover (Melilotus albus Medik.) for Methane Production

The ever-growing number of biogas plants also leads to an increasing demand for suitable, alternative plant substrates. A currently dominant plant substrate is maize silage. However, intensive cultivation of maize (Zea mays L.) as an energy crop in monocultures poses risk to the environment (soil erosion, depletion of soil nutrient supplies, increased concentration of pests—Ostrinia nubilalis). In this study, results of experimental methane production from silages of alternative substrates, such as fodder mallow (Malva verticillata var. crispa L.; FM), white sweet clover (Melilotus albus Medik.; WSC) and their mixture, are presented. Based on the dry matter yield of a mixed culture of mallow and sweet clover, the value of the land equivalent ratio parameter (LER) was set as 1.05. The obtained LER (>1) value shows that the cultivation of the two tested crops in the mixed culture is more beneficial than their monocultures. Methane production from all three silage variants was fully comparable with results of methane production from the maize silage. Anaerobic fermentation of the mixture of FM and WSC did not result in higher methane yield than the average result of monosubstrates.

Continuous Co-Digestion of Agro-Industrial Mixtures in Laboratory Scale Expanded Granular Sludge Bed Reactors

Anaerobic co-digestion often improves the yields and stability of single anaerobic digestion. However, finding the right substrate proportions within mixtures and corresponding optimal operating conditions using a particular reactor technology often presents a challenge. This research investigated the anaerobic digestion of three mixtures from the liquid fractions of piglet manure (PM), cow manure (CWM), starch wastewater (SWW), and sugar beet (SBT) using three 30 L expanded granular sludge bed (EGSB) reactors. The synergistic effects of two three-substrate mixtures (i.e., PM+CWM+SWW and PM+CWM+SBT) were studied using the PM+CWM mixture as a benchmark. These were used to detect the predicted synergistic interactions found in previous batch tests. The methane productivity of both three-substrate mixtures (~1.20 LCH4/Lreact/d) was 2× the productivity of the benchmark mixture (0.64 LCH4/Lreact/d). Furthermore, strong indications of the predicted synergistic effects were found in the three-substrate mixtures, which were also stable due to their appropriate carbon-to-nitrogen ratio values. Moreover, the lowest averaged solid to hydraulic retention times ratio calculated for samples obtained from the top of the reactors was > 1. This confirmed the superior biomass retention capacity of the studied EGSB reactors over typical reactors that have been used in agricultural biogas plants with a continuous stirred tank reactor.

Application of Various Machine Learning Models for Process Stability of Bio-Electrochemical Anaerobic Digestion

The application of a machine learning (ML) model to bio-electrochemical anaerobic digestion (BEAD) is a future-oriented approach for improving process stability by predicting performances that have nonlinear relationships with various operational parameters. Five ML models, which included tree-, regression-, and neural network-based algorithms, were applied to predict the methane yield in BEAD reactor. The results showed that various 1-step ahead ML models, which utilized prior data of BEAD performances, could enhance prediction accuracy. In addition, 1-step ahead with retraining algorithm could improve prediction accuracy by 37.3% compared with the conventional multi-step ahead algorithm. The improvement was particularly noteworthy in tree- and regression-based ML models. Moreover, 1-step ahead with retraining algorithm showed high potential of achieving efficient prediction using pH as a single input data, which is plausibly an easier monitoring parameter compared with the other parameters required in bioprocess models.

Biophotocatalytic Reduction of CO2 in Anaerobic Biogas Produced from Wastewater Treatment Using an Integrated System

This study presents the bio-photocatalytic upgrading of biogas utilising carbon dioxide (CO2) as a potential option for beginning fossil fuel depletion and the associated environmental risks in the pursuit of sustainable development. Herein, magnetite photocatalyst (Fe-TiO2) was employed with an integrated anaerobic-photomagnetic system for the decontamination of municipality wastewater for biogas production. The Fe-TiO2 photocatalyst used, manufactured via a co-precipitation technique, had a specific surface area of 62.73 m2/g, micropore volume of 0.017 cm3/g and pore size of 1.337 nm. The results showed that using the ultraviolet-visible (UV-Vis) photomagnetic system as a post-treatment to the anaerobic digestion (AD) process was very effective with over 85% reduction in colour, chemical oxygen demand (COD) and turbidity. With an organic loading rate (OLR) of 0.394 kg COD/L·d and hydraulic retention time (HTR) of 21 days, a 92% degradation of the organic content (1.64 kgCOD/L) was attained. This maximised the bioenergy production to 5.52 kWh/m3 with over 10% excess energy to offset the energy demand of the UV-Vis lamp. Assuming 33% of the bioenergy produced was used as electricity to power the UV-Vis lamp, the CO2 emission reduction was 1.74 kg CO2 e/m3, with good potential for environmental conservation.

A review on anaerobic digestion with focus on the role of biomass co-digestion, modelling and optimisation on biogas production and enhancement

The status, recent trends and future perspectives in modelling and optimisation of anaerobic co-digestion is investigated. Areas that can be focused on and those which need further research towards enhancing biogas production are pointed out. Co-digestion, modelling and optimisation of anaerobic digestion as well as techno-economic aspects are reviewed in this paper. It was noted that co-digestion requires more research into a variety of bio-resources and their specific blend proportions. Modelling and optimisation of co-digestion with substrate seasonal fluctuations has not been addressed in previous studies. Controlling key process factors including temperature, pH, and carbon to nitrogen ratio is critical in improving biogas yield. Biogas hybridisation is yet to be explored in depth. The majority of researches are focused on mono-digestion, feedstock co-digestion, modelling, and optimisation of anaerobic digestion needs significant further investigations. A multi-objective approach taking all technical and economic parameters in the modelling and optimization is essential.

Recovery of Household Waste by Generation of Biogas as Energy and Compost as Bio-Fertilizer—A Review

Nowadays, organic waste and especially household waste represents a significant global issue due to population growth. The anaerobic digestion (AD) process is an essential operation contributing powerfully to the valorization of organic waste including food waste in terms of renewable energy generation (biogas) and the rich-nutrient residue that can be utilized as bio-fertilizer. Thus, this process (AD) allows for good recovery of household waste by generating biogas and compost. However, the AD operation has been affected by several key factors. In this paper, we aim to involve different critical parameters influencing the AD process, including temperature, pH, organic loading rate (OLR), carbon to nitrogen ratio (C/N), and total solid content (TS(%)). Further, the paper highlights the inhibition caused by the excessive accumulation of volatile fatty acids (VFAs) and ammoniac, which exhibits the positive effects of co-digestion, pretreatment methods, and mixing techniques for maintaining process stability and enhancing biogas production. We analyze some current mathematical models explored in the literature, such as distinct generic, non-structural, combined, and kinetic first-order models. Finally, the study discusses challenges, provides some possible solutions, and a future perspective that promises to be a highly useful resource for researchers working in the field of household waste recovery for the generation of biogas.

The interaction between lipids and ammoniacal nitrogen mitigates inhibition in mesophilic anaerobic digestion

Ammoniacal nitrogen and long chain fatty acids (LCFA) are common inhibitors of the anaerobic digestion process. However, the interaction between these inhibitors has received little attention. Understanding the interaction between these inhibitors is important to optimise the operation of anaerobic digesters treating slaughterhouse waste or using fat, oil and grease (FOG) as co-substrate among others. To study the interaction between ammoniacal nitrogen and LCFA inhibition, 20 different conditions were trialled in mesophilic batch tests. Experimental conditions included 5 mixtures between slaughterhouse wastewater and LCFA (100:0, 75:25, 50:50, 20:80, 0:100 on a VS basis), each one tested at 4 different ammoniacal nitrogen concentrations (0, 1, 3, 6 gN_added·L^-1). Experimental and modelling results showed that ammoniacal nitrogen inhibition was less severe in LCFA-rich mixtures, indicating that LCFA mitigated ammoniacal nitrogen inhibition to a certain extent. However, the positive interaction between inhibitors did not only depend on the LCFA concentration. A protective LCFA coat that limited the diffusion of free ammonia into the cell and/or provided a localised lower pH in the vicinity of the microbial cell could explain the experimental results. However, ammoniacal nitrogen and LCFA inhibition comprise up to 6 different but interrelated inhibitors (i.e. NH₃, NH₄⁺, LCFA, VFA, H₂ and pH) and therefore the specific mechanism could not be elucidated. Nonetheless, these results suggest that LCFA do not exacerbate TAN-related inhibition and that LCFA-rich substrates can be utilised as co-substrates in mesophilic N-rich digesters.

Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling

Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.

Surfactant rhamnolipid promotes anaerobic codigestion of excess sludge and plant waste

In order to solve the bottleneck of low methane production in anaerobic codigestion of excess sludge (ES) and plant waste (PW), a new strategy of enhancing hydrolysis and acidification by rhamnolipid (RL) was proposed under thermophilic condition. The results showed that the optimal dosage of RL was 50 g/kg total suspended solids, and the maximum yield of methane was 198.5 mL/g volatile suspended solids (VSS), which was 2.3 times of that in the control. RL promoted the dissolution of organic matter in the codigestion process of ES and PW, and the higher the dosage of RL, the higher the concentration of soluble chemical oxygen demand (SCOD) in the fermentation broth. When RL was 100 g/kg, the maximum content of SCOD in fermentation broth was 2,451 mg/L, and the contents of soluble protein and polysaccharide were 593 mg/L and 419 mg/L on 10 d, respectively, which were significantly higher than other groups. In addition, the yield of VFA in RL group was also significantly increased, and acetate and propionate were the main components of VFAs. This research work provides data support for the resource utilization of ES and PW, and expands the application field of RL.

Bioengineered bioreactors: a review on enhancing biomethane and biohydrogen production by CFD modeling

Computational fluid dynamics (CFD) is numerical strategy developed for simulating the behavior of liquid and gas flow. CFD may be applied starting from aerospace, engine design, vehicle aerodynamics, power plants and chemical industries for analyzing and solving relevant system design and process issues. Biogas produced during anaerobic digestion (AD) is sustainable and renewable alternative to fossil fuels. AD may improve the controlled production of biogas and offers significant environmental benefits. This review focuses on research outcomes relevant for enhanced biogas production by exploring the possible applications of CFD in AD technology. CFD-related research performed in AD conditions in order to improve mixing performance, reduce power consumption, and understand the effects of total solid (TS) concentrations on flow behavior have been discussed. In addition, the use of AD for bio-hydrogen production, wastewater treatment, and sludge treatment are looked in. This review also identifies novel areas for AD technology advancement where there is potential for economic improvement in renewable energy production. Finally, future research needs have been identified, focusing on the opportunities to integrate conceptual and mathematical models for advancing CFD simulations for bioenergy.

Application of Multi-Criteria Decision-Making Tools for Assessing Biogas Plants: A Case Study in Reykjavik, Iceland

The European Union is planning a new program to achieve climate neutrality by 2050. In this context, the Icelandic government plans to ban new registrations of fossil fuel cars after 2030 as one of the strategies to make Iceland a carbon-neutral country by 2040. Upgraded biogas can be directly used in vehicles with CNG engines, reducing CO2 emissions by 80%. In this paper, several alternatives of biogas plants, simulated in previous research, were evaluated by considering techno-economic and environmental criteria through the application of multi-criteria decision-making tools. Twelve alternatives were analyzed using the Definite 3.1 software. A weighted summation algorithm, which transforms all criteria into the same scale by multiplying them by weights and then summing them to obtain the results, was used in the analysis. The multi-criteria analysis of the twelve proposed alternatives included eleven criteria (three technical, five economic, and three environmental) whose weights were changed in a total of eleven scenarios. From a global perspective, when all criteria were considered (9.1% weight) the best alternative with a score of 0.58 was the single-stage biogas plant working with municipal solid waste. Sensitivity and uncertainty analyses also demonstrated that the multi-criteria results obtained were robust and reliable.

On the effect of the inlet configuration for anaerobic digester mixing

Sludge recirculation mixing in anaerobic digesters is essential for the stable operation of the digestion process. While often neglected, the configuration of the sludge inlet has a substantial influence on the efficiency of the mixing process. The fluid is either injected directly into the enclosed fluid domain or splashes onto the free surface of the slurry flow. In this paper, the aim was to investigate the effect of the inlet configuration by means of computational fluid dynamics-using ANSYS Fluent. Single-phase and multi-phase models are applied for a submerged and splashing inlet, respectively. To reduce the high computational demand, we also develop surrogate single-phase models for the splashing inlet. The digester mixing is analyzed by comparing velocity contours, velocity profiles, mixing time and dead volume. The non-Newtonian characteristics of the sludge is considered, and a [Formula: see text] model is employed for obtaining turbulence closure. Our method is validated by means of a previous study on the same geometry. Applying a submerged inlet configuration, the resulting dead volume in the tank is estimated around 80 times lower than for the case of a splashing inlet. Additionally, by emulating the multi-phase model for splashing inlet configurations with a single-phase one, the simulation clock time reduced to 15%.

Critical insights into psychrophilic anaerobic digestion: Novel strategies for improving biogas production

Anaerobic digestion (AD) under psychrophilic temperature has only recently garnered deserved attention. In major parts of Europe, USA, Canada and Australia, climatic conditions are more suited for psychrophilic (<20 ℃) rather than mesophilic (35 - 37 ℃) and thermophilic (55 - 60 ℃) AD. Low temperature has adverse effects on important cellular processes which may render the cell biology inactive. Moreover, cold climate can also alter the physical and chemical properties of wastewater, thereby reducing the availability of substrate to microbes. Hence, the use of low temperature acclimated microbial biomass could overcome thermodynamic constraints and carry out flexible structural and conformational changes to proteins, membrane lipid composition, expression of cold-adapted enzymes through genotypic and phenotypic variations. Reduction in organic loading rate is beneficial to methane production under low temperatures. Moreover, modification in the design of existing reactors and the use of hybrid reactors have already demonstrated improved methane generation in the lab-scale. This review also discusses some novel strategies such as direct interspecies electron transfer (DIET), co-digestion of substrate, bioaugmentation, and bioelectrochemical system assisted AD which present promising prospects. While DIET can facilitate syntrophic electron exchange in diverse microbes, the addition of organic-rich co-substrate can help in maintaining suitable C/N ratio in the anaerobic digester which subsequently can enhance methane generation. Bioaugmentation with psychrophilic strains could reduce start-up time and ensure daily stable performance for wastewater treatment facilities at low temperatures. In addition to the technical discussion, the economic assessment and future outlook on psychrophilic AD are also highlighted.

Optimization and Analysis of Liquid Anaerobic Co-Digestion of Agro-Industrial Wastes via Mixture Design

Anaerobic co-digestion (AcoD) is a widely employed technique to produce biogas from simultaneous digestion of various biomasses. However, the selection of the optimal proportions of the substrates in the mixtures presents a challenge. This research used a mixture design to investigate the interactions between the liquid fraction of piglet manure (PM), cow manure (CWM), and starch wastewater (SWW). A modified Gompertz model was used to identify the statistically significant parameters of the methane production curves. The optimal compositions of the mixtures were identified based on multi-objective optimization of the maximal methane yield (YCH4) and maximal methane specific production rate (rCH4) parameters. The study was validated using a double mixture of PM and CWM and a triple mixture. The estimated degradation rates for both mixtures were faster than the predicted ones. The absolute relative errors of rCH4 were 27.41% for the double mixture and 5.59% for the triple mixture, while the relative errors of YCH4 were 4.64% for the double mixture and 10.05% for the triple mixture. These relative errors are within the normal limits of a process with high variability like AD. Thus, mixture design supported by the tested models is suitable for the definition of practically advisable mixtures of substrates.

Visualization and Analysis of Mapping Knowledge Domains for Food Waste Studies

Food waste and loss is a global issue involving ethics, society, the environment, and the economy. However, there is a lack of systematic and visual scientific knowledge and graph methods to study the precedents of this field’s development over time. The article is based on the scientific knowledge graph research of articles published in the past 22 years to review the latest food waste research developments. The study will be conducted from the following perspectives: country/region, institution, author, journal, keyword co-occurrence, and article co-citation. It turns out that in the past eight years, food waste research has grown rapidly. A total of 8298 research articles have been published in 8064 journals and 176 Web of Science (WOS) subject categories. Research shows in the past 20 years. The main research hotspots were anaerobic digestion, biogas production, composting, biological hydrogen production, and innovation in system management methods. In the future, efficient and multitask biological value-added conversion technology, systematization of food-supply-chain decision-making aid models, and research on differences in management strategies may become the frontiers of research.

Review on anaerobic digestion of rice straw for biogas production

India is an agrarian country producing a large amount of rice straw as an agricultural residue. These residues are burnt openly leading to severe environmental pollution and health hazards. Among several options available, anaerobic digestion of rice straw into biomethane gas and digestate is a promising technology. The current paper reviews the characteristics, principles of rice straw and the process variables (temperature, volatile fatty acids, and pH, carbon to nitrogen ratio, metal elements and organic loading rate) that affect the performance of the rice straw digestion and process strategies which may alleviate the barriers and may improve the biomethane yield. Co-digestion of rice straw with nitrogen-rich substrates is proven to be an effective way to balance the carbon to nitrogen ratio, in turn, leads to nutrient balance and enhance the biomethane yields of anaerobic co-digestion system. Moreover, pretreatment is another effective strategy; physical, chemical and biological pretreatments are reviewed in the article which improved the performance of digester. The utilisation of rice straw along with other co-substrates and appropriate pretreatment may be a recommended sustainable solution for preventing environmental and health hazards.

Batch Anaerobic Co-Digestion and Biochemical Methane Potential Analysis of Goat Manure and Food Waste

The improper management of goat manure from concentrated goat feeding operations and food waste leads to the emission of greenhouse gasses and water pollution in the US. The wastes were collected from the International Goat Research Center and a dining facility at Prairie View A&M University. The biochemical methane potential of these two substrates in mono and co-digestion at varied proportions was determined in triplicates and processes were evaluated using two nonlinear regression models. The experiments were conducted at 36 ± 1 °C with an inoculum to substrate ratio of 2.0. The biomethane was measured by water displacement method (pH 10:30), absorbing carbon dioxide. The cumulative yields in goat manure and food waste mono-digestions were 169.7 and 206.0 mL/gVS, respectively. Among co-digestion, 60% goat manure achieved the highest biomethane yields of 380.5 mL/gVS. The biodegradabilities of 33.5 and 65.7% were observed in goat manure and food waste mono-digestions, while 97.4% were observed in the co-digestion having 60% goat manure. The modified Gompertz model is an excellent fit in simulating the anaerobic digestion of food waste and goat manure substrates. These findings provide useful insights into the co-digestion of these substrates.

Comparative study of lactic acid production from date pulp waste by batch and cyclic-mode dark fermentation

Biowaste valorization into lactic acid (LA) by treatment with indigenous microbiota has recently gained considerable attention. LA production from date pulp waste provides an opportunity for resource recovery, reduces environmental issues, and possibly turns biomass into wealth. This study aimed to compare the performance of batch and cyclic fermentation processes in LA production with and without enzymatic pretreatment. The fermentation studies were conducted in the absence of an external inoculum source (relying on indigenous microbiota) and without the addition of nutrients. The highest LA volumetric productivity (3.56 g/liter/day), yield (0.07 g/g-TS), and concentration (21.66 g/L) were attained with enzymatic pretreated date pulp in the cyclic-mode fermentation at the optimized conditions. The productivity rate of LA was enhanced in the cyclic-mode as compared to the batch process. Enzymatic pretreatment increased the digestibility of cellulose that led to higher LA yield. An Artificial Neural Network model was developed to optimize the process parameters and to predict the LA concentration from date pulp waste in both fermentation processes. The main advantage of the ANN approach is the ability to perform quick predictions without resource-consuming experiments. The model predicted optimal conditions well and demonstrated good agreement between experimental and predicted data.

The effect of brewery spent grain application on biogas yields and kinetics in co-digestion with sewage sludge

The present study examines the effect of introducing dried brewery spent grain (BSG), known as the main solid by-product of the brewery industry on biogas yields and kinetics in co-digestion with sewage sludge (SS). The experiment was conducted in semi-continuous anaerobic reactors (supplied once a day) operating under mesophilic conditions (35°C) at different hydraulic retention times (HRT) of 18 and 20 d. In co-digestion runs, the BSG mass to the feed volume ratio was constant and maintained 1:10.The results indicated that the addition of BSG did not influence the biogas production, by comparison with SS mono-digestion (control run). At HRT of 18 d, in the co-digestion run, the average methane yield was 0.27 m³ kg/VS_added, while in the control run the higher value of 0.29 m³ kg/VS_addedwas observed. However, there was no difference in terms of statistical significance. At HRT of 20 d, the methane yield was 0.21 m³ kg/VS_added for both mono- and co-digestion runs. In the BSG presence, the decrease in kinetic constant values was observed. As compared to SS mono-digestion, reductions by 21 and 35% were found at HRT of 20 and 18 d, respectively. However, due to the supplementation of the feedstock with BSG rich in organic compounds, the significantly enhanced energy profits were achieved with the highest value of approx. 40% and related to the longer HRT of 20 d. Importantly, the mono- and co-digestion process proceeded in stable manner. Therefore, the anaerobic co-digestion of SS and BSG might be considered as a cost-effective solution that could contribute to the energy self-efficiency of wastewater treatment plants (WWTPs) and sustainable waste management for breweries.

Comparative analysis of prediction models for methane potential based on spent edible fungus substrate

In this study, ten spent edible fungus (SEF) with different compositional features were used for the maximum methanogenic potential (P₀) evaluation, and the prediction models including regression and kinetics based on this were developed separately. The results showed that the regression model with more chemical components had a good correlation with the P₀, and at least three chemical compositions could reach the threshold of sensitivity. The Cone model showed the best fitting effect on P₀ in all kinetic models, which had higher R-square (>0.994) and lower error (1.004-5.672%). Meanwhile, the minimum digestive testing time (14 days) was determined by the evaluation of sensitivity via statistical indicators. It is concluded that the determination of the prediction model of P₀ should be evaluated with the combination of statistical indicators and specific requirements.

Acclimatization of anaerobic sludge with cow manure and realization of high-rate food waste digestion for biogas production

Long-term acclimatization of anaerobic sludge was conducted by operating a mesophilic continuously stirred anaerobic reactor (CSTR) with continuous feeding of food wastes (FW) and cow manure (CM). During the long-term acclimatization, continued increase of enzyme activity was revealed, while the microbial structure tended stable as shown by the Shannon index and microbial community. By biomethane potential analysis, the acclimated sludge had a methane yield about 13 times higher than the initial anaerobic sludge. The acclimated sludge was subsequently used for FW digestion with stepwise organic loading rate increase without CM addition. The functional phyla of Bacteroidetes and Proteobacteria, which originated from CM but not very abundant, were significantly enriched not only during sludge acclimatization with CM addition but also in the process of FW digestion without CM addition. A microbe coexistence network was proposed to support an explanation of the metabolic pathways of FW digestion using the acclimated sludge.

Anaerobic co-digestion of sewage sludge with cellulose, protein, and lipids: Role of rheology and digestibility

Rheology is known to have an impact on the performance of digesters, but the effect of additional substrates (co-digestion) is poorly understood. The main objective of this study was to investigate the effects of the addition of cellulose, protein and lipids to substrates on the rheological behaviour and biogas production of the mixture of primary sludge (PS) and waste-activated sludge (WAS) in a batch system. A mixture of PS and WAS to form the main substrate was anaerobically co-digested with different types of organic matter (cellulose, protein and lipids) as co-substrates at different co-substrate to main substrate ratios of 2-8 (wt%) under mesophilic conditions and below ammonia inhibition levels. Yield stress (τ_y) and the flow consistency index (k) of the combined feed in the case of cellulose and protein were significantly dependent on the amount of co-substrate added, while there was an insignificant impact on these properties when lipids were added. Cellulose significantly increased τ_y and k in the feed, which resulted in poor fluidity and the improper homogenisation of the digester content, and consequently decreased the biogas yield. In contrast, the biogas yield was improved through the addition of 2% to 6% protein despite an increase in τ_y and k of the feed, but the methane yield decreased at 7% and 8% levels of protein concentration. This observation indicates that the threshold for τ_y and k of the digester media depends on the organic nature and digestibility of the substrate. There was no significant impact on the flow properties of the initial mixture when lipids were added, and their addition increased the biogas yield. A first-order kinetic reaction model was used for predicting the yield of methane from these digesters. The rate constant values revealed an increasing trend, with the highest for protein then lipids then cellulose.

Assessing the stability of co-digesting sewage sludge with pig manure under different mixing ratios

This study assessed the digester stability and overall methane production of co-digestion of sewage sludge (SS) and pig manure (PM). Four different ratios of PM were mixed with SS to reach different final concentrations of total solids (TS), i.e. 4%, 6%, 8% and 10%. Volatile solids (VS) reduction rate decreased along with an increase in TS%, and the maximum cumulative methane yield of 342 mL/g VS_rem was obtained in treatment with TS of 6%. When TS was ≥ 8%, accumulation of volatile fatty acids (VFAs), free ammonium nitrogen (FAN) and total ammonium nitrogen (TAN) were observed. At a TS content of 10%, VFAs accumulated to > 20000 mg/L and the highest FAN was 481 mg/L. The suppression of methanogenesis was negatively correlated with FAN and VFA/TIC (P < 0.05). Co-digestion demonstrated to be an effective way to improve the methane yield from SS due to the enriched biodegradable organic substance and more balanced C/N ratio by incorporating PM.

Anaerobic co-digestion of industrial landfill leachate and glycerin: methanogenic potential, organic matter removal and process optimization

The objective of this study was to evaluate the performance of the anaerobic co-digestion of different concentrations of industrial landfill leachate associated with crude residual glycerin, in relation to the methanogenic potential, COD removal, accumulated methane production, the effects of the factors (food/microorganism ratio and percentage of glycerin added to the leachate) and their interactions on kinetic parameters of methane production (CH₄) using the modified Gompertz model. Co-digestion tests were carried out in bench scale (400 mL of useful volume) under batch mode at 30 ± 1°C during 30-day incubation of anaerobic sewage sludge as inoculum. The parameters glycerin addition to the leachate (v/v) (0%, 1.5%, 5%, 8.5% and 10%) and F/M ratio (0.3, 0.5, 1, 1.5 and 1.7) were investigated using Central Composite Rotational Design method (CCRD). The results indicated significant effect to the response variables: methanogenic potential, COD removal, accumulated production of CH₄ and maximum estimated production of CH₄, considering a confidence interval of 95% (p < .05). The ideal mixture of 95.13% of leachate with 4.87% of raw glycerin was obtained by desirability test to F/M of 1.61 gCOD of substrate per gVSS (volatile suspended solids) of sludge. Methanogenic potential was 0.19 L_NCH₄ gTVS_rem ^-1, and the average removal of COD was 92%, resulting in accumulated production and maximum estimated production of CH₄ of 74 and 80 mL, respectively. It was noted that the process of co-digestion of the industrial landfill leachate with the crude residual glycerin is promising, due to is potential of complementing and balancing organic materials, nutrients and other components that influence the biological process. Abbreviations: AN: ammoniacal nitrogen; BMP: biochemical methane potential; CCRD: central composite rotational design; COD: chemical oxygen demand; F/M ratio: food/microorganism ratio; FSS: fixed suspended solids; NTP: normal temperature and pressure; TSS: total suspended solids; TA: total alkalinity; TFS: total fixed solids; TKN: total Kjeldahl nitrogen; TP: total phosphorus; TS: total solids; TVA: total volatile acids; TVS: total volatile solids; VSS: volatile suspended solids; WWTP: wastewater treatment plant.

High solid mono-digestion and co-digestion performance of food waste and sewage sludge by a thermophilic anaerobic membrane bioreactor

The performance of co-digestion of food waste (FW) and sewage sludge (sludge) by a thermophilic anaerobic membrane bioreactor (ThAnMBR) was firstly investigated. The long-term stable operation showed the feasibility of the utilization of ThAnMBR for mono- and co-digestion of FW and sludge at a high solid condition. Good permeate quality was obtained at all sludge ratios while the addition of sludge restricted the methane generation. For a sludge substitution with a 25% TS-based substrate, the biogas yield of 0.812 L/g-VS_fed was at 91% and 158% that of the mono-digestion of FW and sludge, respectively. Membrane performance indicated that the ThAnMBR operated stably at a high flux of 5 LMH under the high solid (~27 g/L) condition. Furthermore, membrane filtration with a 0.1 μm pore size of hollow fiber not only completely removed suspended solids but also rejected about 70% of soluble COD, 80% of soluble carbohydrates and 17% of soluble proteins.

Modelization of anaerobic processes during co-digestion of slowly biodegradable substrates

The influence of the soluble substrates over the anaerobic processes has been extensively investigated, but little is known about the effects of particulate substrate. The biodegradation of these substrates starts with the hydrolytic step, this process is slower than the other ones involved in the biodegradation of particulate substrates and usually becomes the rate-limiting step. This study investigate the effect of the initial total solids (TS) concentration on the anaerobic co-digestion of two slowly biodegradable organic substrates. The wastes mixtures were prepared at different dilutions in the range from 10% to 28% TS. From these experiments it was observed that as TS concentration increased, the methane production decreased. These results were modelled and it was observed that neither hydrolysis nor fermentation stages controlled the methane production rate. Being a substrate inhibition event experienced at the methanogenic stage the responsible of the lower methane production when operating at high TS concentrations.

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.

Response Surface Methodology to Optimize Methane Production from Mesophilic Anaerobic Co-Digestion of Oily-Biological Sludge and Sugarcane Bagasse

Oily-biological sludge (OBS) generated from petroleum refineries has high toxicity. Therefore, it needs an appropriate disposal method to reduce the negative impacts on the environment. The anaerobic co-digestion process is an effective method that manages and converts organic waste to energy. For effective anaerobic digestion, a co-substrate would be required to provide a suitable environment for anaerobic bacteria. In oily-biological sludge, the carbon/nitrogen (C/N) ratio and volatile solids (VS) content are very low. Therefore, it needs to be digested with organic waste that has a high C/N ratio and high VS content. This study investigates the use of sugarcane bagasse (SB) as an effective co-substrate due to its high C/N ratio and high VS content to improve the anaerobic co-digestion process with oily-biological sludge. The sugarcane bagasse also helps to delay the toxicity effect of the methane bacteria. Batch anaerobic co-digestion of oily-biological sludge was conducted with sugarcane bagasse as a co-substrate in twelve reactors with two-liter capacity, each under mesophilic conditions. The interaction effect of a C/N ratio of 20-30 and a VS co-substrate/VS inoculum ratio of 0.06-0.18 on the methane yield (mL CH4/g VSremoved) was investigated. Before the anaerobic digestion, thermochemical pre-treatment of the inoculum and co-substrate was conducted using sodium hydroxide to balance their acidic nature and provide a suitable pH environment for methane bacteria. Design and optimization for the mixing ratios were carried out by central composite design-response surface methodology (CCD-RSM). The highest predicted methane yield was found to be 63.52 mL CH4/g VSremoved, under optimum conditions (C/N ratio of 30 and co-substrate/inoculum ratio of 0.18).

Evaluation of biomethanization during co-digestion of thermally pretreated microalgae and waste activated sludge, and estimation of its kinetic parameters

The maximum methane yield that can be obtained from anaerobic co-digestion of microalgae and waste activated sludge (WAS) mixtures, after thermal pretreatment at 65 °C during 4 h, was investigated. Furthermore, the fitting of the experimental data by five kinetic models (first-order, second-order, modified Gompertz, Logistic, and two-substrate) was evaluated. Thermal pretreatment increased the methane yield of single microalgae and WAS digestion by ≈ 44 and by ≈ 52%, respectively. The results also showed that up to 60% of WAS can be co-digested with microalgae without impairing the methane yield, producing up to 338 mL_CH4 g_VS^-1. Data from digestion of non-pretreated microalgae and WAS were well described by all kinetic models, but digestion of thermally pretreated microalgae, WAS, and their co-digestion mixtures, was best fitted by means of a two-substrate model, indicating that after pretreatment it is necessary to take into account the contribution of both rapidly and slowly biodegradable fractions.

Enhanced performance of anaerobic digestion of cephalosporin C fermentation residues by gamma irradiation-induced pretreatment

Antibiotic fermentation residues is a hazardous waste due to the existence of residual antibiotics and antibiotic resistance genes (ARGs), probably leading to the induction and spread of antibiotic resistant bacteria (ARB) in the environment, which could pose potential harm to the ecosystem and human health. It is urgent to develop an effective technology to remove the residual antibiotics and ARGs. In this study, the anaerobic digestion combined with gamma irradiation was applied for the disposal and utilization of cephalosporin C fermentation residues. The experimental results showed that the antibacterial activities of cephalosporin C against Staphylococcus aureus were significantly decreased after anaerobic digestion. The removal of tolC, a multidrug resistant gene, was improved up to 100% by the combination of gamma irradiation and anaerobic digestion compared to solely anaerobic digestion process, which may be due to the changes of microbial community structures induced by gamma irradiation.

Experiments and Modeling for Flexible Biogas Production by Co-Digestion of Food Waste and Sewage Sludge

This paper explores the feasibility of flexible biogas production by co-digestion of food waste and sewage sludge based on experiments and mathematical modeling. First, laboratory-scale experiments were carried out in variable operating conditions in terms of organic loading rate and feeding frequency to the digester. It is demonstrated that biogas production can achieve rapid responses to arbitrary feedings through co-digestion, and the stability of the anaerobic digestion process is not affected by the overloading of substrates. Compared with the conventional continuous mode, the required biogas storage capacity in flexible feeding mode can be significantly reduced. The optimum employed feeding organic loading rate (OLR) is identified, and how to adjust the feeding scheme for flexible biogas production is also discussed. Finally, a simplified prediction model for flexible biogas production is proposed and verified by experimental data, which could be conveniently used for demand-oriented control. It is expected that this research could give some theoretical basis for the enhancement of biogas utilization efficiency, thus expanding the applications of bio-energy.

A Review on Anaerobic Digestion of Lignocellulosic Wastes: Pretreatments and Operational Conditions

Anaerobic digestion (AD) has become extremely popular in the last years to treat and valorize organic wastes both at laboratory and industrial scales, for a wide range of highly produced organic wastes: municipal wastes, wastewater sludge, manure, agrowastes, food industry residuals, etc. Although the principles of AD are well known, it is very important to highlight that knowing the biochemical composition of waste is crucial in order to know its anaerobic biodegradability, which makes an AD process economically feasible. In this paper, we review the main principles of AD, moving to the specific features of lignocellulosic wastes, especially regarding the pretreatments that can enhance the biogas production of such wastes. The main point to consider is that lignocellulosic wastes are present in any organic wastes, and sometimes are the major fraction. Therefore, improving their AD could cause a boost in the development in this technology. The conclusions are that there is no unique strategy to improve the anaerobic biodegradability of lignocellulosic wastes, but pretreatments and codigestion both have an important role on this issue.

Mechanisms of enhanced biohydrogen production from macroalgae by ferrous ion: Insights into correlations of microbes and metabolites

This study explored the mechanisms of the enhanced hydrogen production from macroalgae by Fe²⁺ supplementation. Highest hydrogen yield of 19.47 mL/g VS_added was achieved at Fe²⁺ supplementation of 400 mg/L, which was 6.25 times of the control test. In depth analysis of substrate degradation, microbial distribution and metabolites formation was conducted. The results showed that Fe²⁺-supplemented group was dominated by Clostridium butyricum (67.2%) and Ruminococcus gnavus (24.2%), which stimulated hydrogen generation and volatile organic acids accumulation. In contrast, Fe²⁺-deficient group had a microbial community dominated by Exiguobacterium sp. (29.0%), Acinetobacter lwoffii (24.5%) and Clostridium stricto 13 (23.4%), which induced higher efficiency of both biomass hydrolysis and mineralization. Microbes from a single system were mutually cooperative, while microbes from Fe²⁺-deficient and those from Fe²⁺-supplemented systems were mutually exclusive. This study suggested that Fe²⁺ is critical in macroalgae fermentation system to affect the microbial community structure and subsequently switch the metabolic pathways.