Modeling anaerobic digestion of blue algae: stoichiometric coefficients of amino acids acidogenesis and thermodynamics analysis

Arc-Induced Electrospray Ionization Mass Spectrometry

Arc-induced electrospray ionization mass spectrometry (AESI-MS) was developed during which alternating current electrospray is simply achieved through the arc plasma. The AESI source exploits the arc's temperature and charge properties to generate aerosols consisting of charged microdroplets. The electrospray region, in which organic molecules are contained within microdroplets, partially overlaps with the arc plasma region. Guided by the electric field, these molecules undergo ionization, yielding ionic target analytes. AESI represents a soft ionization method that combines the mechanisms of atmospheric pressure chemical ionization and electrospray ionization, facilitating the ionization of analytes with wide ranging polarities. The precisely targeted spraying area enhances ion entry into the mass analyzer, thereby enabling excellent ionization efficiency. The AESI source exhibits several notable advantages over the electrospray ionization source, including an elevated but comparable level of active species concentrations and types, simplified mass spectra for direct amino acid analysis, high salt tolerance, versatile analysis of compounds with varying polarities, and reliable quantitative analysis of amino acids in complex matrices. Overall, AESI broadens the methodologies employed to generate microdroplets, providing a technological and scientific framework for creating distinctive electrospray ionization techniques.

Methane production from acetate, formate and H2/CO2 under high ammonia level: Modified ADM1 simulation and microbial characterization

This study evaluated the methanogenic performance of typical substrates (acetate, formate, H₂/CO₂, and glucose) under low and high ammonia levels and the Anaerobic Digestion Model No.1 (ADM1) was extended and modified for better simulation and understanding of the process. Formate-utilizing and hydrogen-utilizing methanogenesis showed stronger ammonia resistance than acetate-utilizing methanogenesis (13-23% vs. 34% decrease in methane production (MP)). Model extension, based on foundational experiments fed with three typical precursors (R² > 0.92), was then validated with glucose degradation experiments, and satisfactory predictions of MP and total volatile fatty acids were obtained (R² > 0.91). Based on the modified ADM1, the carbon fluxes of glucose degradation were determined, and formate-utilizing methanogenesis showed its importance with a 28-34% contribution of the total methanation, becoming the dominant pathway under high ammonia level. Formate-utilizing methanogenesis also had a thermodynamic advantage among the three pathways. 16S rRNA sequencing suggested a homology between the hydrogen-utilizing and formate-utilizing methanogens. Methanobacterium and Methanobrevibacter were found to be key methanogens, and their enrichment under high ammonia level confirmed the stronger ammonia tolerance of formate-utilizing and hydrogen-utilizing methanogenesis. The microbial characterization and modified ADM1 simulations supported each other.

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.

Influence of particle scattering on photo biochemical transformation process of direct absorption methane digester

An outdoor anaerobic fermentation reactor loses a significant amount of energy due to heat dissipation to the surrounding environment. The digester of direct absorption biogas can effectively utilize solar energy and scattering of the medium to enhance reaction temperature, which can promote anaerobic fermentation of microorganisms. A numerical model for the direct absorption methane digester was established to investigate the mechanism of photo biochemical transformation. The average relative values of simulated results were 4.1% and 9.6%, indicating that the model can effectively simulate the heat transfer process of biogas slurry under solar irradiation. Decreasing the albedo and increasing the effect of forward scattering of small particles can improve the regenerative performance and biogas production of digester. Increasing the backward scattering effect of small particles limited biogas fermentation. Scattering distribution had bigger effects on the rates of biogas and propionic acid production than those of albedo.

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

IWA Anaerobic Digestion Model No. 1 (ADM1) is the most widely recognised and popular mathematical model for anaerobic digestion processes. However, the application of ADM1 to acidogenic fermentation is limited by its use of constant stoichiometry to describe the formation of products via carbohydrate fermentation. This study presents a modification of ADM1 using a variable acidogenic stoichiometric approach in which the hydrogen partial pressure (p_H2) and pH are used to predict and regulate the acidogenic process. The fermentation of ethanol and its kinetics were introduced into the model structure. Experimental data from mixed acid-type fermentation in a 28.4 L anaerobic baffled reactor (ABR) fed with a sucrose solution with a chemical oxygen demand of 4000 mg L^-1 were used to calibrate the model parameters. Two case studies involving continuous ethanol-type fermentation in an ABR and a continuous stirring tank reactor (CSTR) were used to validate the approach. The modified model achieved good predictions of the experimental data collected from butyric acid, propionic acid, mixed acid, and ethanol-type fermentation in the ABR and CSTR using the standard ADM1 parameter values without any parameter fitting beyond implementation of the variable acidogenic stoichiometry. The p_H2 and pH thresholds in butyric acid, propionic acid, mixed acid, and ethanol-type fermentation could be predicted using this model, which was shown to be a valid mathematical tool for the regulation of fermentation type.

Can algae-based technologies be an affordable green process for biofuel production and wastewater remediation?

Algae is a well-known organism that its characteristic is prominent for biofuel production and wastewater remediation. This critical review aims to present the applicability of algae with in-depth discussion regarding three key aspects: (i) characterization of algae for its applications; (ii) the technical approaches and their strengths and drawbacks; and (iii) future perspectives of algae-based technologies. The process optimization and combinations with other chemical and biological processes have generated efficiency, in which bio-oil yield is up to 41.1%. Through life cycle assessment, algae bio-energy achieves high energy return than fossil fuel. Thus, the algae-based technologies can reasonably be considered as green approaches. Although selling price of algae bio-oil is still high (about $2 L^-1) compared to fossil fuel's price of $1 L^-1, it is expected that the algae bio-oil's price will become acceptable in the next coming decades and potentially dominate 75% of the market.

Highly effective removal of malachite green from aqueous solution by hydrochar derived from phycocyanin-extracted algal bloom residues through hydrothermal carbonization

Huge volumes of harmful algal bloom residues (ABR) are collected during emergency treatment of cyanobacteria blooms, and phycocyanin-extracted algal bloom residues (PE-ABR) are produced after extraction of phycocyanin from ABR.

Application of ADM1 for modeling of biogas production from anaerobic digestion of Hydrilla verticillata

The present study focused on the application of anaerobic digestion model no. 1 (ADM1) to simulate biogas production from Hydrilla verticillata. Model simulation was carried out by implementing ADM1 in AQUASIM 2.0 software. Sensitivity analysis was used to select the most sensitive parameters for estimation using the absolute-relative sensitivity function. Among all the kinetic parameters, disintegration constant (kdis), hydrolysis constant of protein (khyd_pr), Monod maximum specific substrate uptake rate (km_aa, km_ac, km_h2) and half-saturation constants (Ks_aa, Ks_ac) affect biogas production significantly, which were optimized by fitting of the model equations to the data obtained from batch experiments. The ADM1 model after parameter estimation was able to well predict the experimental results of daily biogas production and biogas composition. The simulation results of evolution of organic acids, bacteria concentrations and inhibition effects also helped to get insight into the reaction mechanisms.

Biomethane recovery from Egeria densa in a microbial electrolysis cell-assisted anaerobic system: Performance and stability assessment

Renewable energy recovery from submerged aquatic plants such as Egeria densa (E. densa) via continuous anaerobic digestion (AD) represents a bottleneck because of process instability. Here, a single-chamber membrane-free microbial electrolysis cell (MEC) equipped with a pair of Ti/RuO2 mesh electrodes (i.e. the combined MEC-AD system) was implemented at different applied voltages (0-1.0 V) to evaluate the potential effects of bioelectrochemical stimulation on methane production and process stability of E. densa fermentation. The application of MEC effectively stabilized E. densa fermentation and upgraded overall process performance, especially solid matters removal. E. densa AD process was operated steadily throughout bioelectrochemical process without any signs of imbalance. The solubilization-removal of solid matters and methane conversion efficiency gradually increased with increasing applied voltage, with an average methane yield of approximately 248.2 ± 21.0 mL L(-1) d(-1) at 1.0 V. Whereas, the stability of the process became worse immediately once the external power was removed, with weaken solid matters removal along with methane output, evidencing the favorable and indispensable role in maintaining process stability. The stabilizing effect was further quantitatively demonstrated by statistical analysis using standard deviation (SD), coefficient of variance (CV) and box-plots. The syntrophic and win-win interactions between fermenting bacteria and electroactive bacteria might have contributed to the improved process stability and bioenergy recovery.

Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion

Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections) and ion pairing on modelling of anaerobic digestion processes in such plant-wide models of wastewater treatment. Using the BSM2 as a case study with a number of model variants and cationic load scenarios, this paper presents the effects of an improved physico-chemical description on model predictions and overall plant performance indicators, namely effluent quality index (EQI) and operational cost index (OCI). The acid-base equilibria implemented in the Anaerobic Digestion Model No. 1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. A speciation sub-routine based on a multi-dimensional Newton-Raphson (NR) iteration method is developed to address algebraic interdependencies. The model also includes ion pairs that play an important role in wastewater treatment. The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength demonstrate that corrections to account for non-ideal conditions lead to significant differences in predicted process performance (up to 18% for effluent quality and 7% for operational cost) but that for pH prediction, activity corrections are more important than ion pairing effects. Both are likely to be required when precipitation is to be modelled.