Feeding frequency efficacy on biogas yield of oily substrate anaerobic digestion in continuous stir tank reactor.

Anaerobic treatment of oily substrate, known as grease trap waste (GTW), was investigated for its practicability via continuous stirred tank reactor (CSTR) at different operating conditions and selected recovery strategies of feeding frequency efficacy. This study determine the performance of feeding frequency efficacy, namely feeding every 24 hours (R24H) and feeding every 12 hours (R12H). Under organic loading rate (OLR) of 2.2 gCOD/L.day, R12H exhibited methane composition of 57%, methane production rate of 0.27 LCH4/L.day, and methane yield of 0.14 LCH4/gCODremoved. At the same OLR, R24H recorded methane composition of 60%, methane production rate of 0.29 LCH4/L.day and similar methane yield as R12H. Findings indicated that R24H showed performance comparable to that of R12H. Given minor variation observed in performance, it is recommended that plant operators may consider scheduling two feedings per day for low loading conditions and switch to one feeding per day for higher loading conditions. This strategy is designed to balance the system and prevent shock loads, which could lead to plant shutdowns. This mechanism will induce their conversion to volatile fatty acids (VFAs); thus, reducing the risk of acid accumulation and pH drops, which could inhibit methanogens to produce methane, especially for oily substrate.

Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefore, eight machine learning models (linear regression (LR), Gaussian process regression (GPR), artificial neural network (ANN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical boosting regressor (CatBoost)) with particle swarm optimization (PSO) and a genetic algorithm (GA) optimizer were developed and evaluated for prediction of H2, CO, CO2, and CH4 gas yields from SCWG of lignocellulosic biomass. A total of 12 input features of SCWG process conditions (temperature, time, concentration, pressure) and biomass properties (C, H, N, S, VM, moisture, ash, real feed) were utilized for the prediction of gas yields using 166 data points. Among machine learning models, boosting ensemble tree models such as XGB and CatBoost demonstrated the highest power for the prediction of gas yields. PSO-optimized XGB was the best performing model for H2 yield with a test R2 of 0.84 and PSO-optimized CatBoost was best for prediction of yields of CH4, CO, and CO2, with test R2 values of 0.83, 0.94, and 0.92, respectively. The effectiveness of the PSO optimizer in improving the prediction ability of the unoptimized machine learning model was higher compared to the GA optimizer for all gas yields. Feature analysis using Shapley additive explanation (SHAP) based on best performing models showed that (21.93%) temperature, (24.85%) C, (16.93%) ash, and (29.73%) C were the most dominant features for the prediction of H2, CH4, CO, and CO2 gas yields, respectively. Even though temperature was the most dominant feature, the cumulative feature importance of biomass characteristics variables (C, H, N, S, VM, moisture, ash, real feed) as a group was higher than that of the SCWG process condition variables (temperature, time, concentration, pressure) for the prediction of all gas yields. SHAP two-way analysis confirmed the strong interactive behavior of input features on the prediction of gas yields.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables.

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

Effect of residual methane emission on physiological characteristics and carcass performance in Japanese Black cattle.

This study investigated the physiological characteristics and carcass performance associated with residual methane emissions (RME), and the effects of bull differences on CH4-related traits in Japanese Black cattle. Enteric methane (CH4) emissions from 156 Japanese Black cattle (111 heifers and 45 steers) were measured during early fattening using the sniffer method. Various physiological parameters were investigated to clarify the physiological traits between the high, middle, and low RME groups. CH4-related traits were examined to determine whether bull differences affected progeny CH4 emissions. Ruminal butyrate and NH3 concentrations were significantly higher in the high-RME group than in the low-RME group, whereas the propionate content was significantly higher in the low-RME group. Blood urea nitrogen, ß-hydroxybutyric acid, and insulin concentrations were significantly higher, and blood amino acids were lower in the high-RME group than in the other groups. No significant differences were observed in the carcass traits and beef fat composition between RME groups. CH4-related traits were significantly different among bull herds. Our results show that CH4-related traits are heritable, wherein bull differences affect progeny CH4 production capability, and that the above-mentioned rumen fermentations and blood metabolites could be used to evaluate enteric methanogenesis in Japanese Black cattle.

Effects of chironomid larvae density and mosquito biocide on methane and carbon dioxide dynamics in freshwater sediments.

Small lentic water bodies are important emitters of methane (CH4) and carbon dioxide (CO2), but the processes regulating their dynamics and susceptibility to human-induced stressors are not fully understood. Bioturbation by chironomid larvae has been proposed as a potentially important factor controlling the dynamics of both gases in aquatic sediments. Chironomid abundance can be affected by the application of biocides for mosquito control, such as Bti (Bacillus thuringiensis var. israelensis). Previous research has attributed increases in CH4 and CO2 emissions after Bti application to reduced bioturbation by chironomids. In this study, we separately tested the effect of chironomid bioturbation and Bti addition on CH4 production and emission from natural sediments. In a set of 15 microcosms, we compared CH4 and CO2 emission and production rates with high and low densities of chironomid larvae at the bioturbating stage, and standard and five times (5x) standard Bti dose, with control sediments that contained neither chironomid larvae nor Bti. Regardless of larvae density, chironomid larvae did not affect CH4 nor CO2 emission and production of the sediment, although both rates were more variable in the treatments with organisms. 5xBti dosage, however, led to a more than three-fold increase in CH4 and CO2 production rates, likely stimulated by bioavailable dissolved carbon in the Bti excipient and priming effects. Our results suggest weak effects of bioturbating chironomid larvae on the CH4 and CO2 dynamics in aquatic ecosystems. Furthermore, our results point out towards potential functional implications of Bti for carbon cycling beyond those mediated by changes in the macroinvertebrate community.

Methanotrophs mediated biogas valorization: Sustainable route to polyhydroxybutyrate production.

This study explores the ability of methanotrophs to convert biogas into biopolymers, addressing H2S as a limitation in the utilization of biogas as a carbon source for bioconversion. Transcriptomic analysis was conducted to understand the growth and changes in the expression patterns of Type I and II methanotrophs under varying H2S concentrations. Results suggested that Type II methanotrophs can possess a native H2S utilization pathway. Both Type I and II methanotrophs were evaluated for their growth and polyhydroxybutyrate (PHB) production from biogas. Methylocystis sp. MJC1 and Methylocystis sp. OK1 exhibited a maximum biomass production of 4.0 and 4.5 gDCW/L, respectively, in fed-batch culture, aligning with the transcriptome data. Furthermore, Methylocystis sp. MJC1 produced 2.9 g PHB/L from biogas through gas fermentation. These findings underscore biogas-based biotechnology as an innovative solution for environmental and industrial challenges with further optimization and productivity enhancement research expected to broaden the potential in this field.

Assessing microbial stability and predicting biogas production in full-scale thermophilic dry methane fermentation of municipal solid waste.

Compared to typical anaerobic digestion processes, little is known about both sludge microbial compositions and biogas production models for full-scale dry methane fermentation treating municipal solid waste (MSW). The anaerobic sludge composed of one major hydrogenotrophic methanogen (Methanoculleus) and syntrophic acetate oxidizing bacteria (e.g., Caldicoprobacter), besides enrichment of MSW degraders such as Clostridia. The core population remained phylogenetically unchanged during the fermentation process, regardless of amounts of MSW supplied (∼35 ton/d) or biogas produced (∼12000 Nm3/d). Based on the correlations observed between feed amounts of MSW from 6 days in advance to the current day and biogas output (the strongest correlation: r = 0.77), the best multiple linear regression (MLR) model incorporating the temperature factor was developed with a good prediction for validation data (R2 = 0.975). The proposed simple MLR method with only data on the feedstock amounts will help decision-making processes to prevent low-efficient biogas production.

Effect of hydrothermal-acid pretreatment on methane yield and microbial community in anaerobic digestion of rice straw.

Hydrothermal pretreatment has been proposed to enhance straw methane yield during anaerobic digestion recently. However, the combined effect of hydrothermal and organic acid pretreatment (HTOAP) needs further investigation. This study identified optimal pretreatment at 120 °C with 3 % acetic acid for 24 h by orthogonal design method. The HTOAP increased the reducing sugar content by destroying the lignocellulosic structure. A 79 % increment of methane production after HTOAP was observed compared to the untreated group. Microbial analysis showed that HTOAP enriched the relative abundance of lignocellulose-degraders, such as W5053, Thermanaerovibrio, Caldicoprobacter, as well as the syntrophic acetate oxidizing bacteria Syntrophaceticus. Moreover, Methanobacterium conducted hydrogenotrophic methanogenesis dominantly. Furthermore, the potential function analysis showed that HTOAP stimulated the expression of key enzymes in the hydrogenotrophic pathway, including carbon-monoxide dehydrogenase (EC 1.2.7.4) and coenzyme F420 hydrogenase (EC 1.12.98.1). This investigation illustrated the potential of HTOAP of rice straw to facilitate methane production.

Integration of anaerobic digestion and electrodialysis for methane yield promotion and in-situ ammonium recovery.

Ammonia inhibition is a common issue encountered in anaerobic digestion (AD) when treating nitrogen-rich substrates. This study proposed a novel approach, the electrodialysis-integrated AD (ADED) system, for in-situ recovery of ammonium (NH4+) while simultaneously enhancing AD performance. The ADED reactor was operated at two different NH4+-N concentrations (5,000 mg/L and 10,000 mg/L) to evaluate its performance against a conventional AD reactor. The results indicate that the ADED technology effectively reduced the NH4+-N concentration to below 2,000 mg/L, achieving this with a competitive energy consumption. Moreover, the ADED reactor demonstrated a 1.43-fold improvement in methane production when the influent NH4+-N was 5,000 mg/L, and it effectively prevented complete inhibition of methane production at the influent NH4+-N of 10,000 mg/L. The life cycle impact assessment reveals that ADED technology offers a more environmentally friendly alternative by recovering valuable fertilizer from the AD system.

Improving anaerobic digestion performance after severe acidification: Unveiling the impacts of Fe3O4-bentonite composites in co-digestion of waste activated sludge and food waste.

Acidification recovery in anaerobic digestion of food waste is challenging. This study explored its in-situ recovery using a co-substrate of food waste and waste activated sludge. Fe3O4 and bentonite were used as conductor and carrier, respectively, to enhance AD performance under severe acidification. The application of Fe3O4-bentonite resulted in a 152% increase in cumulative methane in the Fe3O4-bentonite 10 digester, demonstrating its effectiveness in restoring the acidified AD system. In acidified systems, bentonite enhanced the diversity and richness of microbial communities due to its buffering capacity. The excessive non-conductive polysaccharides excreted by bacteria in extracellular polymeric substances reduced the possibility of electron transfer by Fe3O4. However, in the synergistic application of Fe3O4 and bentonite, this resistance was alleviated, increasing the possibility of direct interspecies electron transfer, and accelerating the consumption of volatile fatty acids. This approach of integrating carrier and conductive materials is significant for in-situ restoration of acidified systems.

Enhanced anaerobic digestion performance and sludge filterability by membrane microaeration for anaerobic membrane bioreactor application.

Slow dissolution/hydrolysis of insoluble/macromolecular organics and poor sludge filterability restrict the application potential of anaerobic membrane bioreactor (AnMBR). Bubble-free membrane microaeration was firstly proposed to overcome these obstacles in this study. The batch anaerobic digestion tests feeding insoluble starch and soluble peptone with and without microaeration showed that microaeration led to a 65.7-144.8% increase in methane production and increased critical flux of microfiltration membrane via driving the formation of large sludge flocs and the resultant improvement of sludge settleability. The metagenomic and bioinformatic analyses showed that microaeration significantly enriched the functional genes and bacteria for polysaccharide and protein hydrolysis, microaeration showed little negative effects on the functional genes involved in anaerobic metabolisms, and substrate transfer from starch to peptone significantly affected the functional genes and microbial community. This study demonstrates the dual synergism of microaeration to enhance the dissolution/hydrolysis/acidification of insoluble/macromolecular organics and sludge filterability for AnMBR application.

A compound enzyme as an additive to a continuous anaerobic dynamic membrane bioreactor for enhanced lignocellulose removal from codigestion: Performance, membrane characteristics and microorganisms.

To explore the enzyme-enhanced strategy of a continuous anaerobic dynamic membrane reactor (AnDMBR), the anaerobic codigestion system of food waste and corn straw was first operated stably, and then the best combination of compound enzymes (laccase, endo-ß-1,4-glucanase, xylanase) was determined via a series of batch trials. The results showed that the methane yield (186.8 ± 19.9 mL/g VS) with enzyme addition was 12.2 % higher than that without enzyme addition. Furthermore, the removal rates of cellulose, hemicellulose and lignin increased by 31 %, 36 % and 78 %, respectively. In addition, dynamic membranes can form faster and more stably with enzyme addition. The addition of enzymes changed the structure of microbial communities while maintaining sufficient hydrolysis bacteria (Bacteroidetes), promoting the proliferation of Proteobacteria as a dominant strain and bringing stronger acetylation ability. In summary, the compound enzyme strengthening strategy successfully improved the methane production, dynamic membrane effect, and degradation rate of lignocellulose in AnDMBR.

Ensemble machine learning prediction of anaerobic co-digestion of manure and thermally pretreated harvest residues.

This study aimed to clarify the statistical accuracy assessment approaches used in recent biogas prediction studies using state-of-the-art ensemble machine learning approach according to 10-fold cross-validation in 100 repetitions. Three thermally pretreated harvest residue types (maize stover, sunflower stalk and soybean straw) and manure were anaerobically co-digested, measuring biogas and methane yield alongside eight thermal preprocessing and biomass covariates. These were the inputs to an ensemble machine learning approach for biogas and methane yield prediction, employing three feature selection approaches. The Support Vector Machine prediction with the Recursive Feature Elimination resulted in the highest prediction accuracy, achieving the coefficient of determination of 0.820 and 0.823 for biogas and methane yield prediction, respectively. This study demonstrated an extreme dependency of prediction accuracy to input dataset properties, which could only be mitigated with ensemble machine learning and strongly suggested that the split-sample approach, often used in previous studies, should be avoided.

Plant-microbe involvement: How manganese achieves harmonious nitrogen-removal and carbon-reduction in constructed wetlands.

Carbon deficits in inflow frequently lead to inefficient nitrogen removal in constructed wetlands (CWs) treating tailwater. Solid carbon sources, commonly employed to enhance denitrification in CWs, increase carbon emissions. In this study, MnO2 was incorporated into polycaprolactone substrates within CWs, significantly enhancing NH4+-N and NO3--N removal efficiencies by 48.26-59.78 % and 96.84-137.23 %, respectively. These improvements were attributed to enriched nitrogen-removal-related enzymes and increased plant absorption. Under high nitrogen loads (9.55 ± 0.34 g/m3/d), emissions of greenhouse gases (CO2, CH4, and N2O) decreased by 147.23-202.51 %, 14.53-86.76 %, and 63.36-87.36 %, respectively. N2O emissions were reduced through bolstered microbial nitrogen removal pathways by polycaprolactone and MnO2. CH4 accumulation was mitigated by the increased methanotrophs and dampened methanogenesis, modulated by manganese. Additionally, manganese-induced increases in photosynthetic pigment contents (21.28-64.65 %) fostered CO2 sequestration through plant photosynthesis. This research provides innovative perspectives on enhancing nitrogen removal and reducing greenhouse gas emissions in constructed wetlands with polymeric substrates.

Synchronous improvement of methane production and digestate dewaterability in sludge anaerobic digestion by nanobubble.

The subsequence anaerobic digestion (AD) of dewatered sludge (DWS) from wastewater treatment plants necessitates an emphasis on enhancing methane production and dewaterability. The effect of different nanobubble water (NBW) on AD of DWS was investigated under mesophilic conditions. Cumulative methane production was improved by 9.0-27.8% with the addition of different NBW (Air, CO2, He, and N2). NBW improved methanogenic performance by significantly enhancing the hydrolysis of sludge AD. Results from the digestate, the capillary suction time, specific resistance to filtration, and moisture content could be decreased by 14.6-18.2%, 18.8-29.6%, and 13.6-19.5%, respectively. The addition of NBW can improve the dewaterability of digestate by reducing the digestate particle size and increasing the zeta potential of digestate. The addition of NBW significantly increased methane production and improved dewaterability in AD; Air-NBW showed the best improvement.

Ammonia stripping by in situ biogas self-circulation to upgrade continuous thermophilic and mesophilic digestion of hydrothermal high-solid sludge.

High-solid anaerobic digestion of hydrothermal sewage sludge has been developed. In order to upgrade the process by focusing on ammonia inhibition, a simply-equipped stripping system without additional alkali or heat supply was introduced by in situ biogas self-circulation. As the determined limit of total ammonia nitrogen at 1500 mg/L and 1000 mg/L for the mesophilic (MAD) and thermophilic anaerobic digestion (TAD) respectively and stripping rate at 5 L/min, continuous MAD and TAD was conducted in parallel. The stripping system successfully polished up the ammonia inhibition, and methanogenic capability of the TAD was promoted to approximately 90.0 % of the potential. Intermittent stripping mode proved usable. More frequent stripping was inevitable for the TAD as compared to the MAD. Hydraulic retention time below 20 d resulted in failure of the stripping mode due to rapid ammonia generation. Overall, this technology was practical in upgrading high-solid sludge digestion by effective ammonia control.

Impacts of free nitrous acid on stabilizing food waste and sewage sludge for anaerobic digestion.

This work investigated the effectiveness of free nitrous acid (FNA) in enhancing organic waste solubilization to improve biogas production in anaerobic digestion (AD). The results indicated that FNA pretreatment can enhance soluble organic content and control H2S odor in tested organic wastes, including food waste, sewage sludge, and their combination. However, a significant decrease (>50 %) in FNA concentration was found in the reactors, possibly due to denitrifier-driven NO2- consumption. Biochemical methane potential (BMP) tests showed a 25 ± 8 % enhancement in CH4 production in the reactors fed with mixed substrate pretreated with 2.9 mg FNA-N/L. However, the presence of NO2- (325.6-2368.0 mg N/L) in some BMP reactors, due to carryover from FNA pretreatment, adversely affected CH4 production (>55 %) and prolonged lag time (>4.2 times). These findings are valuable for researchers and practitioners in waste management, offering insights for implementing FNA pretreatment to enhance the biodegradability of organic wastes in AD.

New insights on ecological roles of waste activated sludge in nutrient-stressed co-digestion.

There have been extensive applications of waste activated sludge (WAS) in anaerobic co-digestion (AcoD). Nonetheless, mechanisms through which AcoD systems maintain stability, particularly under nutrient-stressed conditions, are under-appreciated. In this study, the role of WAS in a nutrient-stressed WAS-food waste AcoD system was re-evaluated. Our findings demonstrated that WAS-based co-digestion increased methane production (by 20-60%) as WAS bolsters such systems' resilience via establishing a core niche-based microbial balance. The carbon utilization investigation suggested a microbial niche balance is attainable if two conditions are satisfied: 1) hydrolysis efficiency is greater than 50%; and 2) both the acidogenesis-to-hydrolysis and acetogenesis-to-hydrolysis efficiencies surpass 0.5. Metagenomic assembly genome (MAG) analysis indicated that the versatile metabolic characteristics strengthened the microbial niche balance, rendering the system resilient and efficient through a syntrophic mode, contributing to both acidogenesis and acetogenesis. The findings of this study provide new insights into the ecological effects of WAS on AcoD.

Ultrafiltration fractionation of potentially inhibitory substances of hydrothermal liquefaction aqueous phase derived from municipal sludge.

Hydrothermal liquefaction (HTL) is a promising thermo-chemical technology for municipal sludge treatment due to its potential for biocrude oil recovery and minimizing biosolids management costs. However, the process generates a high volume of an aqueous byproduct that needs to be treated due to its high chemical oxygen demand (COD) and various organic and inorganic compounds. Although the aqueous phase is known to contain recalcitrant and potentially inhibitory substances that may affect its biological treatment, their molecular weight distribution (MwD) and its impact on anaerobic biodegradability are poorly understood. Ultrafiltration (UF) was conducted to fractionate HTL aqueous into different molecular weight (Mw) fractions using 300, 100, 10, and 1 kDa membranes. Mesophilic biochemical methane potential (BMP) assays were conducted to assess the anaerobic biodegradability of each fraction, and the first-order model was used to calculate the degradation kinetics of potential inhibitory compounds. The highest percentage of organics (65 %) was found in the Mw<1 kDa range, whereas the 10>Mw>1 kDa had the lowest percentage (8 %). There was no significant difference in the cumulative specific methane produced from various Mw fractions (p>0.05). The Mw<1 kDa fraction had the highest first-order specific methane production rate (0.53 day-1), whereas the unfiltered HTL had the lowest (0.38 day-1). Although UF fractionation increased the rate of anaerobic degradation of HTL aqueous for the Mw<1 kDa fraction, the observed methane potential was only 55 % of the theoretical value. This implies that 45 % of COD remains undegraded even after permeation through the lowest Mw cut-off membrane. Therefore, further characterization of HTL aqueous is needed for compounds with molecular weights below 1 kDa to fully understand the nature of inhibitory organics and their impact on anaerobic digestion. Furthermore, pretreatments utilizing techniques such as adsorption and advanced oxidation may be necessary to enhance the specific methane yields from various HTL aqueous fractions, thereby bringing them closer to the theoretical yield.

High-performance internal circulation anaerobic granular sludge reactor for cattle slaughterhouse wastewater treatment and simultaneous biogas production.

This research investigates the efficacy of a high-performance pilot-scale Internal Circulation Anaerobic Reactor inoculated with Granular Sludge (ICAGSR) for treating cattle slaughterhouse wastewater while concurrently generating biogas. The primary objective is to assess the efficiency and performance of ICAGSR in terms of organic pollutant removal and biogas production using granular anaerobic sludge. The research methodology entails operating the ICAGSR system under ambient conditions and systematically varying key parameters, including different Hydraulic Retention Times (HRTs) (24, 12, and 8 h) and Organic Loading Rates (OLRs) (3.3, 6.14, and 12.83 kg COD/m³. d). The study focuses on evaluating pollutants' removal and biogas production rates. Results reveal that the ICAGSR system achieves exceptional removal efficiency for organic pollutants, with Chemical Oxygen Demand (COD) removal exceeding 74%, 67%, and 68% at HRTs of 24, 12, and 8 h, respectively. Furthermore, the system demonstrates stable and sustainable biogas production, maintaining average methane contents of 80%, 76%, and 72% throughout the experimental period. The successful operation of the ICAGSR system underscores its potential as a viable technology for treating cattle slaughterhouse wastewater and generating renewable biogas. In conclusion, this study contributes to wastewater treatment and renewable energy production by providing a comprehensive analysis of the ICAGSR system's hydrodynamic properties. The research enhances our understanding of the system's performance optimization under varying conditions, emphasizing the benefits of utilizing ICAGSR reactors with granular sludge as an effective and sustainable approach. Identifying current gaps, future research directions aim to further refine and broaden the application of ICAGSR technology in wastewater treatment and renewable energy initiatives.