Treatment method of kitchen garbage leachate after garbage classification and recovery

Abstract

The invention relates to the technical field of sewage treatment, and discloses a treatment method of kitchen garbage leachate after garbage classification and recovery. The method comprises the following steps: pretreating leachate to obtain homogenized leachate, and collecting basic physicochemical index data of the homogenized leachate; calculating a target pollutant removal rate according to the data, and further selecting a biodegradation process type and a microbial inoculation formula; on the basis of the data, operating parameters of the bioreactor are set, the system is started for biodegradation, and primary effluent is generated; the method comprises the following steps: dynamically optimizing operation parameters of a bioreactor by detecting monitoring data in a primary effluent process, and continuously degrading by applying the optimized parameters to generate final effluent; and carrying out advanced treatment on the final effluent and verifying the discharge compliance. According to the method, dynamic selection of a treatment process and self-adaptive optimization of operation parameters are realized through data driving, the problems of poor adaptability and unstable operation of a traditional method are solved, and the treatment efficiency of the leachate and the system stability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment, in particular to a treatment method for kitchen waste leachate after garbage classification and recycling. BACKGROUND

[0002] Kitchen waste leachate is difficult to handle in the garbage disposal process due to its complex composition, high pollutant concentration and great water quality fluctuation. The current mainstream biological treatment technology usually adopts a preset fixed process route, such as the combination process of anaerobic digestion and aerobic activated sludge method. This preset mode determines the core process flow at the design stage, and cannot cope with the drastic changes in water quality every day or even every hour. When the water inflow load, carbon-nitrogen ratio or toxic substance concentration changes suddenly, the fixed process combination lacks flexibility and cannot switch to a more efficient processing mode, resulting in weak system impact resistance, unstable treatment effect, and even system collapse.

[0003] At the process operation level, the existing method mainly relies on experience to set initial parameters, and adjusts laggingly after detecting the effluent indicators regularly. The addition of microbial agents also often lacks specificity, and general flora is often used. This static and passive management method cannot achieve fine control of the biological degradation process. Because the microbial community structure and hydraulic conditions in the biological reactor cannot quickly respond to real-time water inflow characteristics and intermediate products, the system operates in a non-optimal state for a long time, the removal potential of specific pollutants is not fully utilized, the treatment efficiency has a ceiling, and the energy and material consumption is high. A treatment method is needed that can intelligently respond to changes in water quality, dynamically adjust process strategies and operating parameters. SUMMARY

[0004] The purpose of the present application is to provide a treatment method for kitchen waste leachate after garbage classification and recycling to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides a treatment method for kitchen waste leachate after garbage classification and recycling, which comprises:

[0006] Pretreatment operation is performed on the kitchen waste leachate to obtain homogenized leachate;

[0007] The basic physicochemical index data of the homogenized leachate is collected;

[0008] According to the basic physicochemical index data, target pollutant removal rate data is calculated;

[0009] According to the target pollutant removal rate data, biological degradation process type data is selected;

[0010] In combination with the selected biological degradation process type data, microbial inoculation formula data is determined;

[0011] setting bioreactor operation parameter data based on the microbial inoculum recipe data and the target contaminant removal rate data;

[0012] starting a treatment system using the bioreactor operation parameter data to biodegrade the homogenized leachate to produce a primary effluent;

[0013] detecting in-process monitoring data of the primary effluent;

[0014] optimizing the bioreactor operation parameter data according to the in-process monitoring data;

[0015] continuing the degradation process using the optimized bioreactor operation parameter data to produce a final effluent;

[0016] performing advanced treatment on the final effluent and verifying discharge compliance.

[0017] Preferably, the kitchen waste leachate is subjected to a pretreatment operation, including:

[0018] filtering the raw leachate through a grid to remove large particulate impurities, adjusting the temperature of the filtered leachate to a preset range, adding a coagulant for flocculation and sedimentation, separating suspended solids, and collecting the supernatant as the homogenized leachate.

[0019] Preferably, the basic physicochemical index data of the homogenized leachate is collected, including:

[0020] measuring the chemical oxygen demand concentration, biological oxygen demand concentration, total nitrogen concentration, and total phosphorus concentration of the leachate using online sensors;

[0021] laboratory analysis of the heavy metal content and pathogenic microorganism quantity of the leachate, integrating the measurement and analysis results to form the basic physicochemical index data;

[0022] The laboratory analysis of the heavy metal content and pathogenic microorganism quantity of the leachate includes the following steps:

[0023] Collecting a stratified representative sample of the homogenized leachate, centrifuging the sample to remove suspended solids, and taking the supernatant as the analysis sample;

[0024] detecting the concentrations of lead, cadmium, mercury, and arsenic heavy metal elements in the sample using atomic absorption spectrometry, detecting the concentrations of trace heavy metal elements chromium, nickel, and copper using inductively coupled plasma mass spectrometry, and summarizing the element concentration values to form the heavy metal content data;

[0025] detecting the number of coliform bacteria in the sample using the multi-tube fermentation method, detecting the gene copy number of Salmonella and Shigella pathogenic microorganisms in the sample using the fluorescent quantitative polymerase chain reaction technology, and summarizing the microorganism quantity to form the pathogenic microorganism quantity data.

[0026] Preferably, according to the basic physicochemical index data, the target pollutant removal rate data is calculated, including:

[0027] A correlation model of pollutant load and treatment efficiency is established, and the key parameters in the basic physicochemical index data are input into the correlation model, and the target pollutant removal rate data, including chemical oxygen demand removal rate and ammonia nitrogen removal rate, is output;

[0028] The correlation model of pollutant load and treatment efficiency includes the following steps:

[0029] The basic physicochemical index data of historical kitchen garbage leachate treatment cases, the target pollutant removal rate data of the corresponding treatment process and the actual treatment efficiency data are collected;

[0030] The key pollutant load parameters affecting the treatment efficiency are screened, including chemical oxygen demand load, ammonia nitrogen load and total phosphorus load;

[0031] Taking the key pollutant load parameters as independent variables and the actual treatment efficiency data as dependent variables, a multivariate linear regression method is used to fit the quantitative relationship between variables to build a correlation model of pollutant load and treatment efficiency.

[0032] Preferably, according to the target pollutant removal rate data, the biological degradation process type data is selected, including:

[0033] The historical performance data of anaerobic digestion, aerobic activated sludge method and membrane bioreactor are compared, and the process most matched with the target pollutant removal rate data is selected as the biological degradation process type data, and the operation requirements and limitation conditions of the selected process are recorded.

[0034] Preferably, in combination with the selected biological degradation process type data, the microbial inoculation formula data is determined, including:

[0035] According to the biological degradation process type data, the dominant strain combination is selected, the strain ratio is adjusted to adapt to the characteristics of the target pollutant, the inoculation amount and activation conditions are determined, and the microbial inoculation formula data is formed, specifically including:

[0036] When the biological degradation process type data is anaerobic digestion, methanogenic bacteria and acidification bacteria are selected as the dominant strain combination; when the biological degradation process type data is aerobic activated sludge method, nitrifying bacteria and denitrifying bacteria are selected as the dominant strain combination;

[0037] The carbon-nitrogen ratio in the basic physicochemical index data is analyzed, and when the carbon-nitrogen ratio is higher than the threshold value, the proportion of denitrifying bacteria is increased, and when the carbon-nitrogen ratio is lower than the threshold value, the proportion of nitrifying bacteria is increased;

[0038] The microbial inoculation amount is calculated according to the target value of the chemical oxygen demand removal rate in the target pollutant removal rate data, and the inoculation amount is the product of the effective volume of the reactor and the inoculation concentration per unit volume;

[0039] The activation condition is set as constant temperature culture in the nutrient solution for a specified time until the microbial activity reaches a preset threshold, and the construction of the microbial inoculation formula data is completed.

[0040] Preferably, based on the microbial inoculation formula data and the target pollutant removal rate data, the biological reactor operation parameter data is set, including:

[0041] The hydraulic retention time and sludge age parameters are calculated, the dissolved oxygen control level and the pH adjustment frequency are set, the nutrient salt dosing scheme is determined in combination with the microbial activity requirement, and the biological reactor operation parameter data is generated by comprehensively considering the parameters.

[0042] Preferably, the treatment system is started using the biological reactor operation parameter data, and the biological degradation of the homogenized leachate is carried out to produce primary effluent, including:

[0043] The microbial inoculant is inoculated into the biological reactor, the influent flow rate and the stirring intensity are adjusted to the set value, the temperature and the gas amount are maintained in the optimization range, and the primary effluent is collected after the system is operated to the steady state, specifically including:

[0044] The microbial inoculant corresponding to the microbial inoculation formula data is uniformly added to the activated sludge in the biological reactor;

[0045] The influent flow rate set value in the biological reactor operation parameter data is read, and the influent flow rate is adjusted to the set value by the frequency conversion pump;

[0046] The stirring intensity is adjusted according to the process type: the intermittent stirring set value is used for anaerobic process, and the continuous aeration stirring set value is used for aerobic process;

[0047] The temperature in the reactor is monitored in real time by the temperature sensor, and the temperature is maintained in the optimization range by the heating / cooling unit;

[0048] The aeration amount is controlled by the gas flow meter, so that the dissolved oxygen concentration is maintained in the optimization range;

[0049] The treatment system is continuously operated until the fluctuation amplitude of the effluent chemical oxygen demand is less than the stable threshold, and it is determined that the system reaches the steady state and the primary effluent is collected.

[0050] Preferably, the process monitoring data of the primary effluent includes:

[0051] The turbidity, conductivity and oxidation-reduction potential of the primary effluent are continuously monitored, the microbial community structure and the metabolic product concentration are detected by timed sampling, and the data are collected as process monitoring data.

[0052] Preferably, the final effluent is subjected to advanced treatment and discharge compliance verification, including:

[0053] Using activated carbon adsorption or advanced oxidation process to remove trace pollutants, measuring the residual pollutant concentration of the final effluent, comparing with the emission standard limit value, and outputting the verification result.

[0054] Compared with the prior art, the beneficial effects of the present application are:

[0055] Based on the real-time collected leachate basic physicochemical index data, the pollutant removal target is dynamically calculated, and the most suitable biochemical degradation process type is selected from multiple alternative schemes. This method changes the rigid mode of traditional fixed process route, and changes the process selection from pre-setting to real-time demand based decision-making process. The system can automatically match the most efficient process according to the water quality characteristics, for example, preferentially starting high-load anaerobic process under high organic load, and preferentially selecting short-cut nitrification or anaerobic ammonia oxidation process under high ammonia nitrogen condition. This dynamic matching ensures that the treatment process is always highly consistent with the characteristics of the influent, improves the pertinence and adaptability of the process, maximizes the overall treatment efficiency of the system, and enhances the ability to cope with water quality fluctuations.

[0056] After determining the process, the microbial inoculation formula is accurately prepared in combination with the removal target, and the reactor initial parameters are set based on this. The key is to form a closed-loop feedback by continuously monitoring the water quality data of the primary effluent, and to perform online adaptive optimization on the operating parameters of the biological reactor. This mechanism realizes real-time fine regulation of the degradation process. The functionality of the microbial flora is directionally strengthened, and the reaction environment parameters such as dissolved oxygen, sludge age, and reflux ratio are dynamically adjusted to the optimal range. This optimization ensures that the biological system is always in a high-efficiency degradation state, improves the pollutant removal load per unit time, strengthens the operation stability of the system, and reduces the risk of operation failure caused by parameter mismatch, thereby reducing energy consumption while ensuring the effluent quality. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 The working principle diagram of the garbage classification and recycling post-kitchen waste leachate treatment method described in the present application;

[0058] Figure 2 The flowchart of pretreatment operation;

[0059] Figure 3 The flowchart of basic physicochemical index data acquisition;

[0060] Figure 4 The multi-dimensional performance comparison and analysis diagram of the biological degradation process;

[0061] Figure 5A comparison chart of key operating parameters of the bioreactor. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0063] Please refer to Figure 1 The present application provides a method for treating kitchen waste leachate after garbage classification and recycling, which comprises: performing pretreatment operation on the collected kitchen waste leachate, including filtration, temperature adjustment and flocculation sedimentation, to obtain homogenized leachate; collecting basic physicochemical index data of the homogenized leachate, covering parameters such as chemical oxygen demand concentration, biological oxygen demand concentration, total nitrogen concentration, total phosphorus concentration, heavy metal content and pathogenic microorganism quantity; based on the basic physicochemical index data, calculating target pollutant removal rate data such as chemical oxygen demand removal rate and ammonia nitrogen removal rate through modeling; according to the target pollutant removal rate data, selecting matched biodegradation process type data from options such as anaerobic digestion, aerobic activated sludge method and membrane bioreactor; combining the selected process type data, determining microbial inoculation formula data, including dominant strain combination, proportion adjustment, inoculum size and activation condition; based on the microbial inoculation formula data and the target pollutant removal rate data, setting bioreactor operating parameter data such as hydraulic retention time, sludge age, dissolved oxygen control level and pH adjustment frequency; starting the treatment system using the bioreactor operating parameter data to perform biodegradation process and generate primary effluent; detecting process monitoring data of the primary effluent, including turbidity, conductivity, oxidation-reduction potential, microbial community structure and metabolic product concentration; dynamically optimizing the bioreactor operating parameter data according to the process monitoring data; continuing degradation using the optimized parameters to produce final effluent; performing advanced treatment on the final effluent, such as activated carbon adsorption or advanced oxidation process, and verifying its discharge compliance by comparing the measured residual pollutant concentration with the standard limit value.

[0064] Example 1: Please refer to Figure 2In a specific implementation, the starting point of the pretreatment operation is to pass the raw kitchen waste leachate through a grid filter device, which has grid bars with a specific aperture for intercepting and removing large-particle impurities, such as food residues, plastic fragments, or other solid debris, present in the leachate. The filtered leachate is introduced into a temperature adjustment unit, in which heat exchange is performed on the leachate through an internal heating coil or cooling coil to adjust and stabilize the temperature of the leachate within a preset range, which is usually determined according to the optimal activity temperature range of the microbial flora in the subsequent biological treatment stage. After completing the temperature adjustment, a pre-prepared coagulant solution is added to the leachate, and the coagulant can be selected from substances such as polyaluminum chloride or ferric sulfate. The addition process is carried out under mechanical stirring, and the stirring speed is controlled to enable the coagulant to mix with the leachate sufficiently but not to destroy the primary flocculation. The flocculation and sedimentation process is carried out in a dedicated sedimentation tank or clarifier, in which the leachate is allowed to stand for a long enough time to enable the alunite flowers and suspended solids formed by coagulation to settle to the bottom of the tank under the action of gravity. The supernatant is collected from the overflow weir at the upper part of the sedimentation tank, and this part of the liquid is defined as homogenized leachate, which has relatively uniform and stable water quality and is suitable for subsequent analysis and treatment processes.

[0065] In a specific implementation, collecting the basic physicochemical index data of the homogenized leachate requires the combination of online monitoring and laboratory analysis. Online sensors are directly installed on the pipeline or buffer tank connected to the outlet of the sedimentation tank, and these sensors continuously measure the chemical oxygen demand concentration, five-day biological oxygen demand concentration, total nitrogen concentration, and total phosphorus concentration of the flowing leachate. The current or optical signals generated by the online sensors are transmitted in real time to the database in the central control room through data transmission cables for recording and storage. Laboratory analysis is carried out for two key indicators, heavy metal content and pathogenic microorganism quantity. The first step of laboratory analysis is to collect representative samples of homogenized leachate. The sampling process must take into account the possible stratification of the leachate, so a stratified sampler is used to obtain samples at different depths and mix them to obtain a representative sample that reflects the overall water quality. The mixed sample is immediately sent to the laboratory, where it is divided into centrifuge tubes and subjected to centrifugal separation using a high-speed centrifuge. The centrifugal force parameters are set according to the density and particle size of the suspended solids, and the supernatant after centrifugation is carefully aspirated as the final analysis sample to avoid interference from solid particles.

[0066] In a specific implementation, laboratory analysis of leachate heavy metal content involves the use of two types of precision instruments, atomic absorption spectrometry and inductively coupled plasma mass spectrometry. Atomic absorption spectrometers are used to detect and analyze the concentrations of several specific heavy metal elements, such as lead, cadmium, mercury, and arsenic, in the analysis sample. The operation process includes atomizing the analysis sample and introducing it into an atomizer, measuring the absorbance of the characteristic spectral line of the specific element, and comparing it with a series of standard solutions of known concentration, thereby calculating the concentration value of each element in the analysis sample. For trace heavy metal elements such as chromium, nickel, and copper, a more sensitive inductively coupled plasma mass spectrometer is used for detection. The analysis sample is ionized in the plasma torch, and the ion signals of different mass-to-charge ratios are separated and detected by the mass spectrometry system. The software built into the instrument automatically calculates the concentration of each trace element according to the standard curve. All test results, including element names and corresponding concentration values, are compiled into a complete heavy metal content data report.

[0067] In a specific implementation, laboratory analysis of the number of pathogenic microorganisms in leachate mainly relies on microbiological culture techniques and molecular biology techniques. The multiple tube fermentation method is the standard method for detecting the number of coliform bacteria. The operation process is to inoculate a series of analysis samples with different dilution factors into fermentation tubes containing lactose peptone medium, incubate at a specific temperature for a period of time, observe the gas production of the fermentation tubes to determine the positive reaction of coliform bacteria, then verify by re-fermentation experiment, and finally calculate the nearest value of coliform bacteria in the analysis sample according to the number of positive reaction tubes and dilution factors by consulting the most probable number table. The fluorescent quantitative polymerase chain reaction technique is used to detect specific pathogenic microorganisms such as Salmonella and Shigella. This technique first extracts total microbial genomic deoxyribonucleic acid from the analysis sample, then uses primers and probes designed for the specific gene sequence of the target pathogenic microorganism for polymerase chain reaction amplification, and the fluorescent quantitative polymerase chain reaction instrument monitors the change of fluorescence signal in the amplification process in real time. By analyzing the number of cycles at which the amplification curve intersects with the set threshold line and referring to the standard curve, the gene copy number of the target pathogenic microorganism in the analysis sample is finally calculated. The number of pathogenic microorganisms is composed of the most probable number of coliform bacteria and the gene copy number of each specific pathogenic bacterium.

[0068] In a specific implementation, the final base physicochemical indicator data is formed by integrating online sensor measurement results and laboratory analysis data. The database system of the central control room receives and stores continuous monitoring data of chemical oxygen demand concentration, five-day biological oxygen demand concentration, total nitrogen concentration, and total phosphorus concentration from online sensors, while laboratory staff manually enter or automatically import heavy metal content data reports and pathogenic microorganism quantity data into the same database through a laboratory information management system interface. The database system timestamps all these data, unifies units, and performs preliminary integrity checks, ultimately generating a structured base physicochemical indicator data file containing all necessary parameters. This data file provides accurate input information for subsequent calculation of target pollutant removal rates. The entire collection process follows strict quality control procedures, including periodic calibration of online sensors, standard substance traceability for laboratory analysis, and determination of parallel samples, to maximize the accuracy and reliability of the base physicochemical indicator data.

[0069] Example 2: In a specific implementation, the first step in establishing a correlation model between pollutant load and treatment efficiency is to systematically collect complete data records of historical kitchen garbage leachate treatment cases. These historical case data come from the operation logs, test reports, and process parameter records of multiple operating leachate treatment plants. The collected base physicochemical indicator data includes at least the chemical oxygen demand concentration, five-day biological oxygen demand concentration, total nitrogen concentration, total phosphorus concentration, pH value, and suspended solid concentration of each case influent sample; the collected target pollutant removal rate data of the corresponding treatment process includes preset chemical oxygen demand removal rate targets and ammonia nitrogen removal rate targets; and the collected actual treatment efficiency data is the actual measured chemical oxygen demand removal rate value and ammonia nitrogen removal rate value after the treatment system is stably operated. The data collection process needs to ensure that the size of the historical data set is large enough and covers different influent load conditions and seasonal changes to enhance the universality and robustness of the constructed correlation model.

[0070] In a specific implementation, screening the key pollutant load parameters affecting the treatment efficiency requires statistical analysis of a large amount of collected historical data, using statistical methods such as correlation analysis or principal component analysis to calculate the correlation coefficient or contribution of each basic physicochemical index and actual treatment efficiency data. By setting a significant level threshold, chemical oxygen demand concentration, ammonia nitrogen concentration and total phosphorus concentration are identified as key independent variables that have a significant impact on the change of treatment efficiency, and the specific value of the key pollutant load parameter is directly measured by the influent concentration. The construction of the correlation model uses a multiple linear regression method, with the screened key pollutant concentration parameters as independent variables and the actual treatment efficiency data as dependent variables to construct a mathematical relationship. The multiple linear regression analysis process is completed using statistical calculation software, which performs least squares fitting to solve the regression coefficient of each independent variable and gives the goodness-of-fit index of the model and the significance test result of the regression coefficient. A correlation model for predicting chemical oxygen demand removal rate can be expressed in the following form:

[0071]

[0072] wherein the symbol represents the chemical oxygen demand removal rate to be predicted, the symbol represents the constant term of the multiple linear regression model, the symbols , respectively, represent the standardized partial regression coefficients corresponding to the three key independent variables of chemical oxygen demand concentration, ammonia nitrogen concentration and total phosphorus concentration, the symbols represent the measured value of the influent chemical oxygen demand concentration, the symbols represent the measured value of the influent ammonia nitrogen concentration, and the symbols represent the measured value of the influent total phosphorus concentration, and the symbols , , are the reference concentrations of chemical oxygen demand, ammonia nitrogen and total phosphorus, respectively, with the same dimension as the corresponding influent concentration, used for non-dimensionalization of the concentration data. The ratio of each concentration term in the formula to its reference concentration is a non-dimensional quantity, so the dimensions on both sides of the entire formula are consistent. After the model is constructed, a part of the historical data not involved in modeling is used to verify the correlation model, to evaluate the deviation between the predicted value and the actual observed value of the correlation model, and to ensure that the correlation model has sufficient prediction accuracy.

[0073] In a specific implementation, the established correlation model is applied to calculate the target pollutant removal rate data. The operation process is to extract the key parameters in the basic physicochemical index data of the homogenized leachate to be treated, which are the measured values of chemical oxygen demand concentration, ammonia nitrogen concentration and total phosphorus concentration. Divide these measured values by the corresponding reference concentrations to obtain dimensionless concentration ratios. These dimensionless ratios are used as input to the validated pollutant load and treatment efficiency correlation model. The correlation model outputs the predicted target pollutant removal rate data by executing a pre-set calculation program. The output data mainly includes the predicted chemical oxygen demand removal rate and ammonia nitrogen removal rate for the current influent conditions. It can be understood that the calculated target pollutant removal rate data is not a fixed value, but a scientifically expected value based on the current influent concentration conditions and historical operation rules, which provides a quantitative basis for the selection of target degradation process type data. It can be understood that the correlation model is not immutable. As the running time of the treatment system accumulates, new operation data will be continuously generated. These new data can be regularly supplemented to the historical database for updating and correcting the correlation model, so that the prediction ability of the correlation model continues to evolve and better adapts to changes in water quality. The selection of reference concentration can be based on the average value of historical data or common design influent concentration. The purpose is to standardize the data so that the regression coefficients have clear physical meaning and comparability.

[0074] Example 3: see Figure 3In a specific implementation, the process of selecting the biodegradation process type data starts with the establishment of a historical performance database containing three mainstream processes, namely anaerobic digestion, aerobic activated sludge process, and membrane bioreactor. The historical performance database is constructed by organizing published academic literature, technical reports, and operation archives of cooperative treatment plants. The database entries cover the long-term average removal efficiency, standard deviation of removal efficiency, typical hydraulic retention time, energy consumption per unit volume, residual sludge production, and system stability records of each process under different influent chemical oxygen demand, ammonia nitrogen, and total phosphorus loads. When selecting the process that best matches the target pollutant removal rate data, a multi-attribute decision analysis method is used. The target chemical oxygen demand removal rate and the target ammonia nitrogen removal rate are used as core screening conditions. At the same time, the pollutant load characteristics presented in the influent basic physicochemical index data, available site area, and budget constraints are also considered. The matching process is quantitatively scored, for example, by assigning a value to the closeness of each process's historical performance data to the current target value. After calculating the comprehensive score, the process with the highest score is selected as the final selected biodegradation process type data. Detailed operation requirements for this biodegradation process type data are also recorded, such as the need for strict anaerobic environment and biogas collection facilities for anaerobic digestion, continuous aeration and sludge return system for aerobic activated sludge process, and regular membrane cleaning and replacement plan for membrane bioreactor. Limiting conditions such as the sensitivity of simultaneous nitrification and denitrification efficiency to dissolved oxygen and membrane fouling trend are also recorded.

[0075] In a specific implementation, determining the microbial inoculation formula data directly depends on the selected biodegradation process type data. When the biodegradation process type data is clearly anaerobic digestion, the dominant species combination in the microbial inoculation formula data is directed to select methanogenic bacteria and acidifying bacteria. These two species can be enriched and cultured from the sludge discharged from a mature anaerobic digestion reactor or purchased as standard strains from a professional microbial strain preservation center. When the biodegradation process type data is clearly aerobic activated sludge process, the dominant species combination in the microbial inoculation formula data is directed to select nitrifying bacteria and denitrifying bacteria. The nitrifying bacteria group mainly includes ammonia-oxidizing bacteria and nitrite-oxidizing bacteria, and the denitrifying bacteria group is heterotrophic bacteria that can use nitrate or nitrite as an electron acceptor. These species usually come from the aerobic activated sludge of municipal wastewater treatment plants. Analyzing the carbon-to-nitrogen ratio in the basic physicochemical index data is a key step in adjusting the species ratio. A carbon-to-nitrogen ratio threshold is set. When the calculated carbon-to-nitrogen ratio is higher than this threshold, it indicates that the carbon source is relatively sufficient, which is conducive to the denitrification process. Therefore, the proportion of denitrifying bacteria in the mixed bacterial inoculation formula data is increased. When the calculated carbon-to-nitrogen ratio is lower than this threshold, it indicates that the carbon source may be insufficient while the nitrogen load is high, so the proportion of nitrifying bacteria in the microbial inoculation formula data needs to be increased to ensure effective conversion of ammonia nitrogen.

[0076] In practice, the calculation of microbial inoculum size is based on the target chemical oxygen demand (COD) removal rate from the target pollutant removal rate data. The calculation follows a fundamental principle: the preset degradation capacity per unit of biomass. The formula for calculating the microbial inoculum size can be expressed as:

[0077]

[0078] Where: symbol Represents the calculated absolute dry weight of the required microbial inoculant, symbol [symbol missing]. Represents the effective volume of a bioreactor, symbol Represents a baseline inoculum concentration parameter related to influent chemical oxygen demand (COD) concentration and microbial specific degradation rate, denoted by [symbol missing]. Represents an empirical constant characterizing the relationship between microbial growth and substrate removal, with the symbol... This represents the target chemical oxygen demand (COD) removal rate set in the target pollutant removal rate data. (Inoculum concentration per unit volume) The determination of the inoculum formulation requires reference to degradation activity data of microbial strains under similar water quality conditions. The activation conditions in the microbial inoculum formulation data include aseptically inoculating a calculated mass of microbial agent into an activation reactor containing a specific nutrient solution. The nutrient solution provides carbon, nitrogen, phosphorus, and trace elements. The isothermal incubation temperature is controlled within a range suitable for the growth of the target microbial strain; typically 35–37 degrees Celsius for anaerobic bacteria and 25–30 degrees Celsius for aerobic bacteria. The incubation period is specified, for example, 24 to 72 hours, during which the microbial activity is monitored periodically until it reaches a preset threshold. Activity can be determined by measuring dehydrogenase activity or substrate consumption rate. Once the activity threshold is met, the microbial inoculum formulation data is considered complete and can be used for subsequent bioreactor start-up. It can be understood that determining the microbial inoculum formulation data is a systematic process that integrates process type, water quality characteristics, and treatment objectives.

[0079] See Figure 4This study uses radar charts to comprehensively compare the overall performance of three mainstream biological treatment processes across five key dimensions. The five axes in the chart represent chemical oxygen demand (COD) removal capacity, ammonia nitrogen conversion efficiency, energy consumption level, sludge production, and system operational stability, respectively. Higher values ​​for each dimension indicate superior performance in that area. The three processes are represented by closed polygons of varying shapes on the radar chart, visually illustrating their respective strengths and characteristics. The polygon area reflects the overall performance level of the process. The distance from the center of the graph to each vertex represents the relative performance on that specific indicator, and the shape of the lines connecting the vertices reveals the technological focus and applicable scenarios of different processes. This multi-dimensional visual comparison clearly identifies the strengths and weaknesses of different treatment processes across various performance indicators, providing an intuitive basis for process selection.

[0080] Example 4: In practical implementation, setting the operating parameters of the bioreactor is a comprehensive calculation and setting process. The hydraulic retention time is calculated based on the target chemical oxygen demand (COD) removal rate and influent COD load set in the target pollutant removal rate data, and is derived using a mathematical model based on reaction kinetics. The sludge age parameter is determined based on the dominant growth rate of the selected microorganisms and the sludge stability required by the system. For systems that mainly remove carbonaceous organic matter, the sludge age is shorter, while for systems that need to complete nitrification, a longer sludge age is required. The setting of dissolved oxygen control level is strictly dependent on the biodegradation process type data. Aerobic processes need to maintain the dissolved oxygen concentration within a specific range to simultaneously meet the needs of heterotrophic bacteria degrading organic matter and autotrophic nitrifying bacteria converting ammonia and oxygen. Anaerobic processes must control the dissolved oxygen concentration at a level close to zero to ensure the activity of strictly anaerobic bacteria. The pH adjustment frequency is achieved by setting a control dead zone. When the value detected by the online pH sensor deviates from the set range by more than the width of the dead zone, the automatic acid or alkali metering pump is activated until the pH value returns to the set range. Nutrient addition schemes need to be formulated based on the microbial activity requirements and the analysis of influent water quality. By calculating the inherent carbon, nitrogen, and phosphorus content in the influent, it is determined whether additional nitrogen or phosphorus sources need to be added to the bioreactor influent to maintain the optimal carbon-nitrogen-phosphorus ratio required for microbial growth. By taking into account parameters such as hydraulic retention time, sludge age, dissolved oxygen control level, pH adjustment frequency, and nutrient addition scheme, a complete dataset of bioreactor operating parameters that can be directly read and executed by the control system is generated.

[0081] In practical implementation, starting the treatment system using bioreactor operating parameter data involves a series of sequentially executed steps. The first step is to uniformly add the activated microbial agent, corresponding to the microbial inoculation formula data, into the activated sludge mixture in the bioreactor. This addition can be achieved through a dedicated inoculation port using a sludge pump, followed by activating the agitator to ensure thorough mixing of the agent with the existing media within the reactor. Next, the preset influent flow rate setting is read from the bioreactor operating parameter data. By adjusting the frequency of the variable frequency pump on the influent pipeline, the influent flow rate of the kitchen waste leachate is precisely adjusted to the set value. Stable influent flow rate is crucial for ensuring accurate hydraulic retention time. The stirring intensity is adjusted according to the biodegradation process type data. For anaerobic digestion processes, the stirring intensity setting adopts an intermittent operation mode, for example, the agitator runs for a period and then stops for a period to prevent excessive shearing of the sludge flocs. For aerobic activated sludge processes or membrane bioreactor processes, the stirring intensity setting is achieved by controlling the air volume of the aeration system to ensure continuous stirring, maintaining sludge suspension and good mass transfer. Temperature maintenance is achieved by real-time monitoring of the mixed liquor temperature using temperature sensors within the reactor. The monitoring signal is fed back to the temperature control unit, which adjusts the flow rate of the circulating heat or coolant in the jacket or coils to stably maintain the reactor temperature within the optimized range specified in the bioreactor operating parameters. Dissolved oxygen concentration control is achieved through a closed-loop system consisting of a gas flow meter and an online dissolved oxygen sensor. The dissolved oxygen sensor detects real-time values, and the controller adjusts the aeration fan speed or valve opening based on the deviation between the detected value and the set dissolved oxygen control level in the bioreactor operating parameters, thereby controlling the amount of air or oxygen supplied to the reactor and maintaining the dissolved oxygen concentration within the optimized range. The treatment system operates continuously, and chemical oxygen demand (COD) concentration is periodically sampled from the effluent outlet. When the fluctuation range of the COD concentration values ​​detected consecutively relative to its average value is less than a predefined stability threshold, the system is considered to have reached a stable state. The liquid collected at this point is the primary effluent. Refer to Table 1 for key operating parameters of the bioreactor.

[0082] Table 1: Operating Parameters of Bioreactor

[0083] Parameter Name Typical Set Values for Anaerobic Digestion Process Typical Set Values for Aerobic Activated Sludge Process Hydraulic Retention Time (days) 20-30 10-15 SRT (days) >30 10-20 Dissolved Oxygen Control Level (mg / L) <0.2 2.0-4.0 pH Adjustment Set Range 6.5-7.5 6.5-8.0 Mixing Intensity Control Mode Intermittent Mixing (e.g. 10 min on / 30 min off) Continuous Aeration Mixing Temperature Control Range (°C) 35±2 25±3

[0084] It is understandable that the hydraulic retention time in the bioreactor operating parameter data... The following formula can be used to correlate it with the inlet flow rate:

[0085]

[0086] Where: symbol Represents the theoretical hydraulic residence time; symbol Represents the effective volume in a bioreactor used for biochemical reactions, excluding dead zones and sedimentation zones; symbol The instantaneous volumetric flow rate value represents the influent flow rate set in the bioreactor operating parameter data.

[0087] See Figure 5 The system uses grouped bar charts to illustrate the differences and relative relationships between two typical biological treatment processes in terms of seven core operating parameters. The three parameters on the left reflect the system's timescale settings, including hydraulic retention time and sludge age; the two middle parameters represent environmental condition control, involving dissolved oxygen concentration and pH range; and the two parameters on the right directly reflect the treatment effect, i.e., the removal rate of major pollutants. Different colored bars correspond to the two treatment processes, and the bar height visually displays the specific numerical level of each parameter. Comparing the heights of adjacent bars clearly shows the significant differences between the two processes in parameter settings. The units for each parameter are labeled at the bottom of the charts to ensure the accuracy of data interpretation. This intuitive comparison method helps to understand the technical characteristics and application requirements of different processes in terms of operating parameter configuration.

[0088] Example 5: In specific implementation, monitoring data during the primary effluent detection is a continuous activity combining online monitoring and offline laboratory analysis. Online monitoring equipment, including turbidity sensors, conductivity sensors, and redox potential sensors, is directly installed on the bioreactor's effluent pipeline. These sensors continuously collect data at a set frequency and transmit voltage or current signals in real time to a database in the central control room for storage and trend display via a data acquisition module. Timed sampling and detection are performed according to preset time intervals. Sampling points are located at dedicated sampling valves downstream of the online sensors. The collected primary effluent samples are immediately aliquoted into sterile sample bottles and labeled with time tags. A portion of the samples is used for microbial community structure analysis, while another portion, after filtration or centrifugation pretreatment, is used for metabolite concentration determination. Microbial community structure analysis employed high-throughput sequencing technology. The experimental procedure included extracting total genomic DNA from samples, PCR amplification of the variable region of the 16S rRNA gene, constructing sequencing libraries, performing paired-end sequencing on a sequencing platform, quality filtering and chimera removal of the raw sequencing data, clustering the effective sequences into operational taxonomic units, and performing species annotation by comparison with a reference database. Finally, relative abundance distribution data of bacteria and archaea at the phylum, class, order, family, genus, and species levels were obtained. Metabolite concentration determination targeted small molecules such as volatile fatty acids (e.g., acetic acid, propionic acid, butyric acid), ammonia nitrogen, nitrite nitrogen, and nitrate nitrogen, using ion chromatography or high-performance liquid chromatography (HPLC). The chromatographs were equipped with appropriate detectors, and the precise concentration of each metabolite was calculated by comparing the sample peak area with the calibration curve of standard substances. The combined data of physical indicators from online monitoring, microbial community structure data obtained from high-throughput sequencing, and metabolite concentration data from chromatographic analysis constituted a complete, multi-dimensional time-series monitoring dataset for assessing biodegradation processes and system health status.

[0089] In practice, the purpose of advanced treatment of the final effluent is to remove trace pollutants that remain after biodegradation, so that they meet strict discharge standards or reuse requirements. The selection of advanced treatment process is based on the analysis of the final effluent quality. When it is necessary to remove recalcitrant organic matter and color, activated carbon adsorption process is adopted. The activated carbon adsorption process uses granular activated carbon or powdered activated carbon. Granular activated carbon is filled in the adsorption tower, and the final effluent flows through the carbon bed at a certain empty tower flow rate. Powdered activated carbon is directly added to the final effluent, mixed and stirred, and then separated by sedimentation or filtration. The pore size distribution and surface chemical properties of the activated carbon are selected according to the molecular size and polarity of the target pollutants. When the final effluent contains highly stable organic pollutants or requires complete inactivation of pathogenic microorganisms, advanced oxidation processes are employed. Examples of such processes include ozone-ultraviolet combined oxidation systems. An ozone generator produces a high concentration of ozone gas, which is injected into the final effluent through a microporous gas distribution device. Simultaneously, ultraviolet lamps emit specific wavelengths of ultraviolet light to irradiate the water flow. The ultraviolet photocatalyzes the decomposition of ozone, generating hydroxyl radicals with extremely strong oxidizing capabilities. These hydroxyl radicals non-selectively attack and mineralize organic pollutants. It is understood that activated carbon adsorption and advanced oxidation processes can be applied individually or combined in series, depending on the water quality, to enhance the treatment effect.

[0090] In practice, verifying discharge compliance is the final water quality assessment step after the advanced treatment process. Measuring the concentration of residual pollutants in the final effluent requires analyzing samples of the final effluent according to official national or local standards and methods. Key indicators, including but not limited to chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD5), total nitrogen, total phosphorus, suspended solids, heavy metal ion concentrations, and coliform count, are tested according to standard operating procedures. Comparison with emission standard limits involves comparing the measured concentrations of each residual pollutant with the maximum permissible emission concentrations specified in the applicable "Integrated Wastewater Discharge Standard" or specific industry emission standards. The verification process can be automated using data processing software. The software inputs the measurement results and standard limits, performs logical judgments, and outputs the verification results, explicitly stating "compliant" or "non-compliant." For non-compliant items, the software lists the specific items exceeding the standard and the multiple of exceedance. The advanced treatment removal rate is an indicator used to quantify the removal effectiveness of specific pollutants. It can be calculated using the following formula:

[0091]

[0092] Where: symbol Represents the percentage of a specific pollutant removed during the advanced treatment stage; symbol Represents the mass concentration of a specific pollutant before it enters the advanced treatment unit; symbol This represents the residual mass concentration of a specific pollutant in the final effluent sample after advanced treatment.

[0093] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0094] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for treating leachate from kitchen waste after waste sorting and recycling, characterized in that, Implement the following procedures: Pretreatment of kitchen waste leachate yields homogenized leachate. Collect basic physicochemical index data of the homogenized leachate; Based on the aforementioned basic physicochemical index data, the target pollutant removal rate data is calculated; Based on the target pollutant removal rate data, select the biodegradation process type data; Based on the data of the selected biodegradation process type, determine the microbial inoculation formulation data; Based on the microbial inoculation formula data and the target pollutant removal rate data, the bioreactor operating parameters are set. The treatment system is started using the bioreactor operating parameter data to biodegrade the homogenized leachate and produce primary effluent. Monitoring data during the detection of the primary effluent; Based on the monitoring data during the process, optimize the operating parameters of the bioreactor; The optimized bioreactor operating parameters are used to continue the degradation process, generating the final effluent. The final effluent undergoes advanced treatment, and discharge compliance is verified.

2. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Pretreatment of kitchen waste leachate includes: Large particles of impurities are removed from the raw leachate by passing it through a grid filter. The temperature of the filtered leachate is adjusted to a preset range, and a coagulant is added to flocculate and settle the suspended solids. The supernatant is then collected as homogenized leachate.

3. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, The basic physicochemical properties of the homogenized leachate were collected, including: The chemical oxygen demand (COD), biological oxygen demand (BOD), total nitrogen (TNO), and total phosphorus (TP) concentrations of leachate were measured using online sensors. Laboratory analysis of heavy metal content and pathogenic microorganism count in leachate, integration of measurement and analysis results to form basic physicochemical index data; The laboratory analysis of the heavy metal content and pathogenic microorganism count in the leachate includes the following steps: Collect representative stratified samples of the homogenized leachate, centrifuge the samples to remove suspended solids, and take the supernatant as the analytical sample; The concentrations of heavy metals such as lead, cadmium, mercury, and arsenic in the samples were detected by atomic absorption spectrometry, and the concentrations of trace heavy metals such as chromium, nickel, and copper were detected by inductively coupled plasma mass spectrometry. The concentration values ​​of each element were summarized to form heavy metal content data. The number of coliform bacteria in the samples was detected by multi-tube fermentation, and the gene copy number of Salmonella and Shigella pathogens in the samples was detected by real-time quantitative polymerase chain reaction (qPCR). The number of microorganisms was then summarized to form pathogen count data.

4. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Based on the aforementioned basic physicochemical index data, the target pollutant removal rate data is calculated, including: Establish a correlation model between pollutant load and treatment efficiency. Input key parameters from basic physicochemical index data into the correlation model and output target pollutant removal rate data, including chemical oxygen demand removal rate and ammonia nitrogen removal rate. The establishment of the correlation model between pollutant load and treatment efficiency includes the following steps: Collect basic physicochemical index data, target pollutant removal rate data, and actual treatment efficiency data of historical kitchen waste leachate treatment cases; Key pollutant load parameters affecting treatment efficiency were screened, including chemical oxygen demand (COD) load, ammonia nitrogen load, and total phosphorus load. Using key pollutant load parameters as independent variables and actual treatment efficiency data as dependent variables, a multiple linear regression method was used to fit the quantitative relationship between variables and construct a correlation model between pollutant load and treatment efficiency.

5. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Based on the target pollutant removal rate data, select the biodegradation process type data, including: By comparing historical performance data of anaerobic digestion, aerobic sludge process and membrane bioreactor, the process that best matches the target pollutant removal rate data is selected as the biodegradation process type data, and the operation requirements and limitations of the selected process are recorded.

6. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Based on the data of the selected biodegradation process type, determine the microbial inoculation formulation data, including: Based on data on biodegradation process types, a dominant microbial strain combination is selected, and the strain ratio is adjusted to adapt to the characteristics of the target pollutant. The inoculum size and activation conditions are determined to generate microbial inoculum formulation data, specifically including: When the biodegradation process type data is anaerobic digestion, methanogenic bacteria and acidifying bacteria are selected as the dominant bacterial species combination; when the biodegradation process type data is aerobic activated sludge process, nitrifying bacteria and denitrifying bacteria are selected as the dominant bacterial species combination. Analyze the carbon-nitrogen ratio in the basic physicochemical index data. When the carbon-nitrogen ratio is higher than the threshold, increase the proportion of denitrifying bacteria; when the carbon-nitrogen ratio is lower than the threshold, increase the proportion of nitrifying bacteria. The microbial inoculum amount is calculated based on the target value of chemical oxygen demand removal rate in the target pollutant removal rate data. The inoculum amount is the product of the effective volume of the reactor and the inoculum concentration per unit volume. The activation conditions are set to constant temperature culture in nutrient solution for a specified time until the microbial activity reaches the preset threshold, thus completing the construction of microbial inoculation formula data.

7. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Based on the microbial inoculation formulation data and the target pollutant removal rate data, the bioreactor operating parameters are set, including: Calculate hydraulic retention time and sludge age parameters, set dissolved oxygen control levels and pH adjustment frequencies, determine nutrient addition schemes based on microbial activity requirements, and generate bioreactor operating parameter data by combining comprehensive parameters.

8. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, The treatment system is started using the bioreactor operating parameter data to biodegrade the homogenized leachate, producing primary effluent, including: Inoculate the bioreactor with microbial agents, adjust the influent flow rate and stirring intensity to set values, maintain temperature and gas volume within the optimized range, and collect the primary effluent after the system reaches a stable state. This process includes: The microbial inoculation formula data is uniformly added to the activated sludge in the bioreactor; Read the influent flow rate set value from the bioreactor operating parameter data, and adjust the influent flow rate to the set value using a variable frequency pump; Adjust the stirring intensity according to the process type: use intermittent stirring setting value for anaerobic process and continuous aeration stirring setting value for aerobic process; The temperature inside the reactor is monitored in real time by a temperature sensor, and the temperature is maintained within the optimized range by a heating / cooling unit. The aeration rate is controlled by a gas flow meter to keep the dissolved oxygen concentration within the optimal range. The system is continuously operated until the fluctuation range of the chemical oxygen demand in the effluent is less than the stable threshold. At this point, the system is considered to have reached a stable state and the primary effluent is collected.

9. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, Monitoring data during the detection of the primary effluent includes: The turbidity, conductivity, and redox potential of the primary effluent were continuously monitored, and the microbial community structure and metabolite concentration were sampled and detected at regular intervals. The data were then compiled as monitoring data during the process.

10. The method for treating leachate from kitchen waste after waste sorting and recycling according to claim 1, characterized in that, The final effluent undergoes advanced treatment, and discharge compliance is verified, including: Trace pollutants are removed using activated carbon adsorption or advanced oxidation processes. The concentration of residual pollutants in the final effluent is measured, compared with the emission standard limits, and the verification results are output.

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