Simulation Of Methane Production Research Articles

Validation of the methane production measurement accuracy and ranking capacity of portable accumulation chambers for use with small ruminants

Using portable accumulation chambers (PAC) is an attractive approach to recording methane (CH4) production of small ruminants. Mass flow controllers (MFC), for their part, are an effective way of validating PAC measurements, as they allow to simulate methane production rates freely of extraneous factors. The present study describes a series of tests carried out to evaluate the accuracy and precision of methane mass recordings of eight PAC against known CH4 masses released by a MFC. Across the tested range, the PAC were able to recover between 67.6 and 74.5% of the true CH4 released. No significant differences were detected between the different PAC, but a statistically significant linear shift was detected over the mass range. Therefore, PAC as currently used are not well suited for applications looking at absolute production levels requiring high absolute accuracy. If recovery tests are conducted regularly across the measurement range, a calibration factor could be generated to correct for the inaccuracy. These PAC were however well suited for investigating relative differences between animals, e.g. ranking animals to compare differences in CH4 production between breeds. The methane recordings made by these chambers were highly precise, with low coefficients of variation between replicates (0.0–2.4%) and high repeatability (>0.99). Furthermore, the correlation between released and recorded CH4 masses was very strong and positive (R > 0.99). Overall, the mass recovery test presented here provides a feasible method for harmonizing methane monitoring procedures using PAC between research groups, thereby improving joint efforts aimed at mitigating greenhouse gas production in small ruminants.

A novel approach for the fractionation of organic components and microbial degraders in ADM1 and model validation based on the methanogenic potential

The anaerobic digestion model No 1 (ADM1), with fixed fractions of the substrate components, is currently used to simulate methane production during the anaerobic digestion (AD) of waste activated sludge (WAS). However, the goodness-of-fit for the simulation is not ideal due to the different characteristics of WAS from different regions. In this study, a novel methodology based on a modern instrumental analysis and 16S rRNA gene sequence analysis for the fractionation of organic components and microbial degraders in the WAS is investigated to modify the fractions of the components in the ADM1. The combination of Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) analyses were used to achieve a rapid and accurate fractionation of the primary organic matters in the WAS that was verified using both the sequential extraction method and the excitation-emission matrix (EEM). The protein, carbohydrate, and lipid contents in the four different sludge samples measured using the above combined instrumental analyses were 25.0 – 50.0%, 2.0 – 10.0%, and 0.9 – 2.3%. The microbial diversity based on 16S rRNA gene sequence analysis was utilized to re-set the initial fractions of the microbial degraders in the ADM1. A batch experiment was utilized to further calibrate the kinetic parameters in the ADM1. Based on the above optimization of the stoichiometric and kinetic parameters, the ADM1 with full parameter modification for WAS (ADM1-FPM) simulated the methane production of the WAS very well with a Theil's inequality coefficient (TIC) of 0.049, which was increased by 89.8% than that of the default ADM1 fit. The proposed approach, with its rapid and reliable performance, demonstrated a strong application potential for the fractionation of organic solid waste and the modification of ADM1, which contributed to a better simulation of methane production during the AD of organic solid wastes.

Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil

AbstractThe fate of organic carbon (C) in permafrost soils is important to the climate system due to the large global stocks of permafrost C. Thawing permafrost can be subject to dynamic hydrology, making redox processes an important factor controlling soil organic matter (SOM) decomposition rates and greenhouse gas production. In iron (Fe)‐rich permafrost soils, Fe(III) can serve as a terminal electron acceptor, promoting anaerobic respiration of SOM and increasing pH. Current large‐scale models of Arctic C cycling do not include Fe cycling or pH interactions. Here, a geochemical reaction model was developed by coupling Fe redox reactions and C cycling to simulate SOM decomposition, Fe(III) reduction, pH dynamics, and greenhouse gas production in permafrost soils subject to dynamic hydrology. We parameterized the model using measured CO2 and CH4 fluxes as well as changes in pH, Fe(II), and dissolved organic C concentrations from oxic and anoxic incubations of permafrost soils from polygonal permafrost sites in northern Alaska, United States. In simulations of repeated oxic‐anoxic cycles, Fe(III) reduction during anoxic periods enhanced CO2 production, while the net effect of Fe(III) reduction on cumulative CH4 fluxes depended on substrate C availability. With lower substrate availability, Fe(III) reduction decreased total CH4 production by further limiting available substrate. With higher substrate availability, Fe(III) reduction enhanced CH4 production by increasing pH. Our results suggest that interactions among Fe‐redox reactions, pH and methanogenesis are important factors in predicting CH4 and CO2 production as well as SOM decomposition rates in Fe‐rich, frequently waterlogged Arctic soils.

Physical, chemical, and bio-pretreatments on microbial gas production in Baode Block coal.

Currently, the exploitation of Baode Block as a biogenic coal-bed gas field has been in the later stage of stable production; hence, exploration and activation of microbial gas production are of great practical significance for the enhancement and stabilization of block production. Pretreatment is the key process to improve anaerobic biodegradation performance and increase yield and production rate of gas. In this study, we examine physical, chemical, and biological pretreatment methods and compare their effectiveness toward microbial gas production in the coal seam. The obtained results indicate that: (1) grinding can enhance contact between the coal sample and bacteria liquid, and coal powder has greater gas-producing performance than the coal lump. (2) Chemical pretreatment of coal samples using acid and base can enhance gas production capacity. NaOH treatment has better gas-producing performance than HCl treatment, and the activity of microbial flora is higher after treatment. (3) Biological pretreatment can greatly enhance the microbial degradation of coal bed. The highest gas yield after white rot fungus pretreatment is 11.65 m3/t, and gas production cycle is shorter than before. This may be due to the white rot fungus effectively degrading macromolecules and, therefore, shortening the duration of methanogenic hydrolysis, which provides more organic matter for methanogens to decompose. During production, in addition to selecting a proper pretreatment method, the treatment cost and balance between energy input of pretreatment and gas energy output must also be considered. The joint pretreatment between different reagents and treatment methods is a possible solution to the problem and a current research trend to realize the large-scale degradation of coal. The simulated microbial methane production of coal seam is feasible for Baode Block in Ordos, where coal samples in this block have great gas-producing potential after treatment, and provides good references for further in-field tests.

Optimal operating parameter determination based on fuzzy logic modeling and marine predators algorithm approaches to improve the methane production via biomass gasification

The current study is related to optimizing methane production from steam gasification of palm kernel shell (PKS) utilizing coal bottom ash as a catalyst. Based on the experimental dataset, the fuzzy logic technique, represented by the Adaptive Network-based Fuzzy Inference System (ANFIS) structure, is used to create a robust model to simulate methane production via biomass gasification. Then, a Marine Predator Algorithm (MPA) is used to determine the optimal operating parameter of the gasification process. The temperature, particle size, CaO/PKS ratio, and coal bottom ash are used as the decision variables, whereas methane production is used as the objective function. The main findings confirmed that the yield of methane gasification reached 52.82 vol% when the associated temperature, particle size, CaO/PKS Ratio, and coal bottom ash are at 678 °C, 0.42 mm, 3.03, and 0.037 wt%, respectively. Accordingly, the proposed strategy provides a better result than the Analysis of Variance (ANOVA) methodology reported in the literature. Furthermore, the proposed strategy's output exceeds both the results obtained experimentally and ANOVA methods by 20.26% and 29.69%, respectively.

Permeability Enhancement and Methane Drainage Capacity of Tree-type Boreholes to Stimulate Low-permeability Coal Seams

Low permeability coal makes methane control in underground coal mines difficult. Drilling tree-type boreholes is a new method for improving the permeability of coal seams to stimulate cross-measure boreholes drainage. This paper presents an analysis of the permeability enhancement and methane drainage capacity of tree-type boreholes based on data from a coal mine in China. After applying the proposed method, numerical models show that a large area of enhanced permeability is created between the tree’s sub-boreholes. Compared with conventional drainage programs, tree-type boreholes increase the average rate of methane extraction by a factor of 13.9 and the effective influence radius of the borehole by a factor of 4.9. The simulated methane production rates from both types of boreholes are verified against field data from the Shoushan mine, China. This paper presents a quantitative analysis of the relationships between different tree-type borehole properties and methane drainage performance. Longer and more numerous sub-boreholes result in logarithmic drainage increases in the enhanced-permeability areas. Orienting the initial tree-type borehole angle parallel to the direction of maximum horizontal stress maximizes borehole stimulation. During drainage, the effective influence radius of tree-type boreholes expands logarithmically with sub-borehole length; cumulative methane production increases linearly with the length and number of sub-boreholes. These results can provide reliable scientific guidance for optimizing the layout of tree-type boreholes in field test.

Resource Assessment and Numerical Modeling of CBM Extraction in the Upper Silesian Coal Basin, Poland

The paper presents the assessment of the resources of methane considered as the main mineral in the most prospective selected areas of the Upper Silesian Coal Basin, Poland in the region of undeveloped deposits. The methane resources were estimated by means of a volumetric method at three depth levels, 1000, 1250, and 1500 m. A part of the Studzienice deposit comprising three coal seams, 333, 336, and 337, located in a methane zone was chosen for the numerical modeling of simulated methane production. The presented static 3D model has been developed using Petrel Schlumberger software. The total resources of methane in the area amount to approximately 446.5 million of Nm3. Numerical simulations of methane production from the selected coal seams with hydraulic fracturing were conducted by means of Schlumberger ECLIPSE reservoir simulator. Based on the simulations, it was concluded that, in the first six months of the simulations, water is produced from the seams, which is connected with the decrease in the rock mass pressure. The process prompts methane desorption from the coal matrix, which in turn results in a total methane production of 76.2 million of Nm3 within the five-year period of the simulations, which constitutes about 17% of total methane resources (GIP). The paper also presents a detailed analysis of Polish legislation concerning the activities aimed at prospecting, exploring, and extracting the deposits of hydrocarbons.

Modified anaerobic digestion model No.1 (ADM1) for modeling anaerobic digestion process at different ammonium concentrations.

Anaerobic digestion (AD) is an established method for sustainable energy production. Anaerobic digestion model No.1 (ADM1) was used to simulate methane production (MP) and volatile fatty acid (VFA) concentrations at different ammonium concentrations. In accordance with the incomplete description of several biochemical reactions and the omission of several reaction processes, ADM1 was modified with the consideration of acetic acid inhibition and valeric acid existence. ADM1_ac (ADM1 added acetic acid inhibition) could obtain better simulation accuracy of MP (goodness-of-fit value=0.945), and VFA concentrations (goodness-of-fit values>0.39) were all higher than ADM1_original, but cannot explain the valeric acid production. ADM1_va (ADM1 added valeric acid existence) could achieve better simulation of valeric acid (achieving a breakthrough of zero), nevertheless the accuracy of propionic and butyric acids was poorer than ADM1_ac with differences between experimental and simulation values were 5%-10% lower. With both factors coordinated, MP and VFA concentrations could be simulated accurately by ADM1_ac_va (ADM1 added acetic acid inhibition and valeric acid existence), with the highest goodness-of-fit values (>0.85). The results of a verification experiment with ADM1_ac_va simulation further indicated that acetic acid inhibition and valeric acid as new component were both important in ADM1. PRACTITIONER POINTS: ADM1_ac could simulate MP and acetate, propionate and butyrate concentrations better. ADM1_va could explain the valerate production during AD of glucose. ADM1_ac_va could simulate AD process quite accurately, with the highest goodness-of-fit values (>0.85). Acetate inhibition and valerate existence were both important and should be considered in ADM1.

Gasification of rice hulls into methane by rumen fluid: A simulation study

Methane gas, the third widely-used source of energy, has been identified as a potential alternative to climate-change causing fuels. Due to increased climate change awareness, recent trends in researches have shifted their focus on optimizing production rates of methane gas. This study contributes to research by investigating the degree of conversion of rice hulls into methane using rumen fluid. We first identify the kinetic parameters defining therate of hydrolyzing rice hulls into glucose by implementing a semi-factorial experimental design. We then simulated methane production in four different reactor configurations. Historical data were extracted from different literatures and these were subsequently used in the simulation study. Simulation results showed that the continuous stirred tank reactor (CSTR) gave the shortest reaction time and highest methane yield which ranged from 7.1 9.5 mol/L and 3 4 days, respectively. In conclusion, this study provides an alternative approach to the conduct of understanding the optimal conditions necessary to achieve maximal methane gas production.

Modified Anaerobic Digestion Model No. 1 for modeling methane production from food waste in batch and semi-continuous anaerobic digestions

A modified Anaerobic Digestion Model No. 1 (ADM1) with optimized kinetic parameters was presented to model methane production in the anaerobic digestion of food waste. Experimental data from batch and semi-continuous fermentations were used to calibrate and verify the model. Modified ADM1 simulation was carried out using AQUASIM 2.0 software. Sensitivity analysis was used to identify and evaluate the most sensitive kinetic parameters during biogas production. The decay constant of microorganisms, the disintegration constant, the hydrolysis constant of carbohydrates, the Monod maximum specific substrate uptake rate, and the half-saturation constants affected biogas production significantly. The optimized values of these parameters were 0.001, 0.16, 3, 1 and 0.23, respectively. Optimization results were validated using batch and semi-continuous experiments. The modified ADM1 well-predicted methane production, with R2 values for the validation experiments all above 90%. These results can be used as basic data to simulate methane production in full-scale reactors.

Robust assessment of both biochemical methane potential and degradation kinetics of solid residues in successive batches

The well-known batch assay test is used worldwide to determine the biochemical methane potential (BMP) of solid substrates in a single batch but its use to estimate the degradation kinetics may lead to underestimations. To overcome this problem, a different approach was carried out to characterize simultaneously both BMP of solid substrates and their degradation kinetics in successive batches, i.e. after an acclimation period. In a second step, a simple model was developed based on the methane production curve in batch mode for dividing the organic matter of the substrate into three sub-fractions according to their degradation rates (rapid, moderate and slow). The protocol developed was applied to 50 different substrates and a database was built. This database includes: the overall BMP (mL CH4/g VS) and the degradation kinetics for each substrate, i.e. the global specific organic degradation rate (g VS/g VSS.d) along with the 3 sub-fractions and their specific degradation rates. The comparison with the BMP from the literature did not highlight significant difference with the BMP measured in this study. Furthermore, the degradation rates seem to be specific characteristics for each substrate and no clear correlation was found between the degradation kinetics and the kind of substrates. The information available in the database will be useful for the design and operation of anaerobic digesters: Optimization of the mix of co-substrates, choice of the applied OLR, simulation of methane production and of the rate of substrate degradation.

Kinetic Modeling of Mixed Culture Process of Anaerobic Co-digestion of Vegetable Wastes with Pistia stratiotes: A Scientific Attempt on Biomethanationy

As co-digestion of two wastes together lead to balanced environment for biomethanation an attempt has been made in the present study to co-digest vegetable waste (VW) and Pistia stratiotes (PS) to overcome the acidification problem during mono-digestion of VW. Optimization of important process parameters for anaerobic co-digestion was done based on Central Composite Design (CCD) based Response Surface Methodology (RSM). Thereafter, modeling of the anaerobic digestion was carried out using first order, modified Gompertz and unstructured segregated model to study the process behavior. First order and modified Gompertz models were found to fit with the observed methane profile with R2 of ~0.99. In case of unstructured segregated model important kinetic constants such as Khs, KSS, KVFA were derived from the model and the values were found to be 0.1 d-1, 2.3 g/L and 881.68 mg/L, respectively. Based on these kinetic parameters, simulated cumulative methane production was generated which matched well with the observed methane yield within the error band of ± 20%. This showed that the developed model could represent the overall process behaviour of this novel anaerobic co-digestion using mixed anaerobic culture as an inoculum.

NUMERICAL SIMULATION OF METHANE EMISSION FROM SUBARCTIC LAKE IN KOMI REPUBLIC (RUSSIA)

During last decades, a special attention has been paid to methane emission from lakes [Bastviken et al., 2004; Wik et al., 2016 and etc.] as one of the significant sources of this important greenhouse gas to the atmosphere. However, attempts to simulate methane production and efflux at the air-water interface are scarce [Stepanenko et al., 2011; Tan et al., 2015a; Tan et al., 2015b] and models proposed so far need further validation using observation datasets. In this study, we use the 1D + numerical model LAKE [Stepanenko et al., 2011; Stepanenko et al., 2016]. The LAKE model was applied to a small subarctic lake in the Seida study site (Komi Republic, Russia) for identification of the key factors influencing the surface CH4flux and its concentration in the lake. We carried out a calibration of biogeochemical constants involving qualitative considerations of the character of biogeochemical and physical processes occurring in the lake and aiming at a satisfactory agreement with observations, performed by the University of Eastern Finland (UEF) [Lind et al., 2009; Marushchak et al., 2016]. Comparing our model calibration results to earlier studies suggest that the crucial parameter of the model – methane production rate constant (Pnew, 0) – has similar values for lakes of different types in high latitudes.

Estimation of Methane Production Rates of Municipal Solid Wastes

In this study, anaerobic digestion tests for municipal solid wastes were performed in order to estimate their methane production rates. To simulate methane production rate, the first derivatives of the sigmoidal equations were calculated. The sigmoidal equations used were Gompertz and Logistic equations. Also, diauxic growth was employed to simulate methane production rate from municipal solid wastes. The equations were fitted to simulate methane production rate by nonlinear regression with a Marquardt-Levenberg algorithm. This is a statistical analysing methodology to minimize the sum of the squares of the differences between the predicted and measured values. Data fittings obtained by using the equations were compared statistically by using the RMSE (Root mean square error) and AIC (Akaike's information criterion). The equations derived from sigmoidal equations successfully described methane production rate for municipal solid wastes. RMSE and AIC were decreased significantly for the equations considering diauxic growth, compared to the equations without diauxic growth. These results showed that the equations derived from sigmoidal equations with diauxic growth can be a useful tool to simulate methane production rate for municipal solid wastes.

Quantifying wetland methane emissions with process-based models of different complexities

Abstract. Bubbling is an important pathway of methane emissions from wetland ecosystems. However the concentration-based threshold function approach in current biogeochemistry models of methane is not sufficient to represent the complex ebullition process. Here we revise an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model into a multi-substance model (CH4, O2, CO2 and N2) to simulate methane production, oxidation, and transport (particularly ebullition) with different model complexities. When ebullition is modeled with a concentration-based threshold function and if the inhibition effect of oxygen on methane production and the competition for oxygen between methanotrophy and heterotrophic respiration are retained, the model becomes a two-substance system. Ignoring the role of oxygen, while still modeling ebullition with a concentration-based threshold function, reduces the model to a one-substance system. These models were tested through a group of sensitivity analyses using data from two temperate peatland sites in Michigan. We demonstrate that only the four-substance model with a pressure-based ebullition algorithm is able to capture the episodic emissions induced by a sudden decrease in atmospheric pressure or by a sudden drop in water table. All models captured the retardation effect on methane efflux from an increase in surface standing water which results from the inhibition of diffusion and the increase in rhizospheric oxidation. We conclude that to more accurately account for the effects of atmospheric pressure dynamics and standing water on methane effluxes, the multi-substance model with a pressure-based ebullition algorithm should be used in the future to quantify global wetland CH4 emissions. Further, to more accurately simulate the pore water gas concentrations and different pathways of methane transport, an exponential root distribution function should be used and the phase-related parameters should be treated as temperature dependent.

Simulation experiments on gas production from hydrate-bearing sediments

Experiments were made on 58 sediment samples from four sites (1244, 1245, 1250 and 1251) of ODP204 at five temperature points (25, 35, 45, 55 and 65°C) to simulate methane production from hydrate-bearing sediments. Simulation results from site 1244 show that the gas components consist mainly of methane and carbon dioxide, and heavy hydrocarbons more than C2+ cannot be detected. This site also gives results, similar to those from the other three, that the methane production is controlled by experimental temperatures, generally reaching the maximum gas yields per gram sediment or TOC under lower temperatures (25 and 35°C). In other words, the methane amount could be related to the buried depth of sediments, given the close relation between the depth and temperature. Sediments less than 1200 m below seafloor are inferred to still act as a biogenic gas producer to pour methane into the present hydrate zone, while sedimentary layers more than 1200 m below seafloor have become too biogenically exhausted to offer any biogas, but instead they produce thermogenic gas to give additional supply to the hydrate formation in the study area.

Simulation of Methane Production from Hydrates by Depressurization and Thermal Stimulation

Recently methane hydrates have attracted attention due to their large quantity on the earth and their potential as a new resource of energy. This paper describes a one-dimensional mathematical model and numerical simulation of methane hydrate dissociation in hydrate reserves by both depressurization and thermal stimulation using a one-dimensional radial flow system (axisymmetric reservoir). A moving front that separates the hydrate reserve into two zones is included in this model. A numerical coordinate transformation method was used to solve the moving boundary problem. The partial differential equations were discretized into ordinary differential equations using the method of lines. Our simulations showed that the moving front location and the gas flow rate production are strong functions of the well pressure and reservoir temperature. The impermeable boundary condition at the reservoir results in very low temperature at the moving front and the formation of ice. The formation of ice, which plugs the po...

Comprehensive model of anaerobic digestion of swine manure slurry in a sequencing batch reactor

An improved mathematical model of anaerobic digestion in a sequencing batch reactor (SBR) process is developed. The model simulates the interactions between the biological, liquid (physicochemical) and gas phases. These phenomena are supported by experimental data. The advanced model assumes: (1) six populations of bacteria, including two populations of acetoclastic bacteria, are present in the bioreactor; (2) hydrogen in the gaseous phase is not in equilibrium with dissolved hydrogen; (3) production of volatile fatty acids (VFA) is regulated by the concentration of hydrogen in the liquid phase; and (4) the process is not affected by large concentrations of VFA and ammonia. The model contains a large number of kinetic constants and has the capability to predict the pH and methane production, as well as the concentrations of acetic (Ac), propionic (Pr) and butyric (Bu) acids; dissolved and gaseous hydrogen and soluble chemical oxygen demand (SCOD) in the SBR as a function of time. The model coefficients were determined for data, gathered from pilot scale digesters operated under psychrophilic conditions. The calibrated model was able to simulate methane production, SCOD, Ac and Pr acid concentrations in the dynamic conditions of an SBR, operated over a range of operating conditions.

Simulation of methane production in anaerobic rice soils by a simple two- pool model

Methane (CH4) is produced in flooded rice fields by anaerobic decomposition of applied organic residues, root-derived materials and native soil organic matter (SOM). Since CH4 is an important greenhouse gas it is important to understand, and to be able to model, the processes which produce it. Anoxic incubation of soils employed in the cultivation of irrigated rice, with and without the addition of various potentially-available organic substrates, provides information on potential CH4 emissions which can be incorporated into process-based models. In this study, a simple two-pool model is employed to simulate the CH4 production of a number of anaerobically-incubated rice soils, and their responses to amendment with a variety of organic substrates. The model differs from most accounts of SOM transformation in that kinetics are microbially-mediated rather than first-order. Simulation yields a reproduction of die general trends of CH4 production in response to amendments of acetate, glucose and rice straw.

Mathematical modeling and simulation of methane gas production in simulated landfill column reactors under sulfidogenic and methanogenic environments

A mathematical model was developed to simulate methane and carbon dioxide production from simulated landfill column reactors operated under sulfate reducing and methane producing conditions. The model incorporated governing equations which describe the chemical and biochemical processes responsible for the degradation of organic waste materials. These processes were hydrolysis, acidogenesis, methanogenesis and sulfidogenesis. The differential equations were numerically solved using Stella Researcher Software. The model was calibrated and verified using 700 days of gas production data from the simulated landfill column reactors. The calibrated hydrolysis rate constants for newspaper and sludge were found to be higher in sulfate reducing reactors as compared to methane producing reactors. The simulated methane production was quite accurate in all the reactors, but the predicted carbon dioxide production in the sulfate reducing reactors was not so accurate for the first 100 days, which may be attributed to the necessity of further governing equations. According to the sensitivity analysis, hydrolysis rate constants and moisture factors were the two most sensitive parameters controlling the gas production.