Tail water treatment ecological benefit analysis method based on life cycle evaluation

Abstract

The invention discloses a tail water treatment ecological benefit analysis method based on life cycle evaluation, which is based on operation of a tail water treatment system, a system water inlet module and a drainage module are provided with water quality sensors, and a treatment module is provided with a gas flow sensor and a gas detector. The water quality monitoring data and the gas monitoring data are transmitted to the data center and are preprocessed; the system is also provided with a medicament feeding device and an operation device; a pollution product analysis model is established based on an LCA method, the total pollution amount is calculated according to monitoring data, medicament putting data and operation data, and an ecological benefit model is established to analyze ecological benefits. The analysis method provided by the invention is based on life cycle evaluation, so that the analysis result is more comprehensive and accurate; the method comprises a preprocessing step, so that the influence of non-uniform concentration distribution on the accuracy of an evaluation result is avoided; and the ecological benefit model gives an evaluation grade, so that the evaluation result is more intuitive.

Description

Technical Field

[0001] This invention belongs to the field of wastewater treatment effect analysis and evaluation technology, specifically involving a method for analyzing the ecological benefits of effluent treatment based on life cycle assessment. Background Technology

[0002] Wastewater refers to water bodies formed after preliminary treatment of various types of wastewater generated in production, daily life, and other activities. It encompasses various types, including aquaculture wastewater, end-of-pipe industrial wastewater, and secondary effluent from municipal wastewater treatment plants. Preliminary treatment typically only filters out large particulate pollutants; particulate or water-soluble pollutants and various compounds remain in the water. To ensure the ecological safety of the discharged water body and the water resource recycling rate, wastewater requires further deep purification treatment. However, wastewater treatment often requires the addition of various agents that can react with pollutants and the maintenance of certain reaction conditions, thus incurring high treatment costs. To control wastewater treatment costs within a low range while ensuring the quality of the treated water, it is necessary to evaluate and analyze the ecological benefits of wastewater treatment using appropriate methods, thereby developing a low-cost treatment plan while meeting water quality requirements. Current research on wastewater treatment effectiveness analysis methods largely focuses on improving analytical efficiency and accuracy through big data. These methods only concern the wastewater treatment process itself. However, the effluent treatment process consumes a large amount of resources and energy, and the production of these resources and energy also generates pollutants, impacting the ecological environment. This impact must also be included in the scope of ecological benefit analysis. Therefore, Life Cycle Assessment (LCA) is suitable for the ecological benefit analysis of effluent treatment. Furthermore, current wastewater treatment effectiveness analysis methods typically only measure treatment effectiveness using pollutant content indicators such as Chemical Oxygen Demand (COD) before and after treatment, failing to directly measure the ecological benefits of the treatment process. In conclusion, it is necessary to propose an ecological benefit analysis method for effluent treatment based on life cycle assessment, which includes the ecological impact of the resources and energy used in effluent treatment within the analysis scope and can quantify the ecological benefits. Summary of the Invention

[0003] The purpose of this invention is to provide a method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment. This method analyzes the ecological impact of the wastewater treatment process itself, as well as the ecological impact of the materials and energy used in the production and treatment, based on the LCA method, and provides an intuitive evaluation of the ecological benefits of wastewater treatment through ecological benefit indicators.

[0004] The technical solution adopted in this invention is as follows: A method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment, operating on a wastewater treatment system, the wastewater treatment system comprising multiple operating devices for driving system operation and a dosing device for dispensing wastewater treatment agents; specifically including the following steps: S1. Establish a monitoring system. Water quality sensors are installed in both the inlet and outlet modules of the wastewater treatment system. Sensors are installed in the treatment modules to monitor the volume, composition, and concentration of each component of the emitted gas. The monitoring system includes all the above sensors and a data center. All sensors are connected to the data center and transmit the monitoring data to the data center in real time.

[0005] S2. Select the types of pollutants and gases to be monitored in the water, and set the monitoring cycle, which is divided into multiple sampling stages of equal duration; the dispensing device can dispense a variety of agents, and the power consumption data of the operating device, as well as the types and amounts of agents dispensed by the dispensing device, are recorded. The data center stores the received data and performs preprocessing.

[0006] S3. Establish a pollution product analysis model based on the LCA method. The pollution product analysis model is used to determine the total pollution amount for a monitoring period based on the electricity consumption data, reagent dosage data, and emission gas monitoring data within that monitoring period.

[0007] S4. Establish an ecological benefit model, which analyzes the ecological benefits of a monitoring period based on water quality index data before and after treatment and total pollution within a certain monitoring period. The water quality index is used to measure the concentration of pollutants in the water.

[0008] The ecological benefits of wastewater treatment depend not only on the concentration of pollutants in the water before and after treatment, but also on the environmental pollution caused directly or indirectly during the treatment process. For example, the pumps, mixing devices, aeration devices, and other operating devices used to drive the wastewater treatment system all consume electricity, and the power generation process emits carbon dioxide, sulfur dioxide, and nitrogen oxides. Commonly used wastewater treatment agents such as ferrous sulfate and aluminum chloride emit acidic wastewater containing heavy metal ions during their production. In addition, the transportation of these agents also pollutes the environment. Therefore, the ecological benefits of wastewater treatment depend not only on the water quality before and after treatment, but also on the electricity and agent consumption during the treatment process.

[0009] Further optimization involves two water quality sensors monitoring multiple pollutants of the same type, with different signal markers for each pollutant, each corresponding to a unique serial number. In step S2, the data center performs the same preprocessing procedure for the water quality monitoring data from the influent and drainage modules, specifically including the following steps: S2.1. Determine the normal value range of each pollutant before treatment based on the composition characteristics of the effluent to be treated, and determine the normal value range of each pollutant after treatment based on the treatment mechanism of the effluent treatment system.

[0010] S2.2. Each sampling stage within the same monitoring period corresponds to a unique sequence number, and all sampling stages include multiple consecutive time points, with water quality sensors performing water quality detection at all times; after each sampling stage is completed, the average concentration of each pollutant is calculated. E i,t , i The serial number represents the type of pollutant. t This is the sampling stage number. E i,t From the sampling stage t Pollutants at all times i The concentration values ​​are obtained by arithmetically averaging.

[0011] S2.3. E i,t First, with the corresponding pollutants i Compared to the normal value range, if E i,t If the value is within the normal range, then E i,t As a sampling stage t pollutants i If the water quality indicators are not within the normal range, then during the sampling stage... t pollutants i The water quality indicators are yet to be determined.

[0012] S2.4. After each sampling stage is completed, a state vector for each pollutant in that sampling stage is established. S i,t , S i,t Number of elements and sampling stage t The number of time points within the sampling phase is equal. t Pollutants at all times i Concentration values ​​and S i,t All elements in the text correspond one-to-one.

[0013] S2.5. After all sampling stages in a certain monitoring cycle are completed, the state vector of the corresponding water quality index to be determined is denoted as the target vector, and a sample set for each pollutant is established. D i Apart from the target vector, it belongs to pollutants. i All state vectors are categorized into D i In, and set a proximity threshold. K ,K It is a positive integer; it will be a vector belonging to the same pollutant as a target vector. D i As the sample set corresponding to the target vector, the distance between the target vector and each state vector in the corresponding sample set is calculated, and all state vectors are sorted in ascending order of proximity. Then, the first few state vectors in the resulting sequence are selected. K The sample vector is obtained by averaging the state vectors. Then, the arithmetic mean of all elements in the sample vector is calculated. The resulting arithmetic mean is used as the water quality index value corresponding to the target vector.

[0014] Considering that the flow of tailwater can affect the distribution of pollutant concentrations in the water, there may be areas in the flow field where pollutant concentrations are much higher or lower than the average concentration. Furthermore, tailwater flow is typically turbulent, making it impossible to predict the flow field distribution. To avoid excessive deviation between the monitoring data obtained from water quality sensors and the actual water quality, this invention designs a water quality monitoring data preprocessing workflow. The preprocessing of water quality monitoring data is based on the K-nearest neighbor algorithm. In each sampling stage, the concentration characteristics of each pollutant are represented as a state vector. For state vectors with abnormal monitoring data, the nearest neighbor is selected. K The flow field and concentration characteristics represented by each state vector are most similar to that of the given state vector. (Through the nearest...) K Each state vector determines the water quality index corresponding to the abnormal state vector, which can reflect the true concentration of pollutants as accurately as possible.

[0015] Further optimization involves equipping the processing module with a gas flow sensor and a gas detector. The gas detector simultaneously monitors the concentrations of multiple gas components, each with a unique serial number. Step S2, the preprocessing of the emission gas monitoring data by the data center, specifically includes the following steps: S2.6. After each sampling phase is completed, the emission amount of each gas at each time point in that sampling phase is calculated separately, using the following formula: (1) in, j The serial number represents the type of gas. τ For time Δ τ The interval between two adjacent moments is . C j,t,τ Sampling phase t middle τ Time gas j concentration, V t,τ Sampling phase t middle τ The volume of gas emitted at any given time, Q j,t,τ Sampling phase t middle τ Time gas j The amount of emissions.

[0016] S2.7. Calculation Sampling Stage t Middle gas j Average emissions at all times Q average j,t and standard deviation s j,t A fraction threshold is set, and then the gas is calculated using the following formula. j All moments Q j,t,τ The corresponding Z-scores are: (2) in, z j,t,τ for Q j,t,τ The corresponding Z-score.

[0017] S2.8. According to Q average j,t and s j,t Determine the sampling phase t Middle gas j upper limit Q max j,t If a certain Q j,t,τ = Q max j,t Then the Q j,t,τ The corresponding Z-score is the score threshold; all z j,t,τ Compare each score with the threshold score; if... z j,t,τ If it is not greater than the score threshold, then z j,t,τ corresponding Q j,t,τ If the value remains unchanged, z j,t,τ If the score is greater than the threshold, then z j,t,τ corresponding Q j,t,τ Replace the numerical values ​​with Q max j,t .

[0018] S2.9. Calculation Sampling Stage t Emissions of all types of gases Qtotal j,t , Q total j,t Sampling phase t It belongs to the gas j All moments Q j,t,τ sum.

[0019] The gases emitted during the treatment process typically flow out in turbulent flow, so the concentration monitoring data for different types of gases may deviate significantly from the actual situation. Unlike effluent, which is primarily water, the concentration of a certain pollutant in the water is largely independent of the concentrations of other pollutants. The concentration of that pollutant at a certain point in the water may be much higher than the average concentration. In contrast, the main components of the gases emitted during the treatment process are the various gases to be monitored. The local concentration of a certain gas may be slightly higher than the average, but it will not be significantly higher than the average. Therefore, the fluctuation range of gas concentration is relatively small. Only Z-score preprocessing is needed, and a threshold is set to truncate data with excessively high concentrations, which can significantly reduce computational complexity.

[0020] Further optimization involves the following steps in step S3: Establishing the pollution product analysis model. S3.1. Calculate the direct emission of each gas per unit volume of treated effluent during the entire monitoring period using the following formula: (3) in, Q j To treat a unit volume of tailwater gas j Direct emissions, V This refers to the total amount of effluent treated during the entire monitoring period. N This refers to the number of sampling phases within the monitoring period.

[0021] S3.2. Calculate the average dosage of each agent per unit volume of treated effluent during the entire monitoring period using the following formula, where each agent has a unique serial number: (4) in, k For drug types, M k Chemicals for treating a unit volume of effluent k Average dosage M k,t Sampling phase t Traditional Chinese medicine k Dosage.

[0022] All the multiple operating devices are electrically powered, and each device has a unique serial number. The electrical energy required to treat a unit volume of wastewater is calculated using the following formula: (5) in, l For the serial number of the operating device, W The electrical energy required to treat a unit volume of wastewater. T l,t For operating devices l During the sampling phase t runtime in P l For operating devices l Rated power.

[0023] S3.3. Calculate the actual emission rate of each gas per unit volume of treated effluent using the following formula: (6) in, Q all j To treat a unit volume of tailwater gas j The actual emissions, R The number of types of drugs used. a k,j Quality reagents for production and transportation units k The resulting gas j Emissions W 0 represents the unit of electricity. b j The gas produced during the generation of a unit of electricity during the power generation process j Emissions.

[0024] Since the composition of effluent is usually not constant, changes in effluent composition will cause changes in parameters including power consumption data, chemical dosage data, emission gas monitoring data, and water quality indicators. Therefore, it is difficult to make an effective analysis and assessment of ecological benefits based on monitoring data, power consumption data, and chemical dosage data over a short period of time. Based on monitoring data, power consumption data, and chemical dosage data over a longer period of time, the average gas emission data per unit volume of treated effluent is conducive to making the ecological benefit assessment more universal and realistic.

[0025] Further optimization involves establishing an ecological benefit model in step S4, specifically including the following steps: S4.1. Establish a global warming potential model, which is described by the following formula: (7) in, GWP The global warming potentialU To treat the types and quantities of gases emitted from the effluent, CF GWP j gas j The warming characteristic factors.

[0026] S4.2. Establish a eutrophication model for the water body, which is described by the following formula: (8) in, EP Eutrophic value of water bodies E out i,t The sampling stage obtained after preprocessing t Pollutants in drainage modules i Water quality indicators X For the types and quantities of pollutants, CF EP i pollutants i . characteristic factors.

[0027] S4.3. Establish a comprehensive acidification impact model, which is described by the following formula: (9) in, AP To determine the overall acidity value, CF AP j gas j The acidification characteristic factor.

[0028] S4.4. Determining the Global Warming Potential Baseline GWP 0. Eutrophication Standard for Water Bodies EP 0 and comprehensive acidity value benchmark AP 0, and calculate the normalized index. S GWP , S EP , S AP , , , .

[0029] S4.5. Establish ecological benefit measurement standards, which include multiple levels, each with a corresponding numerical range; establish a calculation formula for ecological benefit indicators, the formula of which is as follows: (10) in, SEI As an indicator of ecological benefits, W GWP, W EP , W AP Normalized index S GWP , S EP , S AP The corresponding normalized weights, W GWP + W EP + W AP = 1; the result SEI Compare with all numerical ranges in the ecological benefit measurement standards to find SEI The numerical range in which the value falls is used as the ecological benefit level for the monitoring period being analyzed.

[0030] CF GWP j , CF EP i , CF AP i These are all ReCiPe indicators from life cycle assessment, used to measure the impact of different substances on a certain ecological phenomenon. CF GWP j For example, the greenhouse effect caused by CH4 is 28 times that of an equal amount of CO2, therefore the greenhouse effect corresponding to CH4 is... CF GWP j The value corresponding to CO2 CF GWP j 28 times the numerical value. Since different gases cause different acidification processes—for example, carbon dioxide causes ocean acidification and ammonia causes atmospheric acidification—all gases capable of causing acidification are assessed for their environmental impact using a comprehensive acidification impact model to facilitate ecological evaluation.

[0031] The beneficial effects of the method of the present invention are as follows: 1. The wastewater treatment ecological benefit analysis method proposed in this invention is based on life cycle assessment, which can comprehensively consider all pollution caused by the wastewater treatment process by combining electricity consumption data and chemical dosing data, so that the assessment results are comprehensive and accurate. 2. This invention includes preprocessing of water quality monitoring data and gas monitoring data to avoid the impact of uneven distribution of pollutant concentration and gas concentration on the accuracy of the assessment results; 3. The ecological benefit model measures the level of ecological benefit through ecological benefit indicators, making the assessment results more intuitive. Attached Figure Description

[0032] Figure 1 A schematic diagram of the overall process of the tailwater treatment ecological benefit analysis method of this invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below through specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. 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.

[0034] Example 1: A method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment, operating on a wastewater treatment system. The wastewater treated in this example is from large-scale aquaculture. The wastewater treatment system includes an operating device for driving the system's operation, comprising a water pump and an aeration device. The wastewater treatment system also includes a dosing device for dispensing wastewater treatment chemicals. Specifically, the method includes the following steps: S1. The wastewater treatment system includes an inlet module, a treatment module, and a drainage module. The inlet module includes an inlet pipe, and the drainage module includes an outlet pipe. The treatment module uses a combination of "ecological floating bed + artificial wetland" technology to treat the wastewater. The ecological floating bed is a grid floating on the water surface and is located in a closed space. This space is connected to the outside world only through the inlet pipe, the outlet pipe, and the vent pipe. A monitoring system was established, with water quality sensors installed on both the inlet and outlet pipes. The water quality sensors are HQd multi-functional water quality analyzers from HACH Corporation (USA), equipped with digital probes for monitoring the concentrations of various pollutants, including dissolved oxygen (LDO), pH electrode, COD, ammonia nitrogen, and nitrate nitrogen. A gas flow sensor and a gas detector were installed on the exhaust pipe. The gas flow sensor is a SITRANSFUS060 thermal mass flow meter from SIEMENS (Germany), and the gas detector is an HG-1000 multi-component gas analyzer from Laoying Optoelectronics (China). The monitoring system includes all the above sensors and a data center. All sensors are connected to the data center, and all sensors transmit monitoring data to the data center in real time.

[0035] S2. Select the types of pollutants and gases to be monitored in the water. In this embodiment, the pollutants monitored are organic matter, nitrogen-containing compounds, and phosphorus-containing compounds, and the gases monitored are CO2, CH4, and NH3. Set the monitoring cycle, which is divided into multiple sampling stages of equal duration. In this embodiment, the monitoring cycle is one day, and each sampling stage lasts half an hour. The agent dispensed by the dosing device is EM-100 microbial agent. The power consumption data of the operating device and the amount of agent dispensed by the dosing device are recorded. The data center stores the received data and performs preprocessing. Two water quality sensors monitor multiple pollutants of the same type, and each pollutant corresponds to a unique serial number. The data center performs the same preprocessing process for the water quality monitoring data of the inlet and outlet modules, specifically including the following steps: S2.1. Based on the compositional characteristics of aquaculture wastewater, determine the normal value range for each pollutant before treatment, and based on the treatment mechanism of the wastewater treatment system, determine the normal value range for each pollutant after treatment. Taking the wastewater treatment situation on a certain day as an example, the normal value ranges for organic matter, nitrogen compounds, and phosphorus compounds before treatment are 320-450 mg / L, 35-55 mg / L, and 6-10 mg / L, respectively, and the normal value ranges for organic matter, nitrogen compounds, and phosphorus compounds before treatment are 45-65 mg / L, 8-12 mg / L, and 0.3-0.6 mg / L, respectively.

[0036] S2.2. Each sampling stage within the same monitoring period corresponds to a unique sequence number, and all sampling stages include multiple consecutive time points, with water quality sensors performing water quality detection at all times; after each sampling stage is completed, the average concentration of each pollutant is calculated. E i,t , i The serial number represents the type of pollutant. t This is the sampling stage number. E i,t From the sampling stage t Pollutants at all times i The concentration values ​​are obtained by arithmetically averaging.

[0037] S2.3. E i,t First, with the corresponding pollutants i Compared to the normal value range, if E i,t If the value is within the normal range, then E i,t As a sampling stage t pollutants i If the water quality indicators are not within the normal range, then during the sampling stage... t pollutants iThe water quality indicators are yet to be determined; in this embodiment, the corresponding serial numbers for organic matter, nitrogen-containing compounds, and phosphorus-containing compounds are 1, 2, and 3, respectively, and the average values ​​of pollutants in the influent module are respectively... E 1, 1 = 380、 E 1, 2 = 365、 E 1, 3 = 390 … E 1, 48 = 372, E 2, 1 = 42、 E 2, 2 = 45、 E 2, 3 = 40 … E 2, 48 = 43, E 3, 1 = 8.2、 E 3, 2 = 7.8、 E 3, 3 = 8.5 … E 3, 48 = 8.0, the average pollutant values ​​of the drainage modules are respectively, E 1, 1 = 52、 E 1, 2 = 55、 E 1, 3 = 48 … E 1, 48 = 50, E 2, 1 =10.5、 E 2, 2 = 9.8、 E 2, 3 = 11.2 … E 2, 48 = 10.0, E 3, 1 = 0.45、 E 3, 2 = 0.52、 E 3, 3 = 0.48… E 3, 48 = 0.46, all values ​​above are in mg / L, including the inlet module E 3, 12 , E 3, 28 Drainage module E 3, 15 , E 3, 36If the four values ​​are not within the normal range, the water quality indicators for phosphorus compounds in sampling stages 12 and 28 of the influent module and sampling stages 15 and 36 of the drainage module will be determined, and the average values ​​of other pollutants will be used as water quality indicators.

[0038] S2.4. After each sampling stage is completed, a state vector for each pollutant in that sampling stage is established. S i,t , S i,t Number of elements and sampling stage t The number of time points within the sampling phase is equal. t Pollutants at all times i Concentration values ​​and S i,t All elements in the text correspond one-to-one.

[0039] S2.5. After all sampling stages in a certain monitoring cycle are completed, the state vector of the corresponding water quality index to be determined is denoted as the target vector, and a sample set for each pollutant is established. D i Apart from the target vector, it belongs to pollutants. i All state vectors are categorized into D i In, and set a proximity threshold. K In this embodiment K = 4; This will include vectors belonging to the same pollutant type as a target vector. D i As the sample set corresponding to the target vector, calculate the distance between the target vector and each state vector in the corresponding sample set, and sort all state vectors in order of proximity. Then, select the top [state vectors] from the resulting sequence. K The sample vector is obtained by averaging the state vectors. Then, the arithmetic mean of all elements in the sample vector is calculated. The resulting arithmetic mean is used as the water quality index value corresponding to the target vector.

[0040] The gas detector simultaneously monitors the concentration of multiple gases, each with a unique serial number. In this embodiment, the serial numbers for CO2, CH4, and NH3 are 1, 2, and 3, respectively. The preprocessing process of the emission gas monitoring data in the data center specifically includes the following steps: S2.6. After each sampling phase is completed, the emission of each gas at each moment in the sampling phase is calculated using formula (1).

[0041] S2.7. Calculation Sampling Stage t Middle gas j Average emissions at all times Q average j,t and standard deviations j,t And set a fraction threshold, and then calculate the gas using formula (2). j All moments Q j,t,τ The corresponding Z-scores.

[0042] S2.8. According to Q average j,t and s j,t Determine the sampling phase t Middle gas j upper limit Q max j,t If a certain Q j,t,τ = Q max j,t Then the Q j,t,τ The corresponding Z-score is the score threshold; all z j,t,τ Compare each score with the threshold score; if... z j,t,τ If it is not greater than the score threshold, then z j,t,τ corresponding Q j,t,τ If the value remains unchanged, z j,t,τ If the score is greater than the threshold, then z j,t,τ corresponding Q j,t,τ Replace the numerical values ​​with Q max j,t .

[0043] S2.9. Calculation Sampling Stage t Emissions of all types of gases Q total j,t , Q total j,t Sampling phase t It belongs to the gas j All moments Q j,t,τ Sum; in this embodiment Q total 1, 1 = 135、 Q total 1, 2 = 142、 Q total 1, 3=138 … Q total 1, 48 = 136, Q total 2, 1 = 4.2、 Q total 2, 2 = 3.8、 Q total 2, 3 = 4.5 … Q total 2, 48 =4.0, Q total 3, 1 = 2.5、 Q total 3, 2 = 2.3、 Q total 3, 3 = 2.7 … Q total 3, 48 = 2.4, all values ​​above are in kg.

[0044] S3. Establish a pollution product analysis model based on the LCA method. This model is used to determine the total pollution amount for a given monitoring period based on electricity consumption data, reagent dosage data, and emission gas monitoring data. The process of establishing the pollution product analysis model specifically includes the following steps: S3.1. Calculate the treatment capacity of 1 m throughout the entire monitoring cycle using formula (3). 3 The direct emission amount of each gas in the effluent, in this embodiment N = 48; In this embodiment, the daily treatment capacity of the wastewater treatment system is 30,000 m³. 3 This figure is derived from the average of the total amount of wastewater treated in the most recent month.

[0045] S3.2. Calculate the treatment capacity of 1 m throughout the entire monitoring cycle using formula (4). 3 The average dosage of each agent in the effluent is specified, and each agent has a unique serial number. In this example, the daily dosage of EM-100 microbial agent is 0.9 tons. M 1 = 3 × 10 -5 kg / m³; the multiple water pumps and aeration equipment are all electrically driven, and each operating device has a unique serial number. The processing capacity of 1 m³ is calculated using formula (5). 3 The electrical energy required for wastewater treatment in this embodiment is as follows: the water pump has a rated power of 25 kW and operates for 20 hours per day; the aeration equipment has a rated total power of 15 kW and operates for 18 hours per day. W= 0.026 kWh / m³.

[0046] S3.3. Calculate and process 1 m using formula (6) 3 The actual emissions of each gas in the effluent are as follows: In this embodiment, producing 1 kg of EM-100 microbial agent emits 0.8 kg of CO2, 0.05 kg of CH4, and 0.03 kg of NH3; generating 1 kWh of electricity emits 0.58 kg of CO2. Q all 1 = 0.21 kg / m³ Q all 2 = 0.003 kg / m³ Q all 3 = 0.002 kg / m³.

[0047] S4. Establish an ecological benefit model, which analyzes the ecological benefits of a monitoring period based on water quality index data before and after treatment and total pollution levels. The water quality indexes are used to measure the concentration of pollutants in the water. The process of establishing the ecological benefit model specifically includes the following steps: S4.1. Establish a global warming potential model, which is described by formula (7). In this embodiment, the greenhouse effect of CO2 is used as the benchmark. GWP = 0.294 kg CO2-eq / m³.

[0048] S4.2. Establish a water eutrophication model, which is described by formula (8). In this embodiment, the eutrophication potential of phosphate is used as the benchmark. EP = 0.027 kg PO4³⁻-eq / m³.

[0049] S4.3. Establish a comprehensive acidification impact model, which is described by formula (9). In this embodiment, the acidification impact of SO2 is used as the benchmark. AP = 0.0038 kg SO2-eq / m³.

[0050] S4.4. Determining the Global Warming Potential Baseline GWP 0. Eutrophication Standard for Water Bodies EP 0 and comprehensive acidity value benchmark AP 0. In this embodiment, the ecological impact of direct discharge of wastewater is calculated using relevant models in the IPCC database, thereby determining... GWP 0、 EP 0、 AP 0 value, GWP 0 = 0.85 kg CO2-eq / m³ EP 0 = 0.09 kg PO4³⁻-eq / m³, AP 0 = 0.012 kg SO2-eq / m³; and calculate the normalized index. S GWP , S EP , S AP , , , In this embodiment S GWP = 0.65, S EP = 0.7, S AP = 0.68.

[0051] S4.5. Establish ecological benefit measurement standards, which include multiple levels, each with a corresponding numerical range. In this embodiment, the ecological benefit measurement standards are listed in Table 1. Establish ecological benefit index calculation formulas, as shown in formula (10). In this embodiment... W GWP = 0.3, W EP = 0.5, W AP = 0.2, the result SEI = 0.681; the result SEI Compare with all numerical ranges in the ecological benefit measurement standards to find SEI The numerical range in which the value falls is used, and the corresponding level of the numerical range is taken as the ecological benefit level of the monitoring period being analyzed. In this embodiment, the ecological benefit level is good.

[0052] Table 1. Ecological Benefit Levels and Corresponding Ecological Benefit Indicator Value Ranges Ecological benefit indicators (range) Ecological benefit level 0.8~1.0 excellent 0.5~0.79 good 0.2~0.49 generally 0~0.19 Poor <0 negative .

Claims

1. A method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment, operating based on a wastewater treatment system, said wastewater treatment system comprising multiple operating devices for driving system operation, and a dosing device for dispensing wastewater treatment agents; characterized in that, Specifically, the following steps are included: S1. Establish a monitoring system. Water quality sensors are installed in both the inlet and outlet modules of the wastewater treatment system. Sensors are installed in the treatment modules to monitor the volume, composition, and concentration of each component of the emitted gas. The monitoring system includes all the above sensors and a data center. All sensors are connected to the data center and transmit the monitoring data to the data center in real time. S2. Select the types of pollutants and gases to be monitored in the water, and set the monitoring cycle, which is divided into multiple sampling stages of equal duration; the dosing device can dispense various agents, and the power consumption data of the operating device, as well as the types and amounts of agents dispensed by the dosing device, are recorded. The data center stores the received data and performs preprocessing. S3. Establish a pollution product analysis model based on the LCA method. The pollution product analysis model is used to determine the total amount of pollution in a monitoring period based on the electricity consumption data, reagent dosing data and emission gas monitoring data in a certain monitoring period. S4. Establish an ecological benefit model, which analyzes the ecological benefits of a monitoring period based on water quality index data before and after treatment and total pollution within a certain monitoring period. The water quality index is used to measure the concentration of pollutants in the water.

2. The method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment as described in claim 1, characterized in that, Two water quality sensors monitor multiple pollutants of the same type, and the two sensors have different signal markers, with each pollutant corresponding to a unique serial number; the preprocessing process of the water quality monitoring data from the influent module and the effluent module in step S2 is the same, specifically including the following steps: S2.

1. Determine the normal value range of each pollutant before treatment based on the composition characteristics of the effluent to be treated, and determine the normal value range of each pollutant after treatment based on the treatment mechanism of the effluent treatment system. S2.

2. Each sampling stage within the same monitoring period corresponds to a unique sequence number, and all sampling stages include multiple consecutive time points, with water quality sensors performing water quality detection at all times; after each sampling stage is completed, the average concentration of each pollutant is calculated. E i,t , i The serial number represents the type of pollutant. t This is the sampling stage number. E i,t From the sampling stage t Pollutants at all times i The concentration values ​​are obtained by arithmetically averaging them. S2.

3. E i,t First, with the corresponding pollutants i Compared to the normal value range, if E i,t If the value is within the normal range, then E i,t As a sampling stage t pollutants i If the water quality indicators are not within the normal range, then during the sampling stage... t pollutants i Water quality indicators are yet to be determined; S2.

4. After each sampling stage is completed, a state vector for each pollutant in that sampling stage is established. S i,t , S i,t Number of elements and sampling stage t The number of time points within the sampling phase is equal. t Pollutants at all times i Concentration values ​​and S i,t All elements in the text correspond one-to-one; S2.

5. After all sampling stages in a certain monitoring cycle are completed, the state vector of the corresponding water quality index to be determined is denoted as the target vector, and a sample set for each pollutant is established. D i Apart from the target vector, it belongs to pollutants. i All state vectors are categorized into D i In, and set a proximity threshold. K , K It is a positive integer; it will be a vector belonging to the same pollutant as a target vector. D i As the sample set corresponding to the target vector, the distance between the target vector and each state vector in the corresponding sample set is calculated, and all state vectors are sorted in ascending order of proximity. Then, the first few state vectors in the resulting sequence are selected. K The sample vector is obtained by averaging the state vectors. Then, the arithmetic mean of all elements in the sample vector is calculated. The resulting arithmetic mean is used as the water quality index value corresponding to the target vector.

3. The method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment as described in claim 2, characterized in that, The processing module is equipped with a gas flow sensor and a gas detector. The gas detector simultaneously monitors the concentration of multiple gas components, each with a unique serial number. The preprocessing of the emission gas monitoring data in step S2 specifically includes the following steps: S2.

6. After each sampling phase is completed, the emission amount of each gas at each time point in that sampling phase is calculated separately, using the following formula: (1) in, j The serial number represents the type of gas. τ For time Δ τ The interval between two adjacent moments is . C j,t,τ Sampling phase t middle τ Time gas j concentration, V t,τ Sampling phase t middle τ The volume of gas emitted at any given time, Q j,t,τ Sampling phase t middle τ Time gas j Emissions; S2.

7. Calculation of Sampling Stage t Middle gas j Average emissions at all times Q average j,t and standard deviation s j,t A fraction threshold is set, and then the gas is calculated using the following formula. j All moments Q j,t,τ The corresponding Z-scores are: (2) in, z j,t,τ for Q j,t,τ The corresponding Z-score; S2.

8. According to Q average j,t and s j,t Determine the sampling phase t Middle gas j upper limit Q max j,t If a certain Q j,t,τ = Q max j,t Then the Q j,t,τ The corresponding Z-score is the score threshold; all z j,t,τ Compare each score with the threshold score; if... z j,t,τ If it is not greater than the score threshold, then z j,t,τ corresponding Q j,t,τ If the value remains unchanged, z j,t,τ If the score is greater than the threshold, then z j,t,τ corresponding Q j,t,τ Replace the numerical values ​​with Q max j,t ; S2.

9. Calculation Sampling Stage t Emissions of all types of gases Q total j,t , Q total j,t Sampling phase t It belongs to the gas j All moments Q j,t,τ sum.

4. The method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment as described in claim 3, characterized in that, Step S3, which involves establishing an analytical model for pollutants, specifically includes the following steps: S3.

1. Calculate the direct emission of each gas per unit volume of treated effluent during the entire monitoring period using the following formula: (3) in, Q j To treat a unit volume of tailwater gas j Direct emissions, V This refers to the total amount of effluent treated during the entire monitoring period. N This refers to the number of sampling phases within the monitoring period; S3.

2. Calculate the average dosage of each agent per unit volume of treated effluent during the entire monitoring period using the following formula, where each agent has a unique serial number: (4) in, k For drug types, M k Chemicals for treating a unit volume of effluent k Average dosage M k,t Sampling phase t Traditional Chinese medicine k Dosage; All the multiple operating devices are electrically powered, and each device has a unique serial number. The electrical energy required to treat a unit volume of wastewater is calculated using the following formula: (5) in, l For the serial number of the operating device, W The electrical energy required to treat a unit volume of wastewater. T l,t For operating devices l During the sampling phase t runtime in P l For operating devices l Rated power. 5.S3.

3. Calculate the actual emission rate of each gas per unit volume of treated effluent using the following formula: (6) in, Q all j To treat a unit volume of tailwater gas j The actual emissions, R The number of types of drugs used. a k,j Quality reagents for production and transportation units k The resulting gas j Emissions W 0 represents the unit of electricity. b j The gas produced during the generation of a unit of electricity during the power generation process j Emissions.

6. The method for analyzing the ecological benefits of wastewater treatment based on life cycle assessment as described in claim 4, characterized in that, The process of establishing the ecological benefit model in step S4 specifically includes the following steps: S4.

1. Establish a global warming potential model, which is described by the following formula: (7) in, GWP The global warming potential U To treat the types and quantities of gases emitted from the effluent, CF GWP j gas j Warming characteristic factors; S4.

2. Establish a eutrophication model for the water body, which is described by the following formula: (8) in, EP Eutrophic value of water bodies E out i,t The sampling stage obtained after preprocessing t Pollutants in drainage modules i Water quality indicators X For the types and quantities of pollutants, CF EP i pollutants i eigenfactors; S4.

3. Establish a comprehensive acidification impact model, which is described by the following formula: (9) in, AP To determine the overall acidity value, CF AP j gas j Acidification characteristic factors; S4.

4. Determining the Global Warming Potential Baseline GWP 0. Eutrophication Standard for Water Bodies EP 0 and comprehensive acidity value benchmark AP 0, and calculate the normalized index. S GWP , S EP , S AP , , , ; S4.

5. Establish ecological benefit measurement standards, which include multiple levels, each with a corresponding numerical range; establish a calculation formula for ecological benefit indicators, the formula of which is as follows: (10) in, SEI As an indicator of ecological benefits, W GWP , W EP , W AP Normalized index S GWP , S EP , S AP The corresponding normalized weights, W GWP + W EP + W AP = 1; the result SEI Compare with all numerical ranges in the ecological benefit measurement standards to find SEI The numerical range in which the value falls is used as the ecological benefit level for the monitoring period being analyzed.

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