Constructed wetland pollution reduction and carbon reduction synergistic effect analysis system and method

Abstract

The invention discloses a constructed wetland pollution reduction and carbon reduction synergistic effect analysis system and method, and relates to the technical field of water pollution control and greenhouse gas emission reduction. Comprising a simulated wetland reaction unit, a multi-parameter monitoring module, an operation regulation and control module, a microbiological analysis module and a synergistic effect evaluation module. The simulated wetland reaction unit is filled with a FeC composite matrix to realize subsurface flow constructed wetland environment simulation; the multi-parameter monitoring module acquires water quality and greenhouse gas emission data in real time; the operation regulation and control module realizes accurate regulation and control of water inlet parameters; the microbiological analysis module analyzes microflora and functional gene information; and the synergistic effect evaluation module integrates multi-module data to construct a correlation model, calculates a synergistic effect index and outputs an optimization parameter. Through five stages of matrix optimization, operation regulation and control, microbial mechanism revealing, collaborative evaluation optimization and feedback application, evaluation and optimization of the constructed wetland pollution reduction and carbon reduction collaborative efficiency are realized, and a scientific basis is provided for actual constructed wetland engineering design and operation.

Description

Technical Field

[0001] This invention relates to the field of water pollution control and greenhouse gas emission reduction technology, and more specifically, to a system and method for analyzing the synergistic effect of constructed wetlands in pollution reduction and carbon reduction. Background Technology

[0002] Constructed wetlands, as a low-cost and eco-friendly wastewater treatment technology, are widely used to treat low- to medium-concentration wastewater such as livestock and poultry wastewater and domestic sewage. They remove pollutants through the synergistic effects of substrate retention, plant absorption, and microbial metabolism. However, during operation, they easily generate potent greenhouse gases such as CH4 and N2O, contributing to the greenhouse effect and hindering the full realization of their eco-friendly advantages. Therefore, achieving synergistic optimization of pollution reduction and carbon reduction in constructed wetlands has become a current research hotspot and technical challenge in this field.

[0003] Current research on constructed wetlands largely focuses on improving the removal efficiency of single pollutants or monitoring greenhouse gas emission characteristics in isolation, lacking a systematic analysis of the synergistic effects of these two approaches. Furthermore, the operational effectiveness of constructed wetlands is comprehensively influenced by substrate composition, operating parameters (such as influent load and hydraulic retention time), and microbial community structure. Existing technologies struggle to establish a quantitative correlation between "substrate-operating parameters-microorganisms-synergistic efficacy," making it difficult to accurately select the optimal operating scheme and effectively guide the design and operational modification of practical projects.

[0004] FeC composite matrices, formed by combining Fe-based materials with biochar, possess excellent adsorption properties, electron transfer capabilities, and microbial carrier functions. They are expected to enhance pollutant removal while simultaneously regulating microbial metabolic processes and reducing greenhouse gas emissions. However, the impact of different FeC ratios and operating parameters on the synergistic effect of pollution reduction and carbon reduction remains unclear, and the lack of corresponding systematic analysis methods and evaluation frameworks limits the efficient application of FeC composite matrices in constructed wetlands.

[0005] Therefore, there is an urgent need to develop a system and method that can systematically analyze the synergistic effects of pollution reduction and carbon reduction in constructed wetlands. By integrating water quality monitoring, greenhouse gas monitoring, microbial analysis and synergistic evaluation, a quantitative correlation between multiple factors and synergistic effectiveness can be established, and the optimal substrate ratio and operating parameters can be screened to provide a scientific basis for the optimized design and operation control of actual constructed wetland projects. Summary of the Invention

[0006] To address the shortcomings in existing technologies, such as the lack of analysis on the synergistic effect of pollution reduction and carbon reduction in constructed wetlands, unclear correlations among multiple factors, and insufficient targeting of optimization schemes, this invention provides a system and method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands. This system enables systematic monitoring, quantitative evaluation, and precise optimization of the synergistic effectiveness of pollution reduction and carbon reduction in constructed wetlands, filling a gap in existing technologies.

[0007] The technical solution adopted by this invention to solve its technical problem is: This invention proposes a system for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands, comprising: The simulated wetland reaction unit is used to simulate the subsurface flow constructed wetland environment. Its interior is filled with FeC composite matrix, which is composed of iron-based materials, biochar and natural matrix such as zeolite or sand and gravel mixed in a predetermined volume ratio. The multi-parameter monitoring module is connected to the simulated wetland reaction unit and is used to monitor the influent water quality parameters, effluent water quality parameters, and the emission flux of CH4 and N2O gases generated inside the simulated wetland reaction unit in real time. The operation and control module is connected to the inlet of the simulated wetland reaction unit and is used to control the pollution load, hydraulic retention time, aeration conditions and carbon-nitrogen ratio of the influent according to preset strategies or feedback signals. The microbial analysis module is used to perform DNA extraction, high-throughput sequencing, and bioinformatics analysis on samples collected from FeC composite matrix to obtain information on microbial community structure, diversity, and predicted abundance of functional genes related to greenhouse gas emissions. The synergy effect assessment module has its input connected to the multi-parameter monitoring module and the microbial analysis module, and its output connected to the operation and control module; the synergy effect assessment module is used for: a. Calculate pollutant removal efficiency based on water quality parameters; b. Calculate global warming potential based on gas emission fluxes; c. Construct a correlation model for the synergistic effect of pollution reduction and carbon reduction by combining pollutant removal efficiency, global warming potential and microbial functional gene information; d. Based on the correlation model, calculate the synergistic effect index and generate suggestions for optimizing operating parameters, which are then fed back to the operation control module.

[0008] Furthermore, in the above scheme, the mixture of iron-based material and biochar accounts for 10%-40% of the total volume in the FeC composite matrix, and the natural matrix such as zeolite or sand accounts for 60%-90% of the total volume, and the mass ratio of iron-based material to biochar is 1:1-5:1; the iron-based material is one or more of iron filings, pyrite or zero-valent iron; and the biochar is one of bamboo charcoal, straw charcoal or wood chip charcoal.

[0009] Furthermore, the above scheme includes an online water quality sensor and a greenhouse gas static chamber-chromatographic coupling acquisition and analysis device.

[0010] Furthermore, the above scheme includes a proportional pump, a flow controller, an aeration pump, and a carbon / nitrogen source addition device.

[0011] Furthermore, in the above scheme, the association model constructed by the synergy effect assessment module is a multiple regression model, a machine learning model, or a structural equation model, and the synergy effect index (SEI) is calculated using one of the following formulas or a variant thereof: SEI = (Comprehensive Pollutant Removal Index) / (Comprehensive Greenhouse Gas Emission Index); The composite greenhouse gas emissions index in the formula is the standardized GWP value; Or SEI = α × standardized removal rate - β × standardized GWP; In the formula, α and β are weighting coefficients.

[0012] A method for analyzing the synergistic effect of constructed wetlands in pollution reduction and carbon reduction includes the following steps: S1. Construction and initialization: Configure simulated wetland reaction units with different FeC composite matrix ratios and plant wetland plants; S2, First Stage Analysis - Matrix Optimization: Under standard operating conditions, each simulated wetland reaction unit was run, and its pollutant removal rate and greenhouse gas emission data were obtained through a multi-parameter monitoring module. The optimal FeC ratio was determined by comparison. S3. Second Stage Analysis - Operation Control: Under the optimal ratio, the influent load, hydraulic retention time, aeration intensity and carbon-nitrogen ratio are changed through the operation control module system. The "decontamination-gas generation" response curves under different operating scenarios are monitored to identify the optimal operating parameter range. S4. Third-stage analysis - Microbial mechanism revelation: Select typical scenarios within the optimal operating parameter range, and use the microbial analysis module to analyze the microbial community structure, key bacteria and abundance changes of functional genes related to CH4 and N2O production / consumption in the corresponding scenarios, and establish a causal chain of "operating parameters - microbial characteristics - environmental effectiveness". S5. Synergy Effect Assessment and Optimization: Using the synergy effect assessment module, integrate all data from S2 to S4, construct a synergy effect correlation model, calculate the synergy effect index for each scenario, and output a comprehensive evaluation report and system optimization operation plan. S6. Feedback Application: The optimal FeC ratio and optimal operation scheme obtained in S5 are applied to the design, construction or operation and renovation of subsurface flow constructed wetland projects for the treatment of livestock and poultry breeding wastewater on a real scale, and the operation effect of the project is continuously monitored and dynamically optimized.

[0013] Furthermore, in step S1, the wetland plants selected are one or more of reeds, cattails, canna lilies, or calamus, with a planting density of 20-30 plants / m². 2 The effective volume of the simulated wetland reaction unit is 50-100L, and the hydraulic gradient is 1%-3%.

[0014] Furthermore, in step S2, the standard operating conditions simulate the average water quality of the target livestock and poultry farming wastewater, with an average water quality of COD: 300-800 mg / L and NH4+: 0.5%. + -N: 50-150mg / L, TP: 5-20mg / L, hydraulic retention time is 3-7 days, and it is in an anaerobic or hypoxic state.

[0015] Furthermore, in step S3, the influent load adjustment range is 0.5-2.0 kg COD / (m³). 3 •d) The hydraulic retention time is adjustable from 2 to 10 days, and the aeration intensity is adjustable from 0.1 to 0.5 m. 3 / (m 2 ·h), the carbon-nitrogen ratio can be adjusted from 3:1 to 15:1.

[0016] Furthermore, in step S4, the key microbial communities include methanogenic archaea, methanogenic bacteria, ammonia-oxidizing bacteria, denitrifying bacteria, and iron-reducing bacteria; the functional genes include mcrA, pmoA, amoA, nirS, nirK, and nosZ; and in step S5, when constructing the association model, the predicted abundance of microbial functional genes is used as an explanatory variable, and the pollutant removal rate and greenhouse gas emission flux are used as response variables for multivariate statistical analysis.

[0017] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention acquires pollutant removal and greenhouse gas emission data simultaneously through a multi-parameter monitoring module, combines functional gene information from a microbial analysis module, and constructs a correlation model through a synergistic effect assessment module. This invention achieves, for the first time, a quantitative assessment of the synergistic effect of pollution reduction and carbon reduction in constructed wetlands, filling the gap in existing technologies that focus solely on pollutant removal or greenhouse gas emissions, and realizing the synergistic analysis of pollution reduction and carbon reduction.

[0018] 2. This invention establishes a quantitative correlation of the entire chain of "matrix ratio - operating parameters - microbial characteristics - synergistic efficacy". By revealing the intrinsic driving mechanism of synergistic effect through microbial mechanism, the optimization scheme is more scientific and targeted, avoiding the blindness of parameter control in traditional technology.

[0019] 3. The system of this invention integrates simulation, monitoring, control, analysis and evaluation functions. The method and process are clear and can be directly applied to the design, construction and operation and renovation of actual artificial wetland projects. It is especially suitable for livestock and poultry breeding wastewater treatment scenarios, which can significantly improve the wastewater purification effect, reduce greenhouse gas emissions, and have good economic, ecological and social benefits.

[0020] 4. This invention selects FeC composite matrix, which utilizes the electron transfer capability of iron-based materials and the adsorption and carrier function of biochar to enhance pollutant removal while regulating microbial metabolism and reducing greenhouse gas production; the optimal FeC ratio is determined through systematic analysis to give full play to the synergistic advantages of the composite matrix. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the process of the present invention; Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The present invention will be further described with reference to the accompanying drawings and embodiments: On the one hand, this invention proposes a system for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands, including a simulated wetland reaction unit, a multi-parameter monitoring module, an operation and control module, a microbial analysis module, and a synergistic effect evaluation module. The modules work together to achieve a full-process analysis from environmental simulation, data monitoring, parameter control to synergistic evaluation.

[0023] The above plan specifically includes: The simulated wetland reaction unit is used to simulate a subsurface flow constructed wetland environment, and its interior is filled with an FeC composite matrix. The FeC composite matrix is ​​composed of iron-based materials, biochar, and natural matrices such as zeolite or sand in a predetermined volume ratio. The iron-based materials are one or more of iron filings, pyrite, or zero-valent iron, and the biochar is one of bamboo charcoal, straw charcoal, or wood chip charcoal. Furthermore, the predetermined volume ratio of the FeC composite matrix is ​​set as follows: the mixture of iron-based materials and biochar accounts for 10%-40% of the total volume, and the natural matrices such as zeolite or sand account for 60%-90% of the total volume; and the mass ratio of iron-based materials to biochar is 1:1-5:1. This ratio range can accommodate both pollutant adsorption and microbial metabolic regulation needs.

[0024] The multi-parameter monitoring module is connected to the simulated wetland reaction unit to monitor influent water quality parameters, effluent water quality parameters, and the emission flux of CH4 and N2O gases generated inside the reaction unit in real time.

[0025] Specifically, the multi-parameter monitoring module includes an online water quality sensor and a greenhouse gas static chamber-chromatographic coupling acquisition and analysis device; the online water quality sensor is used to monitor COD and NH4. +Key water quality parameters such as -N and TP are collected periodically by a greenhouse gas static chamber-chromatographic analysis device, which collects gas samples above the simulated wetland reaction unit. The concentrations of CH4 and N2O are analyzed by gas chromatography, and the emission flux is calculated by combining the collection time and the chamber volume.

[0026] The operation control module is connected to the inlet of the simulated wetland reaction unit and is used to control the pollution load, hydraulic retention time, aeration conditions and carbon-nitrogen ratio of the influent according to preset strategies or feedback signals.

[0027] Specifically, the operation and control module includes a proportional pump, a flow controller, an aeration pump, and a carbon / nitrogen source addition device. The proportional pump and flow controller work together to regulate the influent flow rate, thereby changing the pollution load and hydraulic retention time. The aeration pump adjusts the aeration intensity to achieve switching between anaerobic, anoxic, and aerobic environments. The carbon / nitrogen source addition device (such as adding glucose as a carbon source and ammonium chloride as a nitrogen source) precisely controls the influent carbon-nitrogen ratio.

[0028] The microbial analysis module is used to perform DNA extraction, high-throughput sequencing, and bioinformatics analysis on samples collected from FeC composite matrix to obtain information on microbial community structure, diversity, and predicted abundance of functional genes related to greenhouse gas emissions.

[0029] The specific procedure is as follows: total microbial DNA is extracted from the matrix sample using a kit, and PCR amplification is performed on the V3-V4 region or ITS region of the 16S rRNA gene. Sequencing data is obtained through high-throughput sequencing. Bioinformatics software is used to perform sequence assembly, noise reduction, and OTU clustering to analyze the composition and diversity of the microbial community. Through functional gene prediction analysis, the predicted abundance of functional genes related to CH4 production (mcrA gene), CH4 oxidation (pmoA gene), ammonia oxidation (amoA gene), and denitrification (nirS, nirK, nosZ genes) is obtained.

[0030] The input end of the synergistic effect assessment module is connected to the multi-parameter monitoring module and the microbial analysis module, and the output end is connected to the operation and control module. It includes: a. Calculate pollutant removal efficiency based on water quality parameters, specifically for COD and NH4. + For pollutants such as -N and TP, the weight of each pollutant is calculated as (influent concentration - effluent concentration) / influent concentration × 100%, and the weight of each pollutant is determined by the entropy weight method to calculate the comprehensive pollutant removal index; for example, the weight coefficient calculation method proposed in "Application No. 202211738282.6, A method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands" is adopted. b. Calculate the global warming potential (GWP) based on gas emission fluxes. According to the latest IPCC standard, the GWP coefficient of CH4 is 28 and the GWP coefficient of N2O is 265. The calculation is performed using the formula GWP = CH4 emission flux × 28 + N2O emission flux × 265. c. Combining pollutant removal efficiency, global warming potential and microbial functional gene information, construct a correlation model for the synergistic effect of pollution reduction and carbon reduction. The correlation model can be a multiple regression model, a machine learning model (such as random forest, neural network) or a structural equation model. d. Calculate the Synergy Effect Index (SEI) based on the correlation model and generate optimized operating parameter suggestions, which are then fed back to the operation and control module. The Synergy Effect Index (SEI) can be calculated using one of the following formulas or a variant thereof: SEI = (Comprehensive Pollutant Removal Index) / (Comprehensive Greenhouse Gas Emission Index); In this formula, the composite greenhouse gas emissions index is the standardized GWP value; Or SEI = α × standardized removal rate - β × standardized GWP; α and β are weighting coefficients, which can be determined according to the pollution reduction and carbon reduction priorities of the actual project, and α+β=1.

[0031] On the other hand, the present invention provides a method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands using the above-mentioned system, comprising the following steps: S1. Construction and Initialization: Simulated wetland reaction units with different FeC composite matrix ratios are configured and wetland plants are planted. The wetland plants selected are one or more of reeds, cattails, thaliana, or calamus, with a planting density of 20-30 plants / m². 2 The simulated wetland reaction unit is made of plexiglass with an effective volume of 50-100L and a hydraulic slope of 1%-3% to simulate the water flow conditions of an actual subsurface flow constructed wetland. Specifically, five simulated wetland reaction units with different FeC ratios are configured. In each group, the predetermined volume ratio of the FeC composite matrix is ​​30% of a mixture of iron-based materials and biochar, and 70% of zeolite. The mass ratio of iron-based materials (zero-valent iron) to biochar (bamboo charcoal) in each group is 1:1, 2:1, 3:1, 4:1, and 5:1, respectively. Reeds are planted at a density of 25 plants / m². 2 Each reaction unit was injected with deionized water and soaked for 7 days to complete matrix initialization.

[0032] S2. First Stage Analysis - Matrix Optimization: Under standard operating conditions, each simulated wetland reaction unit was run. Pollutant removal rates and greenhouse gas emissions were obtained through a multi-parameter monitoring module, and the optimal FeC ratio was determined through comparison. Standard operating conditions were based on the average water quality of the simulated target livestock and poultry farm wastewater, specifically: COD: 500 mg / L, NH4+: 500 mg / L.+ -N: 100 mg / L, TP: 12 mg / L, hydraulic retention time: 5 days, anaerobic condition (no aeration). Each simulated wetland reaction unit operated continuously for 30 days, with influent and effluent samples collected every 3 days. COD and NH4 were detected using online water quality sensors. + -N and TP concentrations were used to calculate the removal rate and comprehensive pollutant removal index. CH4 and N2O emission fluxes were monitored every 5 days using a greenhouse gas static chamber-chromatographic analysis device, and GWP was calculated. The synergistic effect index (SEI) of the 5 reaction units was compared, and the FeC ratio corresponding to the maximum SEI value was selected as the optimal ratio.

[0033] S3. Second Stage Analysis - Operation Control: Under optimal mixing ratios, the influent load, hydraulic retention time, aeration intensity, and carbon-nitrogen ratio are adjusted via the operation control module system. The "decontamination-gas generation" response curves under different operating scenarios are monitored to identify the optimal operating parameter range. The control range for each operating parameter is: influent load 0.5-2.0 kg COD / (m³). 3 ·d) Hydraulic retention time 2-10 days, aeration intensity 0.1-0.5m 3 / (m 2 •h), carbon-nitrogen ratio 3:1 to 15:1. An orthogonal experimental design was adopted, setting up 25 operating scenarios, each scenario running for 15 days. After stable operation, the pollutant removal comprehensive index and GWP were monitored, and the "decontamination-gas production" response curve was plotted. The optimal range of each parameter was determined by response surface methodology.

[0034] S4. Third-Stage Analysis - Microbial Mechanism Revelation: Within the optimal operating parameter range, typical scenarios (such as low, medium, and high influent load levels) are selected. The microbial analysis module is used to analyze the microbial community structure, key bacterial groups, and abundance changes of functional genes related to CH4 and N2O production / consumption under these scenarios, establishing a causal chain of "operating parameters - microbial characteristics - environmental effectiveness." Specifically, after stable operation in each typical scenario, FeC composite matrix samples are collected, total microbial DNA is extracted, and high-throughput sequencing is performed. The relative abundance changes of key bacterial groups such as methanogenic archaea, methanogenic bacteria, ammonia-oxidizing bacteria, denitrifying bacteria, and iron-reducing bacteria are analyzed. The predicted abundance of functional genes such as mcrA, pmoA, amoA, nirS, nirK, and nosZ are detected. Through correlation analysis, the impact of operating parameters on key bacterial groups and functional genes is clarified, as well as the quantitative correlation between key bacterial groups / functional genes and pollutant removal rates and greenhouse gas emission fluxes, constructing a causal chain.

[0035] S5. Synergistic Effect Assessment and Optimization: Utilizing the synergistic effect assessment module, all data from S2 to S4 are integrated to construct a synergistic effect correlation model. The synergistic effect index for each scenario is calculated, and a comprehensive evaluation report and system optimization operation plan are output. When constructing the correlation model, the predicted abundance of microbial functional genes is used as an explanatory variable, and pollutant removal rate and greenhouse gas emission flux are used as response variables for multivariate statistical analysis. Based on the correlation model, the SEI under different parameter combinations is predicted, and the parameter combination corresponding to the maximum SEI value is selected as the optimal operation plan. The optimal operation plan includes the optimal FeC ratio, influent load, hydraulic retention time, aeration intensity, and carbon-nitrogen ratio.

[0036] S6. Feedback Application: The optimal FeC ratio and operating scheme obtained in S5 will be applied to the design, construction, or operation and renovation of subsurface flow constructed wetland projects for large-scale livestock and poultry wastewater treatment, and the operational effectiveness will be continuously monitored and dynamically optimized. Specifically, for a treatment capacity of 500m³... 3 The / d subsurface flow constructed wetland project for treating livestock and poultry breeding wastewater uses substrate filled with the optimal FeC ratio and sets parameters such as influent flow rate and aeration intensity according to the optimal operation plan. During the operation of the project, the influent / effluent water quality and greenhouse gas emission flux are monitored regularly, and substrate samples are collected quarterly for microbial analysis. Combining the monitoring data and microbial information, the operating parameters are dynamically adjusted through the synergistic effect evaluation module to ensure that the project achieves long-term stable pollution reduction and carbon reduction synergistic optimization.

[0037] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands, characterized in that: include: The simulated wetland reaction unit is used to simulate the subsurface flow constructed wetland environment. Its interior is filled with FeC composite matrix, which is composed of iron-based materials, biochar and natural matrix such as zeolite or sand and gravel mixed in a predetermined volume ratio. The multi-parameter monitoring module is connected to the simulated wetland reaction unit and is used to monitor the influent water quality parameters, effluent water quality parameters, and the emission flux of CH4 and N2O gases generated inside the simulated wetland reaction unit in real time. The operation and control module is connected to the inlet of the simulated wetland reaction unit and is used to control the pollution load, hydraulic retention time, aeration conditions and carbon-nitrogen ratio of the influent according to preset strategies or feedback signals. The microbial analysis module is used to perform DNA extraction, high-throughput sequencing, and bioinformatics analysis on samples collected from FeC composite matrix to obtain information on microbial community structure, diversity, and predicted abundance of functional genes related to greenhouse gas emissions. The synergy effect assessment module has its input connected to the multi-parameter monitoring module and the microbial analysis module, and its output connected to the operation and control module; the synergy effect assessment module is used for: a. Calculate pollutant removal efficiency based on water quality parameters; b. Calculate global warming potential based on gas emission fluxes; c. Construct a correlation model for the synergistic effect of pollution reduction and carbon reduction by combining pollutant removal efficiency, global warming potential and microbial functional gene information; d. Based on the correlation model, calculate the synergistic effect index and generate suggestions for optimizing operating parameters, which are then fed back to the operation control module.

2. The system and method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 1, characterized in that: In the FeC composite matrix, the mixture of iron-based materials and biochar accounts for 10%-40% of the total volume, and natural matrices such as zeolite or sand account for 60%-90% of the total volume, and the mass ratio of iron-based materials to biochar is 1:1-5:

1. Furthermore, the iron-based material is one or more of iron filings, pyrite, or zero-valent iron; Biochar is one of bamboo charcoal, straw charcoal, or wood chip charcoal.

3. The system and method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 1, characterized in that: The multi-parameter monitoring module includes an online water quality sensor and a greenhouse gas static chamber-chromatographic coupling acquisition and analysis device.

4. A system and method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 1, characterized in that: The operation control module includes a proportional pump, a flow controller, an aeration pump, and a carbon / nitrogen source addition device.

5. A system and method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 1, characterized in that: The association model constructed by the synergy effect assessment module is a multiple regression model, a machine learning model, or a structural equation model, and the synergy effect index (SEI) is calculated using one of the following formulas or a variant thereof: SEI = (Comprehensive Pollutant Removal Index) / (Comprehensive Greenhouse Gas Emission Index); The composite greenhouse gas emissions index in the formula is the standardized GWP value; Or SEI = α × standardized removal rate - β × standardized GWP; In the formula, α and β are weighting coefficients.

6. A method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands using the system described in any one of claims 1-5, characterized in that: Includes the following steps: S1. Construction and initialization: Configure simulated wetland reaction units with different FeC composite matrix ratios and plant wetland plants; S2, First Stage Analysis - Matrix Optimization: Under standard operating conditions, each simulated wetland reaction unit was run, and its pollutant removal rate and greenhouse gas emission data were obtained through a multi-parameter monitoring module. The optimal FeC ratio was determined by comparison. S3. Second Stage Analysis - Operation Control: Under the optimal ratio, the influent load, hydraulic retention time, aeration intensity and carbon-nitrogen ratio are changed through the operation control module system. The "decontamination-gas generation" response curves under different operating scenarios are monitored to identify the optimal operating parameter range. S4. Third-stage analysis - Microbial mechanism revelation: Select typical scenarios within the optimal operating parameter range, and use the microbial analysis module to analyze the microbial community structure, key bacteria and abundance changes of functional genes related to CH4 and N2O production / consumption in the corresponding scenarios, and establish a causal chain of "operating parameters - microbial characteristics - environmental effectiveness". S5. Synergy Effect Assessment and Optimization: Using the synergy effect assessment module, integrate all data from S2 to S4, construct a synergy effect correlation model, calculate the synergy effect index for each scenario, and output a comprehensive evaluation report and system optimization operation plan. S6. Feedback Application: The optimal FeC ratio and optimal operation scheme obtained in S5 are applied to the design, construction or operation and renovation of subsurface flow constructed wetland projects for the treatment of livestock and poultry breeding wastewater on a real scale, and the operation effect of the project is continuously monitored and dynamically optimized.

7. The method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 6, characterized in that: In step S1, the wetland plants selected are one or more of reeds, cattails, canna lilies, or sweet flag, with a planting density of 20-30 plants / m². 2 ; The effective volume of the simulated wetland reaction unit is 50-100L, and the hydraulic gradient is 1%-3%.

8. The method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 6, characterized in that: In step S2, the standard operating conditions are the average water quality of the simulated target livestock and poultry breeding wastewater, with an average water quality of COD: 300-800 mg / L and NH4+: 0.5%. + -N: 50-150mg / L, TP: 5-20mg / L, hydraulic retention time is 3-7 days, and it is in an anaerobic or hypoxic state.

9. The method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 6, characterized in that: In step S3, the influent load is adjusted within the range of 0.5-2.0 kg COD / (m³). 3 •d) The hydraulic retention time is adjustable from 2 to 10 days, and the aeration intensity is adjustable from 0.1 to 0.5 m. 3 / (m 2 ·h), the carbon-nitrogen ratio can be adjusted from 3:1 to 15:

1.

10. The method for analyzing the synergistic effect of pollution reduction and carbon reduction in constructed wetlands according to claim 6, characterized in that: In step S4, the key bacterial groups include methanogenic archaea, methanogenic bacteria, ammonia-oxidizing bacteria, denitrifying bacteria, and iron-reducing bacteria. The functional genes include mcrA, pmoA, amoA, nirS, nirK, and nosZ; and in step S5, when constructing the association model, the predicted abundance of microbial functional genes is used as the explanatory variable, and the pollutant removal rate and greenhouse gas emission flux are used as the response variables for multivariate statistical analysis.

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