Optimization control method for anaerobic ammonia oxidizing bacteria enrichment based on ecological niche regulation and control

Abstract

The invention relates to an anaerobic ammonia oxidizing bacteria enrichment optimization control method based on ecological niche regulation and control, which comprises the following steps: S1, selecting key ecological niche indexes of a constructed wetland as investigation factors, performing difference setting on the investigation factors, forming experimental systems of different ecological niche, controlling and monitoring the constructed wetland, and collecting data; s2, taking the relative abundance and / or absolute abundance of the anaerobic ammonia oxidizing bacteria collected in the step S1 as dependent variables, taking key ecological niche indexes as independent variables, and performing fitting so as to predict a model; and S3, performing prediction through the prediction model, comparing a prediction result with a control target, and performing optimization control on the anaerobic ammonia oxidizing bacteria enrichment of the constructed wetland according to a comparison result. According to the method, the prediction model with relatively high prediction accuracy can be obtained, so that the enrichment of anaerobic ammonia oxidizing bacteria can be ensured, the sewage treatment efficiency can be improved and a relatively good total nitrogen removal effect can be obtained by adjusting ecological niche indexes in the constructed wetland by virtue of the prediction model.

Description

Technical Field

[0001] The invention relates to the technical field of anaerobic ammonium oxidizing bacteria enrichment, and is an optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation. Background Art

[0002] The removal of total nitrogen in the wastewater treatment process is a key goal. As the main way to remove total nitrogen, biological processes have always been the focus of attention in this field. The traditional denitrification process is to reduce nitrate nitrogen to nitrogen gas through heterotrophic microorganisms to remove total nitrogen. However, the denitrification process requires the addition of an organic carbon source, such as methanol or acetic acid, to provide an electron donor, which increases operating costs and carbon footprint.

[0003] In this context, anaerobic ammonium oxidation (Anammox) as a new biological denitrification technology has shown great advantages. The anaerobic ammonium oxidation process uses specialized anaerobic ammonium oxidation bacteria to directly oxidize ammonium nitrogen into nitrogen gas under anaerobic conditions using nitrite as an electron acceptor without the need for an additional carbon source. The chemical reaction formula of this process is: 1.32NH4 + +1.02NO2 - →1.02N2+0.26NO3 - +2H2O.

[0004] Compared with the traditional nitrification-denitrification process, anaerobic ammonium oxidation has higher nitrogen removal efficiency and lower energy consumption. Studies have shown that anaerobic ammonium oxidation can save more than 50% of aeration energy consumption and reduce sludge generation by 90%. In actual operation, the anaerobic ammonium oxidation process treats ammonium nitrogen loads of 0.5-1.0kg N / (m 3 ·d), the nitrogen removal efficiency can reach more than 80%. Compared with traditional processes, its carbon source demand is reduced by nearly 100%, and it is particularly superior in treating high-ammonium nitrogen wastewater (such as livestock and poultry breeding wastewater). In addition, anaerobic ammonium oxidation helps reduce the emission of greenhouse gases (such as N2O), making the wastewater treatment process more sustainable.

[0005] Constructed wetlands are a near-natural ecological treatment technology that is based on artificial design, construction, operation and maintenance management, uses plants, natural matrices or artificial media as construction materials, and achieves sewage purification through the coupling of biological, physical and chemical processes under low-carbon and low-cost implementation conditions.

[0006] In artificial wetlands, the enrichment of anaerobic ammonium-oxidizing bacteria faces multiple challenges, mainly including their extremely slow growth rate, demanding environmental conditions, and weak competitiveness with other microorganisms. The generation time of anaerobic ammonium-oxidizing bacteria can be as long as 10-30 days, which is much longer than other nitrifying and denitrifying bacteria, making it difficult for them to quickly occupy ecological niches under natural conditions.

[0007] Therefore, it is of great significance to ensure the enrichment of anaerobic ammonium oxidizing bacteria by adjusting the ecological niche indicators in wetlands. However, there are many ecological niche indicators in artificial wetlands in the prior art, some of which have no relevance to the enrichment of anaerobic ammonium oxidizing bacteria, and some of which have multiple effects on the enrichment of anaerobic ammonium oxidizing bacteria, making it difficult to obtain a stable enrichment effect of anaerobic ammonium oxidizing bacteria. Summary of the invention

[0008] The purpose of the present invention is to overcome the difficulties in regulating the enrichment of anaerobic ammonium oxidizing bacteria in existing artificial wetlands and to provide an optimized control method for the enrichment of anaerobic ammonium oxidizing bacteria based on niche regulation.

[0009] In traditional cognition, it is recommended that the dissolved oxygen content in artificial wetlands be controlled below 1 mg / L, and the organic matter content (the organic matter content is usually measured in chemical oxygen demand) must be strictly controlled. The reason is that traditional research believes that anaerobic ammonia oxidizing bacteria are strictly anaerobic bacteria, and higher dissolved oxygen will inhibit their growth, while the presence of organic matter will promote the growth of denitrifying bacteria, resulting in competition for nutrient substrates (nitrite nitrogen) between the two bacteria.

[0010] However, the inventors believe that the above cognition is mostly inherited from the research results of bioreactors, ignoring the structural characteristics of artificial wetlands themselves, and also ignoring the synergistic relationship between microorganisms, resulting in the control effect of anaerobic ammonia-oxidizing bacteria obtained based on the above cognitive bias being unstable and difficult to achieve the expected bacterial enrichment.

[0011] The inventor further discovered through experimental research that when the dissolved oxygen content is controlled below 1 mg / L and no organic matter is added, the secretion content of extracellular polymers of microorganisms is extremely low, and anaerobic ammonium oxidizing bacteria have the characteristic of slow growth. This result makes it difficult to form a biofilm and it is difficult for anaerobic ammonium oxidizing bacteria to be enriched in the system. At the same time, the study found that although the addition of organic matter can enhance the enrichment of denitrifying bacteria, regulation within the effective control range can promote denitrifying bacteria to convert nitrate nitrogen into nitrite nitrogen, and no competitive relationship is formed between the two bacteria, but rather a synergistic effect. In addition, the synergistic effect of key indicators of the ecological niche in wetlands is usually ignored in the prior art, and a quantitative model for the synergistic effect of key indicators of the ecological niche on the relative abundance and absolute abundance of anaerobic ammonium oxidizing bacteria has not yet been established. This model is of great significance for the quantitative design of niche regulation, and can directly guide the establishment of strategies for the enhanced enrichment of anaerobic ammonium oxidizing bacteria. Based on the above content, this application investigated the synergistic effect of niche indicators (pH, DO, AN, NO2-N, NO3-N, B-COD), and fitted them through a multivariate linear model to obtain a prediction model for the relative abundance and absolute abundance of anaerobic ammonia-oxidizing bacteria. It was verified that the prediction model can match the measured values ​​well and has a certain prediction accuracy.

[0012] The specific plan is as follows:

[0013] An optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation comprises the following steps:

[0014] S1. Select key ecological niche indicators of artificial wetlands as investigation factors, set the investigation factors differently, and form experimental systems with different ecological niches; introduce sewage to be treated into the artificial wetlands, control and monitor the artificial wetlands according to the experimental system, and collect data on the relative abundance and / or absolute abundance of anaerobic ammonia-oxidizing bacteria;

[0015] S2. Using the relative abundance and / or absolute abundance of the anaerobic ammonium-oxidizing bacteria collected in S1 as the dependent variable and the key ecological niche indicator as the independent variable, a multivariate linear model is used to fit the relative abundance and absolute abundance of the anaerobic ammonium-oxidizing bacteria, thereby obtaining a relative abundance prediction model for the anaerobic ammonium-oxidizing bacteria and / or an absolute abundance prediction model for the anaerobic ammonium-oxidizing bacteria;

[0016] S3. Predict the relative abundance and / or absolute abundance of anaerobic ammonium oxidizing bacteria in the artificial wetland using the relative abundance prediction model for anaerobic ammonium oxidizing bacteria and / or the absolute abundance prediction model for anaerobic ammonium oxidizing bacteria obtained in S2, compare the prediction result with the control target, and optimize the enrichment of anaerobic ammonium oxidizing bacteria in the artificial wetland based on the comparison result.

[0017] Furthermore, the key ecological niche indicators described in S1 include: at least two of water pH, dissolved oxygen DO in water, ammonium nitrogen concentration AN in water, nitrite nitrogen concentration NO2-N in water, nitrate nitrogen concentration NO3-N in water, and corrected chemical oxygen demand B-COD in water.

[0018] Furthermore, the calculation method of the corrected chemical oxygen demand B-COD of the water body described in S1 is: correct the measured COD value according to the concentration of nitrite in the water body, and the calculation formula is B-COD=x-1.14z, wherein x is the COD concentration of the water body, in mg / L, and the COD concentration of the water body is preferably determined by the potassium dichromate method; z is the nitrite concentration of the water body, in mg / L, and the nitrite concentration of the water body is preferably determined by ion chromatography.

[0019] Furthermore, the artificial wetland described in S1 is an ascending horizontal subsurface flow artificial wetland, and the designed water level height is less than or equal to 60 cm, or the oxygen content of the water at the bottom of the artificial wetland is not less than 0.5 mg / L.

[0020] Furthermore, in S1, the investigation factors are set differently within a certain range, including: the dissolved oxygen DO contained in the water body in the artificial wetland is 1-2.5 mg / L, and the water body pH is 7.3-8.4;

[0021] Preferably, the pH control level of the water body in the artificial wetland is linearly related to the dissolved oxygen DO contained in the water body, and the linear equation is: DO=-1.3837*pH+13.36. The pH of the water body and / or the dissolved oxygen contained in the water body in the artificial wetland are regulated according to the linear equation.

[0022] Furthermore, S1 sets the inspection factors differently within a certain range, and also includes that the nutrient status in the artificial wetland meets the following conditions: the ammonium nitrogen concentration AN of the artificial wetland is controlled at 10-200 mg / L, the nitrite nitrogen concentration NO2-N is controlled at 30-300 mg / L, the nitrate nitrogen concentration NO3-N is controlled at 20-120 mg / L, and the corrected chemical oxygen demand B-COD of the water body is controlled at 25-200 mg / L; and the ratio of AN to NO2-N is maintained at 5%-100%, the ratio of B-COD to AN is maintained at 30%-400%, the ratio of NO2-N to NO3-N is maintained at 100%-300%, and the ratio of COD to NO3-N is maintained at 15%-40%.

[0023] Furthermore, the relative abundance prediction model of anaerobic ammonium-oxidizing bacteria is:

[0024] Relative abundance = 72.9001 + 0.4084*DO + -6.4204*pH + -0.022*AN + -0.0285*NO2-N + -0.0602*NO3-N + 0.0131*B-COD, where the input values ​​of DO, AN, NO2-N, NO3-N, and B-COD are in mg / L.

[0025] Furthermore, the absolute abundance prediction model of anaerobic ammonium-oxidizing bacteria is:

[0026] Absolute abundance = -4878056+19797121*DO+8538451*pH+157015*AN+-255475*NO2-N+-295679*NO3-N+95166*B-COD, where the input values ​​of DO, AN, NO2-N, NO3-N and B-COD are in mg / L.

[0027] The present invention also protects a terminal device for an optimization control method for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation, comprising a processor, a memory, and a computer program stored in the memory and running on the processor, wherein the steps of the method are implemented when the processor executes the computer program.

[0028] The present invention also protects a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method are implemented.

[0029] Beneficial effects: The optimization control method for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation provided by the present invention uses the key niche indicators of artificial wetlands as the investigation factors, sets these factors differently, and analyzes the relative abundance and absolute abundance of anaerobic ammonia-oxidizing bacteria in multiple experimental systems with different niches. Afterwards, the data collected in the above system are used, the relative abundance and absolute abundance of anaerobic ammonia-oxidizing bacteria are used as dependent variables, and the key niche indicators are used as independent variables. The two abundances are fitted using a multivariate linear model, and then a relevant prediction model is obtained.

[0030] Furthermore, the present application calibrates the chemical oxygen demand, thereby improving the reliability of the prediction model and overcoming the interference of the nitrite content in the water body on the model.

[0031] Furthermore, the present application pays attention to the synergistic effect of the water level depth of the artificial wetland and dissolved oxygen, and thus controls the designed water level height of the artificial wetland to be less than or equal to 60 cm, thereby ensuring the effective enrichment of anaerobic ammonia-oxidizing bacteria.

[0032] When examining the correspondence between key niche indicators and the abundance of anaerobic ammonia-oxidizing bacteria, the present application controls the key niche indicators in the artificial wetland within a certain range so that the obtained data can better match the multivariate linear model, thereby ensuring that the prediction model has good accuracy.

[0033] In summary, the optimization control method for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation of the present invention can achieve anaerobic ammonia-oxidizing bacteria enrichment by controlling niche indicators, reduce the difficulty of artificial wetland management and maintenance, and help promote artificial wetlands to maintain a high water purification efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings will be briefly introduced below. Obviously, the accompanying drawings in the following description only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0035] Figure 1 It is a flow chart of an optimization control method for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation provided by one embodiment of the present invention;

[0036] Figure 2 is a graph showing the relationship between relative abundance of bacteria and wetland water level depth provided by one embodiment of the present invention;

[0037] Figure 3 is a graph showing the relationship between the absolute abundance of bacteria and the depth of wetland water level provided by one embodiment of the present invention;

[0038] Figure 4 1 is a graph showing the relationship between dissolved oxygen content and wetland water level depth provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. In the examples, those without specifying specific techniques or conditions are carried out according to the techniques or conditions described in the literature in this area or according to the product specification. Those without specifying the manufacturer of reagents or instruments used are all conventional products that can be obtained commercially. In the following examples, if not clearly stated, "%" refers to weight percentage.

[0040] Embodiment 1

[0041] An optimization control method for the enrichment of anaerobic ammonium-oxidizing bacteria based on niche regulation, such as Figure 1 As shown, the following steps are included:

[0042] S1. Select key ecological niche indicators of artificial wetlands as investigation factors, set the investigation factors differently, and form experimental systems with different ecological niches; introduce sewage to be treated into the artificial wetlands, control and monitor the artificial wetlands according to the experimental system, and collect data on the relative abundance and / or absolute abundance of anaerobic ammonia-oxidizing bacteria.

[0043] Selecting appropriate key ecological niche indicators of artificial wetlands is of great significance to the accuracy of the prediction model. Process control is a systematic and holistic control system, and it is not feasible to control a single factor. The key ecological niche indicators selected in this embodiment include: water pH, dissolved oxygen DO contained in the water, ammonium nitrogen concentration AN in the water, nitrite nitrogen concentration NO2-N in the water, nitrate nitrogen concentration NO3-N in the water, and corrected chemical oxygen demand B-COD in the water.

[0044] For microorganisms, nutrient salt substrates are necessary conditions for their growth. Therefore, considering that anaerobic ammonium oxidizing bacteria belong to denitrifying microorganisms, this embodiment uses nutrient salt substrates that affect denitrifying microorganisms as selection indicators.

[0045] Artificial wetlands usually regulate microbial communities by changing hydraulic load, hydraulic retention time, and water level. The essence of their operation is to change the level of environmental nutrients and key environmental growth conditions, among which dissolved oxygen and pH are the main representatives of key environmental growth conditions. Both will affect microbial growth by affecting the redox process and osmotic pressure of surrounding substances. Therefore, this example also selects DO and pH as investigation factors.

[0046] This example analyzes the effects of different wetland structures on the enrichment of anaerobic ammonium-oxidizing bacteria. The study found that when the wetland water level depth is designed to be 90 cm, the relative abundance and absolute abundance of this type of bacteria at the bottom of the system are the smallest. As the water level design depth decreases, the abundance of anaerobic ammonium-oxidizing bacteria increases significantly, such as Figure 2 , Figure 3 By measuring the bottom ecological niche indicators of the wetland, the study found that only the dissolved oxygen content showed significant differences (P<0.01), such as Figure 4 As shown, the study recognized the importance of the synergistic effect between wetland water level depth and dissolved oxygen.

[0047] For this reason, in this embodiment, the ecological niche regulation is carried out based on the operation mode of the rising horizontal subsurface artificial wetland. The designed water level height of the artificial wetland should be less than or equal to 60cm to ensure the transmission rate of natural oxygen enrichment in the atmosphere and not cause serious anaerobic phenomenon at the bottom of the wetland (i.e. less than 0.5mg / L). The dissolved oxygen (DO) content contained in the water body in the artificial wetland should not be less than 1mg / L. If this level is not reached, aeration and oxygenation by artificial aeration should be considered, but the oxygenation process should control the dissolved oxygen in the wetland to be no higher than 2.5mg / L. The pH level of the water body in the artificial wetland should be controlled between 7.3-8.4. The pH control level should be linearly related to the dissolved oxygen. The design of this relationship can refer to the following linear equation: DO = -1.3837*pH + 13.36. The dissolved oxygen and pH set values ​​should be controlled within the above range. When the predicted value given by the linear equation exceeds its range, the close value within the control interval should be taken.

[0048] In this embodiment, the corrected COD value (i.e., B-COD) is used as the setting condition because the enrichment of anaerobic ammonia-oxidizing bacteria requires nitrite as a substrate, and a high nitrite concentration must be ensured in the sewage. The presence of nitrite will cause the COD test results to be biased high (1 gram of nitrite can be converted into 1.14 grams of COD). Therefore, according to the COD setting standards in the existing patents, the reliability of the actual operation process will be affected.

[0049] In this embodiment, B-COD corrects the measured COD value according to the concentration of nitrite. The specific formula is B-COD=x-1.14z, where X is the COD concentration (mg / L) in the sewage measured by the potassium dichromate method, and z is the nitrite concentration (mg / L) in the sewage measured by ion chromatography.

[0050] When making differential settings, the nutrient status in artificial wetlands should also be considered, and the following requirements should be met: the concentration of ammonium nitrogen (AN) should be controlled within 10-200 mg / L, the concentration of nitrite nitrogen (NO2-N) should be controlled within 30-300 mg / L, the concentration of nitrate nitrogen (NO3-N) should be controlled within 20-120 mg / L, and the concentration of B-COD should be controlled within 25-200 mg / L. The ratio of AN to NO2-N should be maintained at 5%-100%, the ratio of B-COD to AN should be maintained at 30%-400%, the ratio of NO2-N to NO3-N should be maintained at 100%-300%, and the ratio of COD to NO3-N should be maintained at 15%-40%.

[0051] By controlling the key niche indicators of artificial wetlands within the above range, it is helpful to improve the accuracy of prediction. When controlling artificial wetlands, changing the key niche indicators through external interference should also be within the above range. For example, by adding acid and alkali reagents to change the pH of the water body, or by turning on the aeration device to increase oxygen. By changing the values ​​of these key niche indicators, achieving the difference setting goals, and then conducting tests, the relative abundance and absolute abundance of anaerobic ammonia-oxidizing bacteria in multiple experimental systems with different niche indicators can be obtained.

[0052] S2. Using the relative abundance and / or absolute abundance of the anaerobic ammonium oxidizing bacteria collected in S1 as the dependent variable and the key ecological niche indicator as the independent variable, a multivariate linear model is used to fit the relative abundance and absolute abundance of anaerobic ammonium oxidizing bacteria, thereby deriving a relative abundance prediction model for anaerobic ammonium oxidizing bacteria and / or an absolute abundance prediction model for anaerobic ammonium oxidizing bacteria.

[0053] The prediction model of the relative abundance (%) and absolute abundance (copy number / gram) of anaerobic ammonium-oxidizing bacteria in the constructed wetland in this embodiment is as follows:

[0054] Relative abundance = 72.9001 + 0.4084 * DO + -6.4204 * pH + -0.022 * AN + -0.0285 * NO2-N + -0.0602 * NO3-N + 0.0131 * B-COD;

[0055] Absolute abundance = -4878056+19797121*DO+8538451*pH+157015*AN+-255475*NO2-N+-295679*NO3-N+95166*B-COD;

[0056] The input values ​​of DO, AN, NO2-N, NO3-N and B-COD are in mg / L.

[0057] S3. Predict the relative abundance and / or absolute abundance of anaerobic ammonium oxidizing bacteria in the artificial wetland using the relative abundance prediction model for anaerobic ammonium oxidizing bacteria and / or the absolute abundance prediction model for anaerobic ammonium oxidizing bacteria obtained in S2, compare the prediction result with the control target, and optimize the enrichment of anaerobic ammonium oxidizing bacteria in the artificial wetland based on the comparison result.

[0058] In this embodiment, the model prediction situations in three cases are investigated respectively, as shown in Table 1:

[0059] Table 1 Prediction model validation data table

[0060]

[0061] It can be seen from Table 1 that the above prediction model has a certain prediction accuracy, and its prediction accuracy for relative abundance is higher than that for absolute abundance.

[0062] Given the high accuracy of model predictions, the model can be used to generate more niche scenarios and then used to make predictions. The prediction results can then be combined with niche indicators to build a prediction model using other model building methods (such as random forests, support vector machines, and neural networks).

[0063] Embodiment 2

[0064] The present invention also provides an optimization control terminal device for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above-mentioned method embodiment of embodiment 1 of the present invention when executing the computer program.

[0065] Further, as an executable scheme, the optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation can be a computing device such as a desktop computer, a notebook, a PDA and a cloud server. The optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the composition structure of the above-mentioned optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation is only an example of the optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation, and does not constitute a limitation on the optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation. It may include more or less components than the above, or a combination of certain components, or different components. For example, the optimization control terminal device for enrichment of anaerobic ammonia oxidizing bacteria based on niche regulation may also include input and output devices, network access devices, buses, etc., and the embodiments of the present invention do not limit this.

[0066] Further, as an executable solution, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the optimization control terminal device for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation, and various interfaces and lines are used to connect the various parts of the optimization control terminal device for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation.

[0067] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the optimization control terminal device based on the enrichment of anaerobic ammonia oxidizing bacteria regulated by the niche by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0068] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method in the embodiment of the present invention are implemented.

[0069] The module / unit integrated in the terminal device for optimizing the enrichment of anaerobic ammonia-oxidizing bacteria based on niche regulation can be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as an independent product. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory) and software distribution medium, etc.

[0070] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0071] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0072] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. An optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation, characterized in that: The following steps are involved: S1. Select key ecological niche indicators of artificial wetlands as investigation factors, set the investigation factors differently, and form experimental systems with different ecological niches; introduce sewage to be treated into the artificial wetlands, control and monitor the artificial wetlands according to the experimental system, and collect data on the relative abundance and / or absolute abundance of anaerobic ammonia-oxidizing bacteria; S2. Using the relative abundance and / or absolute abundance of the anaerobic ammonium-oxidizing bacteria collected in S1 as the dependent variable and the key ecological niche indicator as the independent variable, a multivariate linear model is used to fit the relative abundance and absolute abundance of the anaerobic ammonium-oxidizing bacteria, thereby obtaining a relative abundance prediction model for the anaerobic ammonium-oxidizing bacteria and / or an absolute abundance prediction model for the anaerobic ammonium-oxidizing bacteria; S3. Predict the relative abundance and / or absolute abundance of anaerobic ammonium oxidizing bacteria in the artificial wetland using the relative abundance prediction model for anaerobic ammonium oxidizing bacteria and / or the absolute abundance prediction model for anaerobic ammonium oxidizing bacteria obtained in S2, compare the prediction result with the control target, and optimize the enrichment of anaerobic ammonium oxidizing bacteria in the artificial wetland based on the comparison result.

2. The optimization control method for anaerobic ammonium-oxidizing bacteria enrichment based on niche regulation according to claim 1, characterized in that: The key ecological niche indicators described in S1 include: at least two of the following: water pH, dissolved oxygen DO in water, ammonium nitrogen concentration AN in water, nitrite nitrogen concentration NO2-N in water, nitrate nitrogen concentration NO3-N in water, and corrected chemical oxygen demand B-COD in water.

3. The optimization control method for anaerobic ammonium-oxidizing bacteria enrichment based on niche regulation according to claim 2, characterized in that: The calculation method of the corrected chemical oxygen demand B-COD of the water body described in S1 is: the measured COD value is corrected according to the concentration of nitrite in the water body, and the calculation formula is B-COD=x-1.14z, wherein x is the COD concentration of the water body, in mg / L, and the COD concentration of the water body is preferably determined by the potassium dichromate method; z is the nitrite concentration of the water body, in mg / L, and the nitrite concentration of the water body is preferably determined by ion chromatography.

4. The optimization control method for anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation according to claim 2 or 3, characterized in that: The artificial wetland described in S1 is an ascending horizontal subsurface flow artificial wetland, and the designed water level height is less than or equal to 60 cm, or the oxygen content of the water at the bottom of the artificial wetland is not less than 0.5 mg / L.

5. The optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation according to claim 4, characterized in that: In S1, the investigation factors are set differently within a certain range, including: the dissolved oxygen DO contained in the water body in the artificial wetland is 1-2.5 mg / L, and the water body pH is 7.3-8.4; Preferably, the pH control level of the water body in the artificial wetland is linearly related to the dissolved oxygen DO contained in the water body, and the linear equation is: DO=-1.3837*pH+13.

36. The pH of the water body and / or the dissolved oxygen contained in the water body in the artificial wetland are regulated according to the linear equation.

6. The optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation according to claim 5, characterized in that: S1 sets the investigation factors differently within a certain range, and also includes that the nutrient status in the artificial wetland meets the following conditions: the ammonium nitrogen concentration AN of the artificial wetland is controlled at 10-200 mg / L, the nitrite nitrogen concentration NO2-N is controlled at 30-300 mg / L, the nitrate nitrogen concentration NO3-N is controlled at 20-120 mg / L, and the corrected water chemical oxygen demand B-COD is controlled at 25-200 mg / L; and The ratio of AN to NO2-N is maintained at 5%-100%, the ratio of B-COD to AN is maintained at 30%-400%, the ratio of NO2-N to NO3-N is maintained at 100%-300%, and the ratio of COD to NO3-N is maintained at 15%-40%.

7. The optimization control method for anaerobic ammonium oxidizing bacteria enrichment based on niche regulation according to claim 6, characterized in that: The relative abundance prediction model of anaerobic ammonium-oxidizing bacteria is: Relative abundance = 72.9001 + 0.4084*DO + -6.4204*pH + -0.022*AN + -0.0285*NO2-N + -0.0602*NO3-N + 0.0131*B-COD, where the input values ​​of DO, AN, NO2-N, NO3-N, and B-COD are in mg / L.

8. The optimization control method for anaerobic ammonium-oxidizing bacteria enrichment based on niche regulation according to claim 6, characterized in that: The absolute abundance prediction model of anaerobic ammonium-oxidizing bacteria is: Absolute abundance = -4878056+19797121*DO+8538451*pH+157015*AN+-255475*NO2-N+-295679*NO3-N+95166*B-COD, where the input values ​​of DO, AN, NO2-N, NO3-N and B-COD are in mg / L.

9. A terminal device for optimizing the control method of anaerobic ammonia-oxidizing bacteria enrichment based on niche regulation, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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