Rural sewage treatment method of enhanced anaerobic-aerobic coupled constructed wetland

Abstract

The invention discloses a rural sewage treatment method of an enhanced anaerobic-aerobic coupled constructed wetland, and relates to the technical field of rural sewage treatment and ecological environment engineering, the treatment method comprises the following steps: S1, sewage pretreatment; s2, strengthening anaerobic wetland treatment; s3, intensified aerobic wetland treatment: introducing effluent of the intensified anaerobic wetland unit into the intensified aerobic wetland unit, laying efficient oxygen supply filler in the intensified aerobic wetland unit, planting aquatic plants, and arranging an intermittent aeration device; and S4, tail water purification and reuse: introducing the effluent of the enhanced aerobic wetland unit into a tail water purification unit, filling the tail water purification unit with a quartz sand filter material, and recycling or discharging the purified tail water after the water quality is monitored to reach the standard. According to the rural sewage treatment method of the enhanced anaerobic-aerobic coupled constructed wetland, efficient treatment of rural sewage and stable operation of the system are realized by optimizing the system structure, enhancing functions of filler and microorganisms and introducing an intelligent regulation and control model.

Description

Technical Field

[0001] This application relates to the field of rural sewage treatment and ecological environment engineering technology, and more specifically, to a rural sewage treatment method using an enhanced anaerobic-aerobic coupled constructed wetland. Background Technology

[0002] Rural sewage is characterized by "high dispersion, large fluctuations in water quality and quantity, and moderate pollutant concentrations." Traditional treatment technologies (such as septic tanks and simple oxidation ponds) have problems such as low pollutant removal efficiency and weak resistance to shock loads, making it difficult to meet increasingly stringent environmental emission standards.

[0003] Constructed wetlands, as an ecological wastewater treatment technology, have advantages such as low cost, simple maintenance, and eco-friendliness, and have been widely used in rural wastewater treatment. However, traditional constructed wetlands have the following key problems: Anaerobic-aerobic coupling is uncoordinated: Traditional wetlands are mostly single anaerobic or aerobic environments, or achieve aerobic processes through natural reoxygenation, resulting in an incomplete nitrification-denitrification nitrogen removal pathway; Low pollutant removal efficiency: The adsorption capacity of a single packing material is limited, and the activity of microorganisms is greatly affected by environmental factors (temperature, DO), resulting in a low TP removal rate and difficulty in meeting emission standards. Operating parameter control relies on experience: Wetland operating parameters (such as HRT and aeration intensity) are mostly determined through static experiments and cannot be dynamically adjusted according to water quality fluctuations, resulting in weak system resistance to shock loads; Poor adaptability to low temperatures: When the water temperature is below 10℃ in winter, the activity of microorganisms decreases significantly, and the removal rates of COD and nitrogen and phosphorus are greatly reduced.

[0004] To address the aforementioned issues, existing technologies have introduced anaerobic-aerobic coupled wetland designs (such as the "An Anaerobic-Aerobic Alternating Constructed Wetland Wastewater Treatment System" disclosed in CN109835177A). However, these technologies still haven't overcome the bottleneck of "single-function packing material and lack of intelligent control," making it difficult to achieve efficient and stable pollutant removal. Therefore, developing a constructed wetland treatment method with enhanced coupling and intelligent control is of great significance for promoting the upgrading of rural wastewater treatment technology. This paper proposes an enhanced anaerobic-aerobic coupled constructed wetland method for rural wastewater treatment, addressing the relevant technical problems mentioned above. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, this application provides a rural sewage treatment method using an enhanced anaerobic-aerobic coupled constructed wetland to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, this application provides the following technical solution: a rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland, the method comprising: S1. Wastewater pretreatment: After removing suspended solids from rural domestic sewage or aquaculture wastewater through a screen, it is introduced into an equalization tank for water quality and quantity homogenization. The equalization tank is equipped with a stirring device to control the hydraulic mixing intensity at 0.1-0.3 m / s, and the hydraulic retention time (HRT) is 4-8 h. S2. Enhanced anaerobic wetland treatment: The pretreated wastewater is introduced into the enhanced anaerobic wetland unit, which is filled with composite anaerobic packing material and inoculated with low-temperature resistant anaerobic microbial agents. The water temperature in the control unit is 15-30℃ and the HRT is 12-24h. Part of the COD in the wastewater is removed and nitrate denitrification is achieved through anaerobic reaction. S3. Enhanced aerobic wetland treatment: The effluent from the enhanced anaerobic wetland unit is introduced into the enhanced aerobic wetland unit. The enhanced aerobic wetland unit is equipped with high-efficiency oxygen supply packing material, planted with aquatic plants, and equipped with an intermittent aeration device to control the dissolved oxygen concentration (DO) in the enhanced anaerobic wetland unit to be 2-4 mg / L and the HRT to be 8-16 h. COD is degraded through aerobic reaction and ammonia nitrogen nitrification is achieved. S4. Wastewater purification and reuse: The effluent from the enhanced aerobic wetland unit is introduced into the wastewater purification unit, which is filled with quartz sand filter media with a particle size of 1-3mm and a filtration rate of 0.5-1.0m / h. After purification, the wastewater is reused or discharged after meeting the water quality standards through water quality monitoring.

[0007] Furthermore, the regulating tank, the enhanced anaerobic wetland unit, the enhanced aerobic wetland unit, and the effluent purification unit are connected in sequence via water pumps.

[0008] Furthermore, the treatment method is based on an improved BP neural network water quality prediction model to predict the effluent pollutant concentration of each treatment unit in real time, and combines particle swarm optimization algorithm, i.e., PSO, to optimize and regulate the HRT of the enhanced anaerobic wetland unit and the aeration intensity and DO concentration of the enhanced aerobic wetland unit.

[0009] Furthermore, the screen in the wastewater pretreatment is a fine screen with a screen width of 0.5-1.0 mm; a level sensor and a temperature sensor are installed in the equalization tank to monitor water quality and quantity parameters in real time and transmit them to the control system.

[0010] Furthermore, the composite anaerobic filler material filling the enhanced anaerobic wetland unit is composed of volcanic rock particles and biochar, with the volcanic rock particles and biochar mixed at a volume ratio of 3:1, a particle size of 5-10 mm, and a specific surface area of ​​800-1200 g / m². The low-temperature resistant anaerobic microbial agent contains methanogens and denitrifying bacteria, and the inoculum size is 5-10 g / L.

[0011] Furthermore, in the S3 enhanced aerobic wetland unit, the high-efficiency oxygen supply filler is made of ceramsite and zeolite, and the ceramsite and zeolite are mixed in a volume ratio of 2:1 with a particle size of 3-8mm. The aquatic plants are sedge and calamus, and the sedge and calamus are mixed in a plant ratio of 1:1 with a planting density of 9-12 plants / m².

[0012] Furthermore, the intermittent aeration device adopts microporous aeration discs with an aeration disc arrangement density of 1-2 discs / m², the aeration intensity of the intermittent aeration device is 0.5-1.2 m³ / (m²・h), and the aeration cycle is "aeration for 30 min - aeration stop for 60 min"; DO sensors are installed in the root zone of aquatic plants to provide real-time feedback on the DO concentration in the enhanced aerobic wetland unit and adjust the aeration parameters.

[0013] Furthermore, the structure of the improved BP neural network water quality prediction model is "input layer - hidden layer - output layer", wherein: Input layer parameters include: COD concentration of effluent from the equalization tank, Concentration and TP concentration are denoted as follows: , , Enhanced anaerobic wetland unit HRT is denoted as The aeration intensity of the enhanced aerobic wetland unit is recorded as follows: and DO concentration denoted as There are a total of 6 input variables; The number of hidden layer nodes was determined to be 12-18 through trial and error, and the Sigmoid function was used to map the input signal to the [0,1] interval. Output layer parameters include: COD of the effluent from the enhanced anaerobic wetland unit, Concentration, and denoted as respectively , Strengthen the COD of the effluent from the aerobic wetland unit. , TP concentration, and denoted as respectively , , There are a total of 5 output variables. The momentum term is introduced during model training to improve the weight update formula: ,in For the learning rate, and The value range is 0.01-0.05; It is the momentum factor, and The value range is 0.8-0.9; This is an error signal; For input variables; for The weight of each moment; for The updated weights at each step; for The weight of each moment; Model training: The model is trained using historical monitoring data, which includes water quality parameters, water quality parameters and effluent concentration. When the prediction error meets the requirement of RMSE < 5%, the model is put into real-time prediction.

[0014] Furthermore, the objective function of the particle swarm optimization algorithm is a multi-objective optimization function. : ,in , , , These are weighting coefficients, and their values ​​range from 0.2 to 0.3. , The cost per unit of system processing; The maximum permissible unit processing cost; The particle position update formula for the particle swarm optimization algorithm is: ; The speed update formula is: ,in This is the inertial weight, and its value ranges from 0.4 to 0.9; , For learning factors; , A random number in the range [0,1]. For the first The optimal position of each individual particle; The globally optimal position; For the first Individual particles The position of time, corresponding optimization parameters , and ; For the first Individual particles The position is updated in real time; For the first Individual particles The speed of time; For the first Individual particles The speed of time; Optimization process: Initialize the particle swarm, iteratively calculate the objective function until the number of iterations reaches the set value or the objective function converges, output the optimal operating parameters and transmit them to the control system for execution.

[0015] The technical effects and advantages of this application are as follows: Compared with existing technologies, this enhanced anaerobic-aerobic coupled constructed wetland rural sewage treatment method achieves efficient rural sewage treatment and stable system operation by optimizing system structure, enhancing the function of packing materials and microorganisms, and introducing intelligent control models. Enhanced anaerobic-aerobic coupling for high pollutant removal efficiency: Composite anaerobic packing material (volcanic rock + biochar) combined with low-temperature resistant bacterial agents enhances anaerobic degradation and denitrification; high-efficiency oxygen supply packing material (ceramsite + zeolite) combined with intermittent aeration enhances aerobic nitrification, resulting in high system COD removal rate. The removal rate and TP removal rate were both effectively improved, and the effluent met the Class A standard. Intelligent dynamic regulation and strong resistance to shock loads: Improved BP neural network for real-time water quality prediction and PSO algorithm for dynamic optimization of operating parameters, capable of coping with fluctuations in rural sewage quality and quantity (such as sudden drops in COD during the rainy season and peak aquaculture season). (This increases the system's stability). Eco-friendly and low operating cost: It uses ecological fillers and aquatic plants, without the addition of chemical agents; intermittent aeration and intelligent control reduce energy consumption, and the unit treatment cost is significantly lower than that of traditional wetlands. Wide applicability and easy maintenance: The system can be modularly designed and is suitable for decentralized rural areas; the filler has a long replacement cycle and aquatic plants can be harvested regularly, reducing the workload of maintenance. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the method of this application; Figure 2 This is a schematic diagram of the connection structure of each unit in the wastewater treatment process of this application.

[0017] In the diagram: 1. Equalization tank; 2. Enhanced anaerobic wetland unit; 3. Enhanced aerobic wetland unit; 4. Wastewater purification unit; 5. Water pump. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] Example As attached Figure 1 The above describes a rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland, the method comprising: S1. Wastewater pretreatment: After removing suspended solids from rural domestic sewage or aquaculture wastewater through a screen, it is introduced into an equalization tank for water quality and quantity homogenization. The equalization tank is equipped with a stirring device to control the hydraulic mixing intensity at 0.1-0.3 m / s, and the hydraulic retention time (HRT) is 4-8 h. The screen used in the wastewater pretreatment is a fine screen with a mesh width of 0.5-1.0 mm; the equalization tank is equipped with a level sensor and a temperature sensor to monitor water quality and quantity parameters in real time and transmit them to the control system. S2. Enhanced anaerobic wetland treatment: The pretreated wastewater is introduced into the enhanced anaerobic wetland unit, which is filled with composite anaerobic packing material and inoculated with low-temperature resistant anaerobic microbial agents. The water temperature in the control unit is 15-30℃ and the HRT is 12-24h. Part of the COD in the wastewater is removed and nitrate denitrification is achieved through anaerobic reaction. The composite anaerobic filler material used in the enhanced anaerobic wetland unit consists of volcanic rock particles and biochar, mixed at a volume ratio of 3:1. The particle size is 5-10 mm, and the specific surface area of ​​the biochar is 800-1200. The low-temperature resistant anaerobic microbial agent contains methanogens and denitrifying bacteria, and the inoculum size is 5-10 g / L; S3. Enhanced aerobic wetland treatment: The effluent from the enhanced anaerobic wetland unit is introduced into the enhanced aerobic wetland unit. The enhanced aerobic wetland unit is equipped with high-efficiency oxygen supply packing material, planted with aquatic plants, and equipped with an intermittent aeration device to control the dissolved oxygen concentration (DO) in the enhanced anaerobic wetland unit to be 2-4 mg / L and the HRT to be 8-16 h. COD is degraded through aerobic reaction and ammonia nitrogen nitrification is achieved. In the S3 enhanced aerobic wetland unit, the high-efficiency oxygen supply filler material is ceramsite and zeolite, and the ceramsite and zeolite are mixed in a volume ratio of 2:1 with a particle size of 3-8mm. The aquatic plants are sedge and calamus, and the sedge and calamus are mixed in a plant number ratio of 1:1 with a planting density of 9-12 plants / m².

[0020] The intermittent aeration device uses microporous aeration discs with an arrangement density of 1-2 discs / m². The aeration intensity of the intermittent aeration device is 0.5-1.2 m³ / (m²・h), and the aeration cycle is "aeration for 30 minutes - aeration stopped for 60 minutes". DO sensors are installed in the root zone of aquatic plants to provide real-time feedback on the DO concentration within the enhanced aerobic wetland unit and to adjust the aeration parameters.

[0021] S4. Wastewater purification and reuse: The effluent from the enhanced aerobic wetland unit is introduced into the wastewater purification unit, which is filled with quartz sand filter media with a particle size of 1-3mm and a filtration rate of 0.5-1.0m / h. After purification, the wastewater is reused or discharged after meeting the water quality standards through water quality monitoring.

[0022] The treatment method is based on an improved BP neural network water quality prediction model to predict the effluent pollutant concentration of each treatment unit in real time. It is combined with particle swarm optimization algorithm (PSO) to optimize and control the HRT of the enhanced anaerobic wetland unit and the aeration intensity and DO concentration of the enhanced aerobic wetland unit. The improved BP neural network water quality prediction model has a structure of "input layer - hidden layer - output layer", where: Input layer parameters include: COD concentration of effluent from the equalization tank, Concentration and TP concentration are denoted as follows: , , Enhanced anaerobic wetland unit HRT is denoted as The aeration intensity of the enhanced aerobic wetland unit is recorded as follows: and DO concentration denoted as There are a total of 6 input variables; The number of hidden layer nodes was determined to be 12-18 through trial and error, and the Sigmoid function was used to map the input signal to the [0,1] interval. Output layer parameters include: COD of the effluent from the enhanced anaerobic wetland unit, Concentration, and denoted as respectively , Strengthen the COD of the effluent from the aerobic wetland unit. , TP concentration, and denoted as respectively , , There are a total of 5 output variables. The momentum term is introduced during model training to improve the weight update formula: ,in For the learning rate, and The value range is 0.01-0.05; It is the momentum factor, and The value range is 0.8-0.9; This is an error signal; For input variables; for The weight of each moment; for The updated weights at each step; for The weight of each moment; Model training: The model is trained using historical monitoring data, which includes water quality parameters, water quality parameters and effluent concentration. When the prediction error meets the requirement of RMSE < 5%, the model is put into real-time prediction.

[0023] The objective function of the particle swarm optimization algorithm is a multi-objective optimization function. : ,in , , , These are weighting coefficients, and their values ​​range from 0.2 to 0.3. , The cost per unit of system processing; The maximum permissible unit processing cost; The particle position update formula for the particle swarm optimization algorithm is: ; The speed update formula is: ,in This is the inertial weight, and its value ranges from 0.4 to 0.9; , For learning factors; , A random number in the range [0,1]. For the first The optimal position of each individual particle; The globally optimal position; For the first Individual particles The position of time, corresponding optimization parameters , and ; For the first Individual particles The position is updated in real time; For the first Individual particles The speed of time; For the first Individual particles The speed of time; Optimization process: Initialize the particle swarm, iteratively calculate the objective function until the number of iterations reaches the set value or the objective function converges, output the optimal operating parameters and transmit them to the control system for execution.

[0024] The equalization tank, enhanced anaerobic wetland unit, enhanced aerobic wetland unit, and effluent purification unit are connected in sequence by water pumps.

[0025] Finally: The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland, characterized in that, The processing method includes: S1. Wastewater pretreatment: After removing suspended solids from rural domestic sewage or aquaculture wastewater through a screen, it is introduced into an equalization tank for water quality and quantity homogenization. The equalization tank is equipped with a stirring device to control the hydraulic mixing intensity at 0.1-0.3 m / s, and the hydraulic retention time (HRT) is 4-8 h. S2. Enhanced anaerobic wetland treatment: The pretreated wastewater is introduced into the enhanced anaerobic wetland unit, which is filled with composite anaerobic packing material and inoculated with low-temperature resistant anaerobic microbial agents. The water temperature in the control unit is 15-30℃ and the HRT is 12-24h. Part of the COD in the wastewater is removed and nitrate denitrification is achieved through anaerobic reaction. S3. Enhanced aerobic wetland treatment: The effluent from the enhanced anaerobic wetland unit is introduced into the enhanced aerobic wetland unit. The enhanced aerobic wetland unit is equipped with high-efficiency oxygen supply packing material, planted with aquatic plants, and equipped with an intermittent aeration device to control the dissolved oxygen concentration (DO) in the enhanced anaerobic wetland unit to be 2-4 mg / L and the HRT to be 8-16 h. COD is degraded through aerobic reaction and ammonia nitrogen nitrification is achieved. S4. Wastewater purification and reuse: The effluent from the enhanced aerobic wetland unit is introduced into the wastewater purification unit, which is filled with quartz sand filter media with a particle size of 1-3mm and a filtration rate of 0.5-1.0m / h. After purification, the wastewater is reused or discharged after meeting the water quality standards through water quality monitoring.

2. The rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 1, characterized in that: The regulating tank, enhanced anaerobic wetland unit, enhanced aerobic wetland unit, and effluent purification unit are connected in sequence by water pumps.

3. The rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 2, characterized in that: The treatment method is based on an improved BP neural network water quality prediction model to predict the effluent pollutant concentration of each treatment unit in real time. It combines particle swarm optimization algorithm (PSO) to optimize and control the HRT of the enhanced anaerobic wetland unit and the aeration intensity and DO concentration of the enhanced aerobic wetland unit.

4. The rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 1, characterized in that: The screen used in the wastewater pretreatment is a fine screen with a mesh width of 0.5-1.0 mm; a level sensor and a temperature sensor are installed in the equalization tank to monitor water quality and quantity parameters in real time and transmit them to the control system.

5. The rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 1, characterized in that: The composite anaerobic filler material filling the enhanced anaerobic wetland unit is composed of volcanic rock particles and biochar, with the volcanic rock particles and biochar mixed at a volume ratio of 3:

1. The particle size is 5-10 mm, and the specific surface area of ​​the biochar is 800-1200. The low-temperature resistant anaerobic microbial agent contains methanogens and denitrifying bacteria, and the inoculum size is 5-10 g / L.

6. The rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 1, characterized in that: The S3 enhanced aerobic wetland unit is filled with high-efficiency oxygen supply filler consisting of expanded clay and zeolite, with the expanded clay and zeolite mixed in a volume ratio of 2:1 and a particle size of 3-8mm. The aquatic plants are sedge and calamus, with the sedge and calamus mixed in a plant ratio of 1:1 and a planting density of 9-12 plants / m².

7. A rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 6, characterized in that: The intermittent aeration device uses microporous aeration discs with an arrangement density of 1-2 discs / m². The aeration intensity of the intermittent aeration device is 0.5-1.2 m³ / (m²・h), and the aeration cycle is "aeration for 30 minutes - aeration stopped for 60 minutes". DO sensors are installed in the root zone of aquatic plants to provide real-time feedback on the DO concentration within the enhanced aerobic wetland unit and to adjust the aeration parameters.

8. A rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 7, characterized in that: The improved BP neural network water quality prediction model has the structure of "input layer - hidden layer - output layer", where: Input layer parameters include: COD concentration of effluent from the equalization tank, Concentration and TP concentration are denoted as follows: , , Enhanced anaerobic wetland unit HRT is denoted as The aeration intensity of the enhanced aerobic wetland unit is recorded as follows: and DO concentration denoted as There are a total of 6 input variables; The number of hidden layer nodes was determined to be 12-18 through trial and error, and the Sigmoid function was used to map the input signal to the [0,1] interval. Output layer parameters include: COD of the effluent from the enhanced anaerobic wetland unit, Concentration, and denoted as respectively , Strengthen the COD of the effluent from the aerobic wetland unit. , TP concentration, and denoted as respectively , , There are a total of 5 output variables. The momentum term is introduced during model training to improve the weight update formula: ,in For the learning rate, and The value range is 0.01-0.05; It is the momentum factor, and The value range is 0.8-0.9; This is an error signal; For input variables; for The weight of each moment; for The updated weights at each step; for The weight of each moment; Model training: The model is trained using historical monitoring data, which includes water quality parameters, water quality parameters and effluent concentration. When the prediction error meets the requirement of RMSE < 5%, the model is put into real-time prediction.

9. A rural wastewater treatment method using an enhanced anaerobic-aerobic coupled constructed wetland according to claim 8, characterized in that: The objective function of the particle swarm optimization algorithm is a multi-objective optimization function. : ,in , , , These are weighting coefficients, and their values ​​range from 0.2 to 0.

3. , The cost per unit of system processing; The maximum permissible unit processing cost; The particle position update formula for the particle swarm optimization algorithm is: ; The speed update formula is: ,in This is the inertial weight, and its value ranges from 0.4 to 0.9; , For learning factors; , A random number in the range [0,1]. For the first The optimal position of each individual particle; The globally optimal position; For the first Individual particles The position of time, corresponding optimization parameters , and ; For the first Individual particles The position is updated in real time; For the first Individual particles The speed of time; For the first Individual particles The speed of time; Optimization process: Initialize the particle swarm, iteratively calculate the objective function until the number of iterations reaches the set value or the objective function converges, output the optimal operating parameters and transmit them to the control system for execution.

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