A method for simulating and evaluating the biological consumption of methane in marine sediments

Abstract

The present invention discloses a method for simulating and evaluating the biological consumption process of methane in marine sediments, belonging to the field of marine sediment geochemistry and marine geology research. The method is based on geochemical processes related to methane in sediments: a methanogenesis process related to organic matter degradation in bottom anaerobic sediments, an anaerobic oxidation process of methane involving methane in overlying fluids and sulfate in pore water, a reduction process of methane in overlying fluids and environmental iron and manganese ions, and an oxidation process of methane in surface sediments and oxygen. The method calculates the biological consumption efficiency of methane in sediments by biogeochemical modeling of the above reaction processes. The method not only considers the effects of the above processes on methane consumption in sediments, but also considers the effects of the distribution of microorganisms in sediments on methane consumption in sediments. The method is of great significance for studying the biological consumption efficiency of methane in sediments in different regions of the global ocean, as well as the potential impact of the marine methane cycle on the global greenhouse effect.

Description

Technical Field

[0001] The present invention belongs to the field of marine sediment geochemistry and marine geology research, and specifically relates to a method for simulating and evaluating the efficiency of marine sediment methane biological consumption taking into account microbial processes. Background Art

[0002] Methane is a significant atmospheric greenhouse gas, and changes in the global methane cycle have a significant impact on global temperature changes. Marine sediments are the world's largest reservoir of organic matter, and methane production, the final process in the evolution of marine organic matter, makes them a significant global methane source. The leakage of methane from sediments into seawater causes seawater acidification, impacting the marine ecosystem. Furthermore, large-scale sediment methane leakage events make it possible for the ocean to release methane into the atmosphere, contributing to the greenhouse effect. Therefore, modeling the methane consumption process in sediments is of great significance for studying the global ecological environment.

[0003] Methane-related geochemical processes in sediments include methanogenesis, anaerobic methane oxidation involving sulfate, methane reduction involving cations (iron and manganese ions), and methane oxidation in surface sediments. Methanogenesis is primarily related to the degradation of organic matter in sediments. Currently, organic matter degradation is primarily simulated using a continuous organic matter degradation model based on a gamma distribution. However, the gamma distribution cannot accurately capture the distribution of organic matter activity at different sites, resulting in inaccurate calculations of methanogenesis in sediments and an inability to adequately simulate the bottom methane cycle. Modeling of anaerobic methane oxidation involving sulfate primarily relies on a second-order kinetic model based on sulfate and methane concentrations, which fails to capture the dominant role of microorganisms in this process. Modeling of methane reduction involving cations is still limited, and quantitative modeling of methane consumption by this process is urgently needed.

[0004] Therefore, constructing an accurate sediment methane consumption model involving microorganisms is of great significance for studying the impact of sediment methane leakage on the ecological environment of marine water bodies and evaluating the contribution of the marine methane cycle process to the global carbon cycle. Summary of the Invention

[0005] To address the drawback of prior art in ignoring microbial abundance when establishing models to simulate methane consumption in sediments, the present invention proposes a simulation and evaluation method for the biological methane consumption process in marine sediments that takes into account microbial processes. This method comprehensively considers various methane-related processes in sediments and simulates and calculates the consumption rate of biological methane in sediments.

[0006] The present invention is implemented by adopting the following technical solution: a method for simulating and evaluating the biological consumption of methane in marine sediments, comprising the following steps:

[0007] Step A: Simulation of methanogenesis in bottom sediments:

[0008] A continuous marine organic matter degradation model based on lognormal distribution was constructed to simulate the organic matter degradation process in sediments. Then, based on the differences in the acceptor electron Gibbs free energy related to organic matter degradation in sediments, a reduction reaction zone based on an error function was constructed to quantitatively divide the methane-producing areas in the sediments. A numerical model of the methane production process in sediments was established to calculate the methane generation rate of this process. ; Step B, simulation of microbial-mediated sulfate methane consumption process:

[0009] The reaction rate of the anaerobic methane oxidation process involving sulfate is related to the sulfate concentration and methane concentration. Based on this, a second-order reaction kinetic model based on the sulfate and methane concentrations in pore water was constructed and modified to calculate the methane consumption rate of the process. ;

[0010] Step C: Simulation of the methane consumption process involving cations and the aerobic consumption process of methane in surface sediments:

[0011] (1) Based on the factors related to the methane reduction rate of cations, a metal cation methane consumption rate model considering the influence of microorganisms was constructed to calculate the methane consumption rate of the process. ;

[0012] (2) The methane aerobic consumption process is linearly related to the methane concentration. A first-order kinetic methane aerobic consumption kinetic model based on methane concentration is constructed to calculate the methane consumption rate of the process. ;

[0013] Step D: Combine the methane generation rate and methane consumption rate of each process calculated in steps A, B, and C to comprehensively evaluate the consumption rate of biogenic methane in the sediment.

[0014] Furthermore, the step D is specifically implemented in the following manner:

[0015] Step D1: Quantitatively estimate the total methane flux in the pore water overlying the bottom sediment according to Fick quantification ;

[0016] ,

[0017] Where, t For time, D me is the methane diffusion coefficient, C m is the methane concentration, fis the porosity, and the differential phase is the concentration gradient of methane at the lower boundary;

[0018] Step D2: Calculate the consumption rate of biogenic methane in the sediment to obtain the net change rate of methane in the sediment. R Net_Me :

[0019] ,

[0020] Integrate the above equation over depth and time to obtain the change in methane concentration in sediments: F Mc , which is expressed as follows:

[0021] ,

[0022] Where, t For time, x To simulate depth;

[0023] The biogenic methane consumption rate in sediments is Ratio BM It is expressed as follows:

[0024] ,

[0025] The purpose of evaluating the methane interception efficiency of sediment biogeochemical processes is achieved by calculating the methane release flux in surface sediments.

[0026] Furthermore, in step A, the activity distribution of organic matter is described by lognormal distribution, and a continuous marine organic matter degradation model of lognormal distribution is constructed in combination with the decay equation:

[0027] ,

[0028] Where, G ( t ) represents the change of organic matter content over time, G (0) represents the content of organic matter at the sediment-seawater interface, k Indicates the activity of organic matter. t Indicates time, g ( k ,0) is lognormal distribution;

[0029] ,

[0030] In the formula, ln m It is ln k The average value of s 2 It is ln k The variance of mIndicates the overall size of organic matter activity, s Indicates the range of organic matter activity.

[0031] Furthermore, in step A, a conversion function of organic matter degradation from sulfate reduction process to methanogenesis process is constructed by using an error function. f s , quantitatively divide the methane-producing areas in the sediments as follows:

[0032] ,

[0033] Where, erfc is the error function, [ SO 4 2− ] is the sulfate concentration, C S * is the threshold concentration of sulfate, b To control the conversion adjustment coefficient, when organic matter is degraded by sulfate, f s is 1; when organic matter is degraded by methanogenesis, f s is 0.

[0034] Furthermore, in step A, the numerical model of the methane production process constructed is as follows:

[0035] ,

[0036] Where, R ME is the methanogenesis rate, R OM is the organic matter degradation rate, .

[0037] Furthermore, in step B, the reaction rate of the anaerobic methane oxidation process involving sulfate is expressed as the product of sulfate concentration and methane concentration. The second-order reaction kinetic model of sulfate and methane concentration in pore water is expressed as follows:

[0038] ,

[0039] Where, k AOM is the reaction kinetic coefficient, [ C m ] is the methane concentration, [ C s ] is the sulfate concentration.

[0040] Furthermore, in step B, the model is radially corrected, as shown below:

[0041] ,

[0042] Where, F M is the abundance of microorganisms in sediments, F K The influence of environmental energy distribution on the reaction process:

[0043] ,

[0044] Where, Δ G r represents the Gibbs energy of the AOM reaction, Δ G BQ It represents the minimum bioenergy supply required to maintain the anaerobic oxidation of methane with the participation of sulfate. x represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant and T represents the temperature.

[0045] Furthermore, in step C, a cationic methane consumption rate model is constructed as follows:

[0046] ,

[0047] Where, k NM is the second-order reaction kinetic coefficient, [ C n ] is the cation concentration, [ C s ] is the sulfate concentration, F nM is the distribution abundance of microorganisms involved in the cation-consuming methane process in sediments, F nK The influence of environmental energy distribution on the reaction process:

[0048] ,

[0049] Where, Δ G r represents the Gibbs energy of the AOM reaction, Δ G nQ represents the minimum bioenergy supply required to sustain the cationic methane consumption process, x represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant and T represents the temperature.

[0050] Furthermore, in step C, the methane aerobic consumption kinetic model is expressed as follows:

[0051] ,

[0052] Where, R AeOM is the methane redox rate, i.e. the methane consumption rate, k OM is the first-order reaction kinetic coefficient, [ C m ] is the cation concentration.

[0053] Compared with the prior art, the advantages and positive effects of the present invention are:

[0054] This approach fully considers all geochemical processes involved in methane in sediments. The modeling process incorporates the distribution of electron acceptor Gibbs free energy, the distribution of microorganisms, and the distribution of the bioenergy field that sustains microbial survival. Methanogenesis in sediments is simulated using a continuous organic matter degradation model based on a lognormal distribution. The model for anaerobic methane consumption involving sulfate fully considers microbial distribution and the supply of the energy field. The methane consumption process involving cations fully considers cation concentration, the abundance of cation-consuming microorganisms, and the corresponding energy field. Furthermore, a first-order kinetic model for methane oxidation was established. This approach overcomes the drawback of other models that ignore microbial abundance when simulating methane consumption in sediments. This provides important technical support for subsequent assessments of the efficiency of sediment methane interception during marine methane leaks and a theoretical basis for studying the impact of marine methane leaks on the global carbon cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The present invention is implemented by the method of the flow chart. DETAILED DESCRIPTION

[0056] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described below with reference to the accompanying drawings and embodiments. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can also be implemented in other ways than those described herein. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0057] The present invention proposes a simulation and evaluation method for the efficiency of methane bioconsumption in marine sediments taking into account microbial processes, such as Figure 1 As shown, the following steps are included:

[0058] Step A: Numerical simulation of the methane production process in bottom sediments:

[0059] Step A1: Methanogenesis in sediments is related to organic matter degradation. The distribution characteristics of organic matter activity at different sites were characterized using a log-normal distribution. Combined with the decay equation, a continuous marine organic matter degradation model based on the log-normal distribution was constructed to simulate the organic matter degradation process in sediments.

[0060] The organic matter degradation model is expressed as follows: (1)

[0061] Where, G ( t ) represents the change of organic matter content over time, G (0) represents the content of organic matter at the sediment-seawater interface, k Indicates the activity of organic matter. t Indicates time, g ( k ,0) is a log-normal distribution, as follows: (2)

[0062] In the formula, ln m It is ln k The average value of s 2 It is ln k The variance of m Reflects the overall size of organic matter activity (i.e. the higher the organic matter activity, the m The larger the value), s The range of organic matter activity is related to the amount of organic matter components. The degradation rate of organic matter can be obtained by combining equations (1) and (2) and taking the derivative of the time term. R OM .

[0063] Step A2: Considering the differences in the acceptor electron Gibbs free energy related to organic matter degradation in the sediment, a reduction reaction zone based on the error function is constructed to quantitatively delineate the methanogenic areas in the sediment;

[0064] The degradation of organic matter in sediments is usually caused by a variety of reduction processes (e.g., iron reduction, sulfate reduction, and carbon dioxide reduction). Studies have shown that the degradation of organic matter in sediments through methanogenesis occurs primarily in environments with sulfate concentrations below 1 mM. Therefore, this example uses an error function to construct a conversion function for organic matter degradation from sulfate reduction to methanogenesis. , as shown below: (3)

[0065] Where, erfc is the error function, [ SO 42− ] is the sulfate concentration, C S * is the threshold concentration of sulfate (~1mM), b To control the conversion adjustment coefficient, when organic matter is degraded by sulfate, f s is 1; conversely, when organic matter is degraded by methanogenesis, f s is 0.

[0066] Step A3: Combine steps A1 and A2 to establish a numerical model of the methane production process in sediments and calculate the methane flux as follows: (4)

[0067] Where, R ME is the methanogenesis rate, R OM is the organic matter degradation rate.

[0068] Step B: Simulation of the microbial-mediated methane sulfate consumption process:

[0069] Step B1: First, a second-order reaction kinetic model based on the concentrations of sulfate and methane in pore water is constructed;

[0070] The reaction rate of the anaerobic oxidation of methane (AOM) process involving sulfate is primarily related to the sulfate and methane concentrations. When the methane and sulfate concentrations are higher, the AOM effect becomes stronger, and the rate of methane and sulfate consumption increases. The reaction rate of the AOM process can be expressed as the product of the sulfate and methane concentrations, as shown below: (5)

[0071] Where, is the methane consumption rate of the AOM process, k AOM is the reaction kinetic coefficient, [ C m ] is the methane concentration, [ C s ] is the sulfate concentration.

[0072] Step B2: Considering the influence of environmental energy distribution on microbial activity and the influence of microbial abundance on reaction intensity, the minimum bioenergy required to maintain AOM is approximately 11 kJ mol -1 , while the available bioenergy in the sediment is limited. At the same time, microbial abundance is also an important factor affecting the intensity of the reaction. The radial correction of the model constructed in B1 is as follows: (6)

[0073] Where, F M is the abundance of microorganisms in sediments, F K is the influence of environmental energy distribution on the reaction process, which is expressed as follows: (7)

[0074] Where, Δ G r represents the Gibbs energy of the AOM reaction, Δ G BQ It represents the minimum bioenergy supply required to maintain the anaerobic oxidation of methane with the participation of sulfate. x represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant and T represents the temperature.

[0075] Step C: Simulation of the methane consumption process involving cations and the aerobic consumption process of methane in surface sediments:

[0076] Step C1: The rate at which metal cations (iron and manganese ions) participate in the sediment methane reduction process is mainly related to the methane concentration and cation concentration in the pore water. At the same time, the environmental energy supply and the abundance of the corresponding microorganisms participating in the reaction also have an impact. Based on this, the metal cation methane consumption rate considering the influence of microorganisms is constructed ( R NM ) model, as follows: (8)

[0077] Where, k NM is the second-order reaction kinetic coefficient, [ C n ] is the cation concentration, [ C s ] is the sulfate concentration, F nM is the distribution abundance of microorganisms involved in the cation-consuming methane process in sediments, F nK is the influence of environmental energy distribution on the reaction process, which is expressed as follows: (9)

[0078] Where, Δ G r represents the Gibbs energy of the AOM reaction, Δ G nQ represents the minimum bioenergy supply required to sustain the cationic methane consumption process, x represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant and T represents the temperature.

[0079] Step C2: Unlike the relatively slow consumption of methane in anaerobic sediments, the methane oxidation process involving oxygen in surface sediments or bottom seawater is extremely rapid. The aerobic consumption of methane with oxygen is mainly linearly related to the methane concentration. Based on this, a first-order kinetic methane aerobic consumption model based on methane concentration is constructed. The methane redox rate ( R AeOM ) is represented by the following model: (10)

[0080] Where, is the methane redox rate, also known as the methane consumption rate, k OM is the first-order reaction kinetic coefficient, [ C m ] is the cation concentration.

[0081] Step D: Comprehensively evaluate the consumption rate of biogenic methane in sediments:

[0082] Step D1: First, quantitatively estimate the total methane flux in the pore water overlying the bottom sediment according to Fick's quantification. F Me ; (11)

[0083] Where, t For time, D me is the methane diffusion coefficient, C m is the methane concentration, f is the porosity, and the differential phase is the concentration gradient of methane at the lower boundary.

[0084] Step D2: Calculate the biogenic methane consumption rate in the sediment based on the methane generation and consumption rates calculated in A, B, and C to obtain the net change rate of methane in the sediment ( R Net_Me ), its model is expressed as follows: (12)

[0085] By integrating Equation (12) over depth and time, the change in methane concentration in sediments can be obtained ( F Mc ), which is expressed as follows: (13)

[0086] Where, t For time, x To simulate depth.

[0087] According to equations (11) and (13), the biogenic methane consumption rate in sediments can be calculated ( Ratio BM ), which is expressed as follows: (14)

[0088] Then, by calculating the methane release flux in surface sediments, the methane interception efficiency of sediment biogeochemical processes can be evaluated.

[0089] The above description is merely a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any person skilled in the art may utilize the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes for application in other fields. However, any simple modification, equivalent change, and modification of the above embodiments made in accordance with the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for simulating and evaluating the biological consumption of methane in marine sediments, characterized in that: The following steps are involved: Step A: Simulation of methanogenesis in bottom sediments: A continuous marine organic matter degradation model based on lognormal distribution was constructed to simulate the organic matter degradation process in sediments. Then, based on the differences in the acceptor electron Gibbs free energy related to organic matter degradation in sediments, a reduction reaction zone based on an error function was constructed to quantitatively divide the methane-producing areas in the sediments. A numerical model of the methane production process in sediments was established to calculate the methane generation rate of this process. ; Step B: Simulation of the microbial-mediated methane sulfate consumption process: The reaction rate of the anaerobic methane oxidation process involving sulfate is related to the sulfate concentration and methane concentration. Based on this, a second-order reaction kinetic model based on the sulfate and methane concentrations in pore water was constructed and modified to calculate the methane consumption rate of the process. ; Step C: Simulation of the methane consumption process involving cations and the aerobic consumption process of methane in surface sediments: (1) Based on the factors related to the methane reduction rate of cations, a metal cation methane consumption rate model considering the influence of microorganisms was constructed to calculate the methane consumption rate of the process. ; (2) The methane aerobic consumption process is linearly related to the methane concentration. A first-order kinetic methane aerobic consumption kinetic model based on methane concentration is constructed to calculate the methane consumption rate of the process. ; Step D: Combine the methane generation rate and methane consumption rate of each process calculated in steps A, B, and C to comprehensively evaluate the consumption rate of biogenic methane in the sediment. Specifically: Step D1: Quantitatively estimate the total methane flux in the pore water overlying the bottom sediment according to Fick quantification ; ; Where t is time, D me is the methane diffusion coefficient, C m is the methane concentration, φ is the porosity, and the differential phase is the concentration gradient of methane at the lower boundary; Step D2: Calculate the consumption rate of biogenic methane in the sediment to obtain the net change rate of methane in the sediment R Net_Me : ； Integrate the above formula over depth and time to obtain the change in methane concentration in sediments: Mc , which is expressed as follows: ； Where t is time and x is simulation depth; The biogenic methane consumption rate in sediments is Ratio BM It is expressed as follows: ; The purpose of evaluating the methane interception efficiency of sediment biogeochemical processes is achieved by calculating the methane release flux in surface sediments.

2. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 1, wherein: In step A, the activity distribution of organic matter is described by log-normal distribution, and a continuous marine organic matter degradation model of log-normal distribution is constructed in combination with the decay equation: ; Where G(t) represents the change of organic matter content over time, G(0) represents the content of organic matter at the sediment-seawater interface, k represents the activity of organic matter, t represents time, and g(k,0) is a log-normal distribution; ; Where ln μ is the average value of ln k, σ 2 is the variance of ln k, μ represents the overall size of organic matter activity, and σ represents the range of organic matter activity.

3. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 2, wherein: In step A, the conversion function f from the sulfate reduction process to the methanogenesis process of organic matter degradation is constructed by the error function. s , quantitatively divide the methane-producing areas in the sediments as follows: ; Where erfc is the error function, [SO4 2− ] is the sulfate concentration, C S * is the threshold concentration of sulfate, b is the adjustment coefficient for controlling conversion, when organic matter is degraded by sulfate, f s is 1; when organic matter is degraded by methanogenesis, f s is 0.

4. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 3, wherein: In step A, the numerical model of the methane production process is constructed as follows: ; Where R ME is the methanogenesis rate, R OM is the organic matter degradation rate, .

5. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 1, wherein: In step B, the reaction rate of the anaerobic methane oxidation process involving sulfate is expressed as the product of sulfate concentration and methane concentration. The second-order reaction kinetic model of sulfate and methane concentrations in pore water is expressed as follows: ; Where k AOM is the reaction kinetic coefficient, [C m ] is the methane concentration, [C s ] is the sulfate concentration.

6. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 5, wherein: In step B, the model is corrected radially, as shown below: ; Where, F M is the abundance of microorganisms in sediments, F K The influence of environmental energy distribution on the reaction process: ; Where ΔG r represents the Gibbs energy of the AOM reaction, ΔG BQ represents the minimum bioenergy supply required to maintain the anaerobic oxidation of methane with the participation of sulfate, χ represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant, and T represents the temperature.

7. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 1, wherein: In step C, the cationic methane consumption rate model is constructed as follows: ; Where k NM is the second-order reaction kinetic coefficient, [C n ] is the cation concentration, [C s ] is the sulfate concentration, F nM is the distribution abundance of microorganisms involved in the cation-consuming methane process in sediments, F nK The influence of environmental energy distribution on the reaction process: ; Where ΔG r represents the Gibbs energy of the AOM reaction, ΔG nQ represents the minimum bioenergy supply required to maintain the cationic methane consumption process, χ represents the number of protons transported across the cell membrane during the reaction, R represents the gas constant, and T represents the temperature.

8. The method for simulating and evaluating the biological consumption of methane in marine sediments according to claim 1, wherein: In step C, the methane aerobic consumption kinetic model is expressed as follows: ; Where R AeOM is the methane redox rate, i.e. the methane consumption rate, k OM is the first-order reaction kinetic coefficient, [C m ] is the cation concentration.

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