Biological carbon source optimization method and application of biological carbon source optimization method in goaf in-situ purification of high-sulfate mine water

Abstract

The invention discloses a biological carbon source optimization method and application of the biological carbon source optimization method to in-situ purification of high-sulfate mine water in a goaf. Preliminarily screening cheap degradable carbon sources, and determining the material cost of each carbon source; measuring and evaluating the carbon release performance of the carbon source and the availability degree and activity of the sulfate reducing bacteria; and constructing a carbon source optimization multi-index comprehensive evaluation model according to the evaluation indexes, and selecting an optimal carbon source. And finally, preparing a structured cage body, punching right above a coal mine goaf, directly putting the cage body into the goaf through a drill hole, introducing nitrogen into high-sulfate mine water to remove oxygen, discharging the high-sulfate mine water into the goaf, and discharging low-sulfate low-suspended-matter mine water from an outlet of the goaf. According to the method, the underground mining space of the coal mine is fully utilized, the mine water treatment cost can be greatly reduced, the sulfate removal efficiency can be improved, green low-carbon treatment of the mine water is promoted, and efficient synergistic removal of sulfate and suspended solids is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal mine environment governance, water treatment and microbial remediation, and particularly relates to a biological carbon source optimization method and application thereof to in-situ purification of high-sulfate mine water in a goaf. BACKGROUND

[0002] With the development of human economic living standards, the demand for energy increases, thereby increasing the demand for mineral resources. Coal occupies a dominant position in the main structure of energy in China, and in the process of diversification of energy structure, coal will still be the cornerstone of guaranteeing national energy security and stability in a long period. In the process of coal production, a large amount of mine water is inevitably generated. In the process of formation of mine water, water-rock interaction is carried out with coal-bearing strata and overburden rock, especially with sulfur-containing coal seams, thereby forming mine water with high water inflow and high sulfate. If the high-sulfate mine water is directly discharged to the ground without treatment, it will cause environmental hazards such as soil salinization, vegetation yellowing and groundwater pollution. Due to the high water inflow of mine water, the treatment capacity of the ground mine water treatment station has been exceeded, so part of the mine water can be discharged to the abandoned goaf in the underground coal mine. After the coal mining face is completed, a huge abandoned mining space and a natural closed environment are formed. If the mine water is discharged into the goaf, the underground space can be fully utilized, and the mine water can be treated.

[0003] Sulfate-reducing bacteria can reduce SO4 2- to H2S through the dissimilatory sulfate reduction pathway. The collapsed coal and rock in the goaf is rich in clay minerals and has strong adsorption, and provides porous adsorption sites for sulfate-reducing bacteria. Sulfate-reducing bacteria are strict anaerobic microorganisms, and their growth is limited by the redox environment and carbon source. In the process of treating mine water in the goaf, the reduction environment of the mine water can be enhanced by injecting nitrogen into the goaf, thereby strengthening the removal efficiency of sulfate in the mine water. However, the growth of sulfate-reducing bacteria requires continuous energy supply, and only enhancing the anaerobic environment without strengthening the carbon source limits the growth of sulfate-reducing bacteria. When the original carbon source in the goaf is consumed, the removal efficiency of SO4 2- in the mine water will be significantly reduced. However, most of the carbon sources for studying sulfate-reducing bacteria are preferentially selected as sodium lactate, acetic acid, glucose and other expensive carbon sources. Although sulfate-reducing bacteria are more efficient, they are not economical and practical. Therefore, according to the existing crops in the coal mine, the most suitable and low-cost carbon source for sulfate-reducing bacteria is selected for in-situ purification of high-sulfate mine water in the goaf, which can reduce the cost of mine water treatment while improving the removal efficiency of sulfate. The existing researches do not evaluate the adaptability of carbon source selection under the in-situ conditions of coal mine, thereby resulting in high cost of mine water treatment. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a biological carbon source optimization method and its application in in-situ purification of high sulfate mine water in goaf, which solves the problems of high cost, low sulfate removal rate and expensive carbon source, etc., fully utilizes the underground mining space and the on-site situation of the coal mine, greatly reduces the mine water treatment cost and improves the sulfate removal efficiency, and promotes the realization of green and low-carbon mine water treatment.

[0005] To achieve the above-mentioned object, the present application is implemented by the following technical solutions:

[0006] A biological carbon source optimization method, comprising the following steps:

[0007] Step 1: investigate the cheap agricultural by-product resources around the coal mine, preliminarily screen the cheap degradable carbon sources, and determine the material cost Y (yuan / kg) of each carbon source;

[0008] Step 2: analyze the carbon release performance of the multiple carbon sources, evaluate the carbon release performance of the carbon sources through experimental determination: the soluble organic carbon release rate RR DOC (mg / (L·h)), the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)), the specific surface area A S (m 2 / g), the cumulative release amount of heavy metals HM (mg / L), the total concentration of small molecule organic matter SOM (mg / L), the fluorescence biological index BIX, and E2 / E3;

[0009] Step 3: analyze the availability degree and activity of sulfate-reducing bacteria through experiments, and evaluate the activity of sulfate-reducing bacteria under different carbon source conditions according to the following indexes: the SO4 2- removal rate η (%), and the sulfite reductase activity X SIR (U / ml);

[0010] Step 4: classify the material cost, carbon release performance indexes and sulfate-reducing bacteria activity indexes determined in steps 1, 2 and 3, wherein the positive indexes are the soluble organic carbon release rate RR DOC , the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)), the SO4 2- removal rate η, the specific surface area A S (m 2 / g), the sulfite reductase activity X (U / ml), the total concentration of small molecule organic matter SOM (mg / L), the fluorescence biological index (BIX), and E2 / E3 (Euv), the negative indexes are the material cost Y (yuan) and the release amount of heavy metals HM (mg / L), a carbon source optimization multi-index comprehensive evaluation model is constructed according to the classification indexes, and the score C is obtained in combination.i An optimal carbon source for purifying high sulfate mine water in situ is selected, wherein,

[0011]

[0012] In the formula, C i represents the degree to which the carbon source material i approaches the optimal carbon source material, i.e., the model score, and takes a value in the range [0, 1]; represents the distance of the carbon source material i from the positive ideal solution; represents the distance of the carbon source material i from the negative ideal solution;

[0013] Further, the analysis experiment step of the carbon release performance in the second step is as follows:

[0014] (1) 10 g of the dried carbon source material is weighed and placed in a non-woven fabric tea bag, the tea bag is placed in a glass bottle containing 1000 mL of deionized water, and the glass bottle is placed in a shaking table at 25°C and 175 rpm, and samples are taken at 1, 4, 8, 12, 24, 48, 72, 96 and 120 h after the start of the experiment;

[0015] (2) The water sample is tested for soluble organic carbon concentration (DOC), and the soluble organic carbon release rate RR DOC (mg / (L·h)) and the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)) are calculated according to the following formula,

[0016]

[0017] In the formula, t is the reaction time (h), V is the water volume (L), and m is the sample mass (g);

[0018] (3) The heavy metal release amount HM (mg / L) of the carbon source material is tested using ICP-MS, the total concentration of small molecule organic matter SOM (mg / L) is tested using a gas chromatograph-mass spectrometer and a liquid chromatograph-tandem mass spectrometer, and the fluorescence biological index BIX and E2 / E3 (Euv) are tested using a three-dimensional fluorescence spectrometer;

[0019] (4) The BET specific surface area A S (m 2 / g) of the solid material after vacuum freeze-drying is measured, and the greater the specific surface area, the more conducive to microbial adsorption.

[0020] Further, the experiment step of the analysis of the sulfate-reducing bacteria availability degree and activity in the third step is as follows:

[0021] (1) The high sulfate mine water is injected with nitrogen to remove oxygen, 10g of dried carbon source material is weighed, wrapped with non-woven fabric, placed in a glass bottle, 1000mL of deoxygenated mine water is added, then centrifuged sulfate-reducing bacteria liquid is inoculated at a ratio of 5% (v / v), placed in a 25℃ constant temperature incubator for static culture, and samples are taken on the 1st, 3rd, 5th, 7th, 10th, 15th and 20th day after the start of the experiment;

[0022] (2) The SO4 2- concentration (mg / L) and sulfite reductase activity X SIR (U / ml) of each water sample are tested, and the SO4 2- removal rate η is calculated according to the following formula, wherein,

[0023]

[0024] In the formula, η is the SO4 2- removal rate, C SO4 (T) is the SO4 2- concentration on the Tth day, C SO4 (0) is the initial SO4 2- concentration.

[0025] Further, a carbon source construction multi-index comprehensive evaluation model is constructed in the fourth step, which is a TOPSIS multi-index comprehensive evaluation model based on double weights of subjective weighting method and entropy weight method, and the specific steps are as follows:

[0026] (1) There are n carbon source candidate schemes, and there are m=10 evaluation indexes. Let the original index matrix be:

[0027] X=[x ij ] n×m

[0028] In the formula: x ij represents the original value of the ith carbon source on the jth index;

[0029] (2) The evaluation indexes are normalized in the positive direction,

[0030] Positive indexes:

[0031]

[0032] Negative indexes:

[0033]

[0034] The normalized matrix is: R=[r ij ]

[0035] In the formula: min(x j) represents the original minimum value of the j-th index of all carbon sources, max(x j ) represents the original maximum value of the j-th index of all carbon sources, r ij This represents the value of the i-th carbon source after normalization to the j-th index;

[0036] (3) Calculate the weights

[0037] Based on expert scoring, manual weighting was applied: Y: 0.2, η: ​​0.2, RR DOC : 0.12, DOC cum 0.12, A S 0.08, X SIR =0.08, HM: 0.08, SOM: 0.05, BIX: 0.035, EUV: 0.035, satisfying:

[0038]

[0039] In the formula, This represents the subjective weight of the j-th indicator;

[0040] The objective weights are calculated using the entropy weight method.

[0041] For the normalized matrix R = [r ij Each indicator is standardized to obtain the proportion of the i-th carbon source under the j-th indicator:

[0042]

[0043] Then, the entropy values ​​of each indicator are calculated based on the information entropy theory.

[0044]

[0045] Then, calculate the redundancy of the j-th indicator based on the entropy value; the higher the redundancy, the greater the weight.

[0046] d j =1-e j

[0047] The redundancy of all indicators is weighted and normalized to obtain the objective weight of each indicator.

[0048]

[0049] The subjective weights and objective weights are weighted and combined to obtain the comprehensive weight:

[0050]

[0051] In the formula: p ij Indicates the first The proportion of the jth index in the total carbon source, e j The information entropy of the jth index, e j ∈[0,1]; k represents a normalization constant; e j The redundancy of the jth index; The objective weight of the jth index; α is the subjective and objective weight factor, and the value range is [0,1]; w j The comprehensive weight of the jth index.

[0052] (4) Calculate the positive ideal solution and the negative ideal solution, that is, the optimal and worst

[0053] According to the comprehensive weight, construct a weighted normalized matrix: v ij = r ij ·w j

[0054] Positive ideal solution (maximum value):

[0055] A + = {max(v 1j ,…,v nj )}

[0056] Negative ideal solution (minimum value):

[0057] A - = {min(v 1j ,…,v nj )}

[0058] In the formula, A + represents the maximum value of the matrix v ij , that is, the most perfect, most suitable, and most ideal carbon source material; A - represents the minimum value of the matrix v ij , that is, the worst carbon source material.

[0059] (5) Calculate the distance and closeness degree

[0060] Calculate the distance between carbon source material i and the positive ideal solution:

[0061]

[0062] Calculate the distance between carbon source material i and the negative ideal solution:

[0063]

[0064] According to the TOPSIS evaluation method, calculate the degree to which the ith carbon source is closer to the optimal carbon source and farther from the worst carbon source, and finally select the carbon source material with the largest score C i

[0065] ​

[0066] In the formula, represents the distance of the carbon source material i from the positive ideal solution; represents the distance of the carbon source material i from the negative ideal solution;C i represents the degree of the carbon source material i approaching the optimal carbon source material, and the value range is [0, 1].

[0067] The application of the carbon source obtained by the preferred method to in-situ purification of high-sulfate mine water in a goaf is specifically as follows:

[0068] First step: the carbon source material obtained by the biological carbon source optimization method is prepared into a structured cage with a diameter of 5-10 cm to ensure the structure stability and excellent slow-release performance;

[0069] Second step: according to the technical solution of CN202410221310.X, a suitable position in the goaf is selected, a water quality monitoring system and a gas monitoring system are arranged, and a nitrogen production device is installed;

[0070] Third step: a hole is drilled directly above the goaf, and the cage is directly put into the goaf through the hole;

[0071] Fourth step: after the high-sulfate mine water is deoxidized by nitrogen, the water is discharged into the goaf, and low-sulfate and low-suspended solid mine water flows out from the outlet of the goaf.

[0072] Beneficial effects:

[0073] Compared with the prior art, the carbon source optimization method for in-situ purification of high-sulfate mine water in a goaf has the following beneficial effects:

[0074] 1. The application of the preferred agricultural and sideline products to in-situ purification of high-sulfate mine water in a goaf can remove 95% of the suspended solids and 50% of the sulfates in the water, and the mine water treated in the goaf can be directly reused underground or discharged to a mine water treatment station for desalination, thereby eliminating the “precipitation + filtration” link in the pre-treatment end of the mine water, greatly reducing the cost of coal mine water treatment, and realizing the resource utilization of agricultural waste and contributing to the local agricultural development.

[0075] 2. The ground mine water treatment plant has a water treatment cost of 16 yuan per ton, and compared with the ground mine water treatment plant for treating high-sulfate mine water, the carbon source optimization method for in-situ purification of high-sulfate mine water in a goaf has a water treatment cost of 5 yuan per ton, which can save 5.28 thousand yuan per day, and the construction cost can be saved after 190 days of operation. The actual application significantly reduces the treatment cost and has good application effect. BRIEF DESCRIPTION OF DRAWINGS

[0076] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0077] Figure 1 A multi-index comprehensive evaluation model is preferred for the carbon source;

[0078] Figure 2 A flowchart for purifying high-sulfate mine water in situ in a goaf using the preferred carbon source;

[0079] Figure 3 An implementation schematic diagram of in-situ purification of high-sulfate mine water in a goaf. DETAILED DESCRIPTION

[0080] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0081] The preferred embodiments of the present application will be described in detail below with reference to the drawings in the specification.

[0082] Embodiment 1

[0083] A biological carbon source optimization method, comprising the following steps:

[0084] Step 1: Investigate the cheap agricultural by-product resources around the coal mine, preliminarily screen the cheap degradable carbon sources, and determine the material cost Y (yuan / kg) of each carbon source;

[0085] Specifically, the agricultural by-product resources in the location of the coal mine are closely related to the local dominant crops and climate conditions; according to the division of coal mine regions in China, there are five types of coal mines in Northeast China, North China, Northwest China, Southwest China and South China. According to the cost comparison of agricultural products, 10 kinds of relatively cheap agricultural products are selected. The relatively cheap agricultural products in the five coal mine regions in China are shown in Table 1 below.

[0086] Table 1 List of different agricultural products in different regions

[0087]

[0088]

[0089] Second step: carbon release performance analysis of multiple carbon sources, evaluate the carbon release performance of carbon sources through experimental determination: soluble organic carbon release rate RR DOC (mg / (L·h)), soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), specific surface area A S (m 2 / g), heavy metal cumulative release amount HM(mg / L), total concentration of small molecule organic matter SOM(mg / L), fluorescence biological index BIX, E2 / E3;

[0090] Third step: analyze the availability degree and activity of sulfate-reducing bacteria through experiments, and evaluate the activity of sulfate-reducing bacteria under different carbon source conditions according to the following indexes: SO4 2- removal rate η(%), sulfite reductase activity X SIR (U / ml);

[0091] Fourth step: classify the material cost, carbon release performance index and sulfate-reducing bacteria activity index determined in the first step, the second step and the third step, wherein the positive indexes are soluble organic carbon release rate RR DOC , soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), SO4 2- removal rate η, specific surface area A S (m 2 / g), sulfite reductase activity X(U / ml), total concentration of small molecule organic matter SOM(mg / L), fluorescence biological index(BIX), E2 / E3(Euv), and the negative indexes are material cost Y(yuan), heavy metal release amount HM(mg / L), and a carbon source optimization multi-index comprehensive evaluation model is constructed according to the classification indexes, and then combined with the score C i to select an optimal carbon source for in-situ purification of high sulfate mine well water, wherein,

[0092]

[0093] In the formula, C i represents the degree to which the carbon source material i approaches the optimal carbon source material, i.e. the model score, and the value range is [0, 1]; represents the distance between the carbon source material i and the positive ideal solution; represents the distance between the carbon source material i and the negative ideal solution;

[0094] Further, the analysis experiment steps of the carbon release performance in the second step are as follows:

[0095] (1) 10 g of the dried carbon source material was weighed into a non-woven cloth tea bag, the tea bag was placed in a glass bottle containing 1000 mL of deionized water, and the glass bottle was placed in a shaker at 25°C and 175 rpm, and samples were taken at 1, 4, 8, 12, 24, 48, 72, 96 and 120 h after the start of the experiment;

[0096] (2) The water sample was tested for soluble organic carbon concentration (DOC), and the soluble organic carbon release rate RR was calculated according to the following formula DOC (mg / (L·h)) and the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)) were calculated according to the following formula

[0097]

[0098] wherein t is the reaction time (h), V is the volume of the water body (L), and m is the mass of the sample added (g);

[0099] (3) The release amount of heavy metals HM (mg / L) of the carbon source material was tested using ICP-MS, the total concentration of small molecule organic matter SOM (mg / L) was tested using a gas chromatograph-mass spectrometer and a liquid chromatograph-tandem mass spectrometer, and the fluorescence biological index BIX and E2 / E3 (Euv) were tested using a three-dimensional fluorescence spectrometer;

[0100] (4) The BET specific surface area A S (m 2 / g) of the solid material after vacuum freeze-drying was determined, and the greater the specific surface area, the more conducive to microbial adsorption.

[0101] Further, the experimental steps for analyzing the availability and activity of the sulfate-reducing bacteria in the third step are as follows:

[0102] (1) The high-sulfate mine water was deoxygenated by nitrogen injection, 10 g of the dried carbon source material was weighed, packaged with non-woven cloth, and placed in a glass bottle, 1000 mL of deoxygenated mine water was added, and then the centrifuged sulfate-reducing bacteria liquid was inoculated at a proportion of 5% (v / v), and the glass bottle was placed in a constant temperature incubator at 25°C for static culture, and samples were taken at 1, 3, 5, 7, 10, 15 and 20 days after the start of the experiment;

[0103] (2) The SO4 2- concentration (mg / L) and the sulfite reductase activity X SIR (U / ml) of each water sample were tested, and the SO4 2- removal rate η was calculated according to the following formula, wherein

[0104]

[0105] wherein η is the SO4 2-Removal rate, C SO4 (T) represents the SO4 content on day T. 2- Concentration, C SO4 (0) represents the initial SO4 2- concentration.

[0106] Furthermore, based on the ten indicators of carbon source materials obtained in the first, second, and third steps, the positive indicator is: soluble organic carbon release rate (RR). DOC Cumulative release of soluble organic carbon (DOC) cum (mg / (g·L)), SO4 2- Removal rate η, specific surface area A S (m 2 The carbon source optimization multi-index comprehensive evaluation model was constructed, which is based on the TOPSIS multi-index comprehensive evaluation model with dual weighting of subjective weighting method and entropy weighting method. The specific steps are as follows: (g), sulfite reductase activity X (U / ml), total concentration of small molecule organic matter SOM (mg / L), fluorescence biological index (BIX), E2 / E3 (Euv), and the inverse indicators are: material cost Y (yuan) and heavy metal release HM (mg / L).

[0107] (1) Given n alternative carbon sources and m = 10 evaluation indicators, the original indicator matrix is:

[0108] X = [x ij ] n×m

[0109] In the formula: x ij This represents the original value of the i-th carbon source on the j-th index;

[0110] (2) The evaluation indicators are positively normalized.

[0111] Positive indicators:

[0112]

[0113] Contrarian Indicators:

[0114]

[0115] The normalized matrix is: R = [r ij ]

[0116] Where: min(x) j ) represents the original minimum value of the j-th index of all carbon sources, max(x j ) represents the original maximum value of the j-th index of all carbon sources, r ij This represents the value of the i-th carbon source after normalization to the j-th index;

[0117] (3) Calculate the weights

[0118] Based on expert scoring, manual weighting was applied: Y: 0.2, η: ​​0.2, RR DOC : 0.12, DOC cum 0.12, A S 0.08, X SIR =0.08, HM: 0.08, SOM: 0.05, BIX: 0.035, EUV: 0.035, satisfying:

[0119]

[0120] In the formula, This represents the subjective weight of the j-th indicator;

[0121] The objective weights are calculated using the entropy weight method.

[0122] For the normalized matrix R = [r ij Each indicator is standardized to obtain the proportion of the i-th carbon source under the j-th indicator:

[0123]

[0124] Then, the entropy values ​​of each indicator are calculated based on the information entropy theory.

[0125]

[0126] Then, calculate the redundancy of the j-th indicator based on the entropy value; the higher the redundancy, the greater the weight.

[0127] d j =1-e j

[0128] The redundancy of all indicators is weighted and normalized to obtain the objective weight of each indicator.

[0129]

[0130] The subjective weights and objective weights are weighted and combined to obtain the comprehensive weight:

[0131]

[0132] In the formula: p ij Indicates the first The proportion of each carbon source to all carbon sources in the j-th index. e j The information entropy of the j-th indicator, e j ∈[0,1]; k represents the normalization constant; e j Represents the redundancy of the j-th indicator; Objective weight representing the jth index; a is the main and objective weight factor, with a value range of [0, 1]; w j is the comprehensive weight of the jth index.

[0133] (4) Calculate the positive ideal solution and the negative ideal solution, that is, the optimal and the worst of the model

[0134] According to the comprehensive weight, construct a weighted normalized matrix: v ij = r ij · w j

[0135] Positive ideal solution (maximum value):

[0136] A + = {max(v 1j ,…,v nj )}

[0137] Negative ideal solution (minimum value):

[0138] A - = {min(v 1j ,…,v nj )}

[0139] In the formula, A + represents the maximum value of the matrix v ij , that is, the most perfect, most suitable, and most ideal carbon source material; A - represents the minimum value of the matrix v ij , that is, the worst carbon source material.

[0140] (5) Calculate the distance and closeness

[0141] Calculate the distance of carbon source material i to the positive ideal solution:

[0142]

[0143] Calculate the distance of carbon source material i to the negative ideal solution:

[0144]

[0145] According to the TOPSIS evaluation method, calculate the degree to which the ith carbon source is closer to the optimal carbon source and farther from the worst carbon source, and finally select the carbon source material with a larger score C i :

[0146]

[0147] In the formula, represents the distance of carbon source material i to the positive ideal solution; represents the distance of carbon source material i to the negative ideal solution; C iThe representative carbon source material i is close to the optimal carbon source material, and the value range is [0, 1].

[0148] The application of the carbon source obtained by the above-mentioned preferred method to the in-situ purification of high-sulfate mine water in a goaf is as follows:

[0149] Step 1: The carbon source material obtained by the biological carbon source optimization method is prepared into a structured cage with a diameter of 5-10 cm to ensure stable structure and excellent slow-release performance.

[0150] Step 2: According to the technical solution of CN202410221310.X, select a suitable position in the goaf, arrange the water quality monitoring system and the gas monitoring system, and install a nitrogen production device.

[0151] Step 3: Drill a hole directly above the coal mine goaf, and directly drop the cage into the goaf through the hole.

[0152] Step 4: After the high-sulfate mine water is deoxygenated by nitrogen, it is discharged into the goaf, and low-sulfate low-suspended solid mine water flows out from the goaf outlet.

[0153] Further, the first step coal mine local agricultural by-product resources are closely related to the local dominant crops and climate conditions. According to the regional division of coal mines in China, there are five types: coal mines in Northeast China, coal mines in North China, coal mines in Northwest China, coal mines in Southwest China, and coal mines in South China. The dominant crops and agricultural by-products in different coal mine regions are different. Further, the second step carbon release performance analysis experimental method is as follows:

[0154] (1) Take 10 g of dried carbon source material, wrap the material with non-woven cloth tea, and place it in a 1000 mL glass bottle. Add 1000 mL of deionized water, place it in a 25℃, 175 rpm shaker, and take samples at 1, 4, 8, 12, 24, 48, 72, 96, and 120 h after the start of the experiment.

[0155] (2) Test the total organic carbon (DOC) of the water sample, and calculate the soluble organic carbon release rate and the cumulative release amount of soluble organic carbon (mg / (g·L)) accordingly;

[0156] (3) Use gas chromatography-mass spectrometry, three-dimensional fluorescence spectrometer, and ultraviolet-visible spectrophotometer to determine the composition of the released organic matter, such as total volatile organic matter concentration, total semi-volatile organic matter concentration, fluorescence index (FI), fluorescence biological index (BIX), SUVA 254 , E2 / E3(A 254 / A 365 );

[0157] (4) Environmental adaptability indicators include pH, heavy metal concentration, indicators that may pose a threat to the growth of sulfate-reducing bacteria;

[0158] (5) The BET specific surface area of the solid material is measured after vacuum freeze-drying. The larger the specific surface area, the more conducive to microbial adsorption.

[0159] Further, the degree of sulfate-reducing bacteria availability and activity analysis experiment method in the third step is as follows:

[0160] (1) The high sulfate mine water is injected with nitrogen to remove oxygen, 10g of dried carbon source material is weighed, wrapped with non-woven fabric, placed in a glass bottle, 1000mL of deoxygenated mine water is added, then 5% (v / v) of centrifuged sulfate-reducing bacteria liquid is inoculated, placed in a 25℃ constant temperature incubator for static culture, and sampled at 1, 3, 5, 7, 10, 15, 20 days after the start of the experiment;

[0161] (2) The SO4 2- , H2S, and microbial community structure of each water sample are tested;

[0162] (3) The sulfite reductase activity and APS reductase activity are measured using a spectrophotometer.

[0163] Further, the carbon source in the fourth step is preferably a multi-index comprehensive evaluation model, and the evaluation indicators include material cost Y (yuan), soluble organic carbon release rate RR DOC (mg / (L·h)), soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), SO4 2- removal rate η, specific surface area A S (m 2 / g), sulfite reductase activity X SIR (U / ml), heavy metal release amount HM (mg / L), total concentration of small molecule organic matter SOM (mg / L), fluorescence biological index (BIX), E2 / E3 (Euv).

[0164] Further, the carbon source in the fourth step is preferably a multi-index comprehensive evaluation model, and the indicators that have a positive relationship with the model are: soluble organic carbon release rate RR DOC , soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), SO4 2- removal rate η, specific surface area A S (m 2(g), sulfite reductase activity X (U / ml), total concentration of small molecule organic matter SOM (mg / L), fluorescence biological index (BIX), E2 / E3 (Euv), and the indicators in inverse relationship with the model are: material cost Y (yuan), heavy metal release amount HM (mg / L).

[0165] Further, the fourth step of the carbon source preferred multi-index comprehensive evaluation model, the index with the largest subjective weight is material cost Y (yuan) and SO4 2- removal rate η, followed by soluble organic carbon release rate RR DOC (mg / (L·h)), cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)), specific surface area A S (m 2 / g), sulfite reductase activity X SIR (U / ml), heavy metal release amount HM (mg / L), and the index with the smallest weight is: total concentration of small molecule organic matter SOM (mg / L), fluorescence biological index (BIX), E2 / E3 (Euv).

[0166] Further, the fourth step of the carbon source preferred multi-index comprehensive evaluation model, that is, the TOPSIS multi-index comprehensive evaluation model based on subjective weighting method and entropy weight method double weight, the specific steps are:

[0167] (1) Assuming that there are n carbon source candidate schemes, there are m=10 evaluation indexes, and the original index matrix is:

[0168] X=[x ij ] n×m

[0169] In the formula: x ij represents the original value of the i th carbon source on the j th index;

[0170] (2) The evaluation indexes are normalized in the positive direction

[0171] Positive indexes (RR DOC , DOC cum , η, A S , X SIR , SOM, BIX, Euv):

[0172]

[0173] Reverse indexes (Y, HM):

[0174]

[0175] The normalized matrix is: R=[r ij ]

[0176] min(x j ) represents the original minimum value of the jth index of all carbon sources, max(x j ) represents the original maximum value of the jth index of all carbon sources, and r ij represents the normalized value of the ith carbon source at the jth index.

[0177] (3) Calculate the weight

[0178] According to the expert scoring method, artificial weighting is performed: Y: 0.2, η: 0.2, RR DOC : 0.12, DOC cum : 0.12, A S : 0.08, X SIR : 0.08, HM: 0.08, SOM: 0.05, BIX: 0.035, Euv: 0.035. Satisfies:

[0179]

[0180] In the formula, represents the subjective weight of the jth index.

[0181] According to the entropy weight method, the objective weight is calculated. For the normalized matrix R = [r ij ], each index is standardized to obtain the proportion of the ith carbon source at the jth index:

[0182]

[0183] Then, based on the information entropy theory, the entropy value of each index is calculated:

[0184]

[0185] Then, according to the entropy value, the redundancy of the jth index is calculated, and the higher the redundancy, the greater the weight:

[0186] d j = 1 - e j

[0187] All index redundancies are weighted and normalized to obtain the objective weight of each index

[0188]

[0189] The subjective weight and the objective weight are combined to obtain the comprehensive weight:

[0190]

[0191] In the formula: p ijrepresents the proportion of the i th carbon source in the j th index, e j represents the information entropy of the j th index, e j ∈ [0, 1]; k represents a normalization constant; e j represents the redundancy of the j th index; represents the objective weight of the j th index; a is a subjective and objective weight factor, and the value range is [0, 1]; w j is the comprehensive weight of the j th index.

[0192] (4) Calculate the positive ideal solution and the negative ideal solution,

[0193] According to the comprehensive weight, a weighted normalization matrix v is constructed: ij = r ij · w j

[0194] Positive ideal solution (maximum value):

[0195] A + = {max(v 1j ,…,v nj )}

[0196] Negative ideal solution (minimum value):

[0197] A - = {min(v 1j ,…,v nj )}

[0198] In the formula, A + represents the maximum value of the matrix v ij , that is, the most perfect and most suitable carbon source material; A - represents the minimum value of the matrix v ij , that is, the worst carbon source material.

[0199] (5) Calculate the distance and closeness degree.

[0200] Calculate the distance between carbon source material i and the positive ideal solution:

[0201]

[0202] Calculate the distance between carbon source material i and the negative ideal solution:

[0203]

[0204] According to the TOPSIS evaluation method, the degree of how close the i th carbon source is to the optimal carbon source and how far it is from the worst carbon source is calculated, and the carbon source material with the largest C i is selected,

[0205]

[0206] wherein, represents the distance of carbon source material i to the positive ideal solution; represents the distance of carbon source material i to the negative ideal solution; C i represents the degree of carbon source material i approaching the optimal carbon source material, and the value range is [0, 1].

[0207] Example 2

[0208] A carbon source optimization method for in-situ purification of goaf high-sulfate mine water, according to the method provided in Example 1, the coal mine water is treated, and the specific steps are:

[0209] First step: the coal mine water of a certain coal mine in northwest Ordos is high turbidity and high sulfate mine water, the water inflow is greater than 1000 m 3 / h, which has exceeded the processing capacity of the mine water treatment station, and plans to discharge 200 m 3 / h of mine water into the goaf for treatment, and the nitrogen injection deoxidization equipment has been equipped underground.

[0210] Second step: 10 kinds of relatively inexpensive agricultural and sideline products in Ordos are mainly corn cob (0.6 yuan / kg), corn straw (0.7 yuan / kg), wheat straw (0.45 yuan / kg), bran (1.64 yuan / kg), soybean straw (0.85 yuan / kg), millet straw (0.58 yuan / kg), rice bran (0.69 yuan / kg), oat bran (0.5 yuan / kg), sweet potato residue (3.4 yuan / kg), and straw (0.56 yuan / kg).

[0211] Third step: test the agricultural and sideline products collected in the second step for the soluble organic carbon release rate RR DOC (mg / (L·h)), the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)), the SO4 2- removal rate η, the specific surface area A S (m 2 / g), the sulfite reductase activity X SIR (U / ml), the heavy metal release amount HM(mg / L), the total concentration of small molecule organic matter SOM(mg / L), the fluorescence biological index BIX, and E2 / E3(Euv) 9 indexes, and the indexes corresponding to each material are shown in Table 2.

[0212] Table 2 Performance indexes corresponding to different carbon source materials

[0213]

[0214]

[0215] Fourth step: according to the model evaluation index in the third step, using MATLAB software, running the TOPSIS multi-index comprehensive evaluation model based on the subjective weighting method and the entropy weight double weight, the score C of each carbon source material is obtained i : corn cob (0.6367), bran (06235), sweet potato residue (0.5812), rice bran (0.5691), corn straw (0.5592), oat bran (0.5290), wheat straw (0.4412), soybean straw (0.4321), millet straw (0.4249), straw (0.3808), and the most suitable material is corn cob.

[0216] Fifth step: selecting the carbon source material corn cob, packaging the corn cob in a cage with a diameter of 5cm to ensure stable structure and excellent slow-release performance; referring to the technical solution of CN202410221310.X, selecting a suitable position in the goaf, arranging the water quality monitoring system and the gas monitoring system, and installing nitrogen making equipment, drilling the cage into the goaf, then filling the goaf with nitrogen through the nitrogen making equipment, and removing oxygen in the mine water at the same time, the deoxygenated high-sulfate mine water is introduced into the goaf, the water inlet index of the mine water is 1800mg / L of sulfate concentration and 900mg / L of suspended matter concentration, the water outlet index is 800mg / L of sulfate concentration and 10mg / L of suspended matter concentration, the sulfate removal rate is 55.56%, and the suspended matter removal rate is 98.89%.

[0217] Cost accounting

[0218] The ton water treatment cost of the ground mine water treatment plant is 16 yuan, and the water quality meets the III class water standard of the Surface Water Quality Standard. Compared with the ground mine water treatment plant for treating high-sulfate mine water, the cost of establishing carbon source injection drillings, nitrogen making equipment, artificial dam, waterproof sealing wall, water tank and the like is 10 million yuan; the goaf can treat 4800 tons of water per day, 1kg of corn cob can treat 0.1 tons of water, and the ton water treatment cost of the material is 4 yuan, and the ton water treatment cost of the carbon source optimization method is about 5 yuan, which can save 52,800 yuan per day, and the construction cost can be saved after running for 190 days.

[0219] The embodiments provided in the present application are under relatively optimal conditions, but are not limited to the above-mentioned contents. Related technicians in the field can easily repeat the above-mentioned embodiments, and further extend and change the schemes, as long as they do not deviate from the spirit of the present application, which are within the protection scope of the present application.

Claims

1. A preferred method for a biological carbon source, characterized in that, Comprising the following steps: Step 1: Investigate the cheap agricultural by-product resources around the coal mine, preliminarily screen the cheap degradable carbon sources, and determine the material cost Y (yuan / kg) of each carbon source; Second step: carbon release performance analysis of multiple carbon sources, evaluate the carbon release performance of carbon sources through experimental determination: soluble organic carbon release rate RR DOC (mg / (L·h)), soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), specific surface area A S (m 2 / g), heavy metal cumulative release amount HM(mg / L), total concentration of small molecule organic matter SOM(mg / L), fluorescence biological index BIX, E2 / E3; Third step: Perform sulfate-reducing bacteria availability degree and activity analysis through experiments, and evaluate the activity of sulfate-reducing bacteria under different carbon source conditions according to the following indexes: SO4 2- Removal rate η (%), sulfite reductase activity X SIR (U / ml); The fourth step is to classify the material cost, carbon release performance index and sulfate reducing bacteria activity index determined in the first step, the second step and the third step, wherein the positive indexes are the soluble organic carbon release rate RR DOC , the soluble organic carbon cumulative release amount DOC cum (mg / (g·L)), the SO4 2- removal rate η, the specific surface area A S (m 2 / g), the sulfite reductase activity X(U / ml), the total concentration of small molecule organic matter SOM(mg / L), the fluorescence biological index(BIX), E2 / E3(Euv), and the negative indexes are the material cost Y(yuan) and the heavy metal release amount HM(mg / L), a carbon source optimization multi-index comprehensive evaluation model is constructed according to the classification indexes, and a score C i is combined to select an optimal carbon source for in-situ purification of high sulfate mine well water, wherein wherein C i represents the degree to which carbon source material i is close to the optimal carbon source material, i.e. the model score, and takes values in the range [0, 1]; represents the distance of carbon source material i from the positive ideal solution; represents the distance of carbon source material i from the negative ideal solution.

2. The method for selecting a preferred biocarbon source according to claim 1, characterized in that, The analysis experiment steps of carbon release performance in the second step are as follows: (1) 10g of dried carbon source material is weighed and placed in a non-woven tea bag, the tea bag is placed in a glass bottle containing 1000mL of deionized water, and the glass bottle is placed in a shaking table at 25℃ and 175rpm, and samples are taken at 1, 4, 8, 12, 24, 48, 72, 96 and 120h after the start of the experiment; (2) The water sample is tested for soluble organic carbon concentration (DOC), and the soluble organic carbon release rate RR is calculated according to the following formula DOC (mg / (L·h)) and the cumulative release amount of soluble organic carbon DOC cum (mg / (g·L)) In the formula, t is the reaction time (h), V is the volume of the water body (L), and m is the mass of the sample added (g); (3) The heavy metal release amount HM (mg / L) of the carbon source material is tested using ICP-MS, the total concentration of small molecule organic matter SOM (mg / L) is tested using gas chromatography-mass spectrometry and liquid chromatography tandem mass spectrometry, and the fluorescence biological index BIX and E2 / E3 (Euv) are tested using a three-dimensional fluorescence spectrometer; (4) The BET specific surface area A is determined after vacuum freeze-drying of the solid material S (m 2 / g), the greater the specific surface area, the more advantageous the adsorption of microorganisms.

3. The method for selecting a preferred biocarbon source according to claim 1, characterized in that, The experiment steps of the availability degree and activity analysis of sulfate-reducing bacteria in the third step are as follows: (1) The high-sulfate mine water is deoxygenated by nitrogen injection, 10g of dried carbon source material is weighed and packaged with non-woven fabric, and then placed in a glass bottle containing 1000mL of deoxygenated mine water, then inoculated with centrifuged sulfate-reducing bacteria liquid at a ratio of 5% (v / v), and placed in a 25℃ constant temperature incubator for static culture, and samples are taken at 1, 3, 5, 7, 10, 15 and 20 days after the start of the experiment; (2) The SO4 concentration (mg / L) of each water sample was tested 2- SO4 concentration (mg / L), sulfite reductase activity X SIR (U / ml), and the SO4 removal rate η was calculated according to the following formula 2- removal rate η, where, wherein η is SO4 2- Removal, C SO4 (T) is SO4 2- Concentration, C SO4 (0) is initial SO4 2- Concentration.

4. The method for selecting a preferred biocarbon source according to claim 1, characterized in that, The fourth step is to construct a carbon source optimization multi-index comprehensive evaluation model, which is a TOPSIS multi-index comprehensive evaluation model based on subjective weighting method and entropy weighting method double weight, and the specific steps are as follows: (1) There are n carbon source candidate schemes, m=10 evaluation indexes, and the original index matrix is: X = [x ij ] n×m wherein: x ij represents the original value of the ith carbon source on the jth indicator; (2) The evaluation indexes are normalized in the positive direction, Positive index: Negative index: The normalized matrix is: R=[r ij ] where: min(x j ) represents the original minimum value of the jth index of all carbon sources, max(x j ) represents the original maximum value of the jth index of all carbon sources, and r ij represents the value of the ith carbon source after normalization of the jth index. (3) Calculate the weight According to the expert scoring method, manual empowerment is carried out: Y: 0.2, η: 0.2, RR DOC : 0.12, DOC cum : 0.12, A S : 0.08, X SIR : 0.08, HM: 0.08, SOM: 0.05, BIX: 0.035, Euv: 0.035, meet: In the formula, denotes the subjective weight of the jth indicator; According to the entropy weight method, the objective weight is calculated, For the normalized matrix R = [r ij ], each index is normalized to obtain the proportion of the ith carbon source under the jth index: Then the entropy value of each index is calculated based on the information entropy theory Then the redundancy of the jth index is calculated according to the entropy value, the higher the redundancy, the greater the weight: d j = 1 - e j All index redundancy is weighted and normalized to get the objective weight of each index The subjective weight and objective weight are combined to get the comprehensive weight: In the formula: p ij represents the proportion of the ith carbon source in the jth index to the total carbon source, e j represents the information entropy of the jth index, e j ∈[0,1]; k represents a normalization constant; e j represents the redundancy of the jth index; represents the objective weight of the jth index; α is a subjective and objective weight factor, and the value range is [0,1]; w j is the comprehensive weight of the jth index. (4) Calculate the positive ideal solution and negative ideal solution, that is, the best and worst of the model According to the comprehensive weight, a weighted normalization matrix v is constructed: ij = r ij ·w j Positive ideal solution (maximum value): A + = {max(v 1j ,…,v nj )} Negative ideal solution (minimum value): A - = {min(v 1j ,…,v nj )} wherein A + represents the maximum value of the matrix v ij , i.e. the best, most suitable, ideal carbon source material; A - represents the minimum value of the matrix v ij , i.e. the worst carbon source material; (5) Calculate the distance and closeness Calculate the distance between carbon source material i and the positive ideal solution: Calculate the distance between carbon source material i and the negative ideal solution: According to the TOPSIS evaluation method, the closer the distance of the ith carbon source to the optimal carbon source, the farther the distance to the worst carbon source, and the final selection score C is calculated i Large carbon source material: wherein, represents the distance of carbon source material i from the positive ideal solution; represents the distance of carbon source material i from the negative ideal solution; C i represents the degree to which carbon source material i is close to the optimal carbon source material, taking a value in the range [0, 1].

5. The application of the carbon source optimized by the method of any one of claims 1-4 in the in-situ purification of high-sulfate mine water in the goaf.

6. Use according to claim 5, characterized in that, The specific steps of the application are as follows: First step: According to the biological carbon source optimization method, the carbon source material is prepared into a structured cage with a diameter of 5-10cm to ensure stable structure and excellent slow-release performance; Second step: According to the technical solution of CN202410221310.X, select a suitable location in the goaf, arrange the water quality monitoring system and gas monitoring system, and install nitrogen generating equipment at the same time; Third step: drilling directly above the coal mine goaf, and putting the cage into the goaf through the drilling; Fourth step: after the high-sulfate mine water is deoxidized by nitrogen, it is discharged into the goaf, and the low-sulfate and low-suspended solids mine water flows out of the goaf outlet.

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