A method for detecting perfluorinated compound pollution in lakes

Abstract

The present invention relates to the field of data analysis technology, and in particular to a method for detecting lake perfluorinated compound pollution, including setting a sampling time interval, dividing the collection area into two-dimensional grids, and integrating water sample data with environmental data to improve the accuracy and reliability of subsequent data analysis; optimizing the adsorption conditions and elution efficiency of the target perfluorinated compound, and using the sensitivity analysis method to obtain the best separation conditions, thereby improving the enrichment efficiency and purity of the target perfluorinated compound, and providing a better quality test sample for analysis and detection; detecting and analyzing the separated target perfluorinated compound, and judging whether its concentration exceeds the standard, timely discovering pollution problems and taking adjustment measures, and effectively controlling the spread and deterioration of environmental pollution. The present invention is used to solve the technical problem of insufficient accuracy of water sample sampling and detection and analysis in water resource management in existing solutions.

Description

Technical Field

[0001] The invention relates to the technical field of data analysis, and in particular to a method for detecting perfluorinated compound pollution in lakes. Background Art

[0002] Data analysis technology refers to the process of using appropriate statistical analysis methods to analyze large amounts of collected data in order to extract useful information and form conclusions. This process involves detailed research and summarization of the data, aiming to maximize the development of data functions and maximize the role of data.

[0003] With the continuous development of science and technology, data analysis technology has been widely used in many fields, including transportation, energy, and medical care. At present, water resource management in the field of environmental protection still faces some challenges, including the following aspects: low efficiency of data collection and processing. Traditional methods may only rely on the collection of water samples at a single point or a few points, resulting in incomplete data coverage, and unable to fully reflect the spatial distribution and concentration changes of perfluorinated compounds in lakes; low efficiency of pollutant separation. Perfluorinated compounds are difficult to separate in the environment due to their high stability and difficulty in degradation; poor detection effect. Traditional detection methods may not be able to accurately detect low concentrations of perfluorinated compounds due to sensitivity limitations, resulting in the inability to accurately detect the presence of pollutants, thereby underestimating the degree of pollution; lack of comprehensive assessment and response measures. Previous methods may only focus on the concentration detection of pollutants, while ignoring the ecological effects of pollutants and the control of potential risks; in response to these challenges, corresponding solutions and technical means need to be adopted to improve the detection efficiency of perfluorinated compound pollution in lakes. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose a method for detecting perfluorinated compound pollution in lakes.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for detecting perfluorinated compound pollution in lakes, comprising:

[0007] Step 1: Set the sampling time interval, divide the collection area into two-dimensional grids, and integrate the water sample data with the environmental data to form a complete data set to provide multi-dimensional information for subsequent analysis;

[0008] Step 2: Optimize the adsorption conditions and elution efficiency of the target perfluorinated compound, and use the sensitivity analysis method to obtain the optimal separation conditions based on the optimized adsorption conditions and elution efficiency;

[0009] Step 3: Separate the target perfluorinated compounds from the water sample using the optimal separation conditions, detect and analyze the separated target perfluorinated compounds, determine whether their concentration exceeds the standard based on the detected and analyzed target perfluorinated compounds, and take adjustment measures based on the determination results.

[0010] It should be noted that the method for detecting lake perfluorinated compound pollution proposed in the present invention can be widely used in ecological monitoring and management or water resource control in the field of environmental protection. The method can be used to monitor the water quality of lake water bodies or environmental pollution in sediments and other aspects. Specifically, it can be used to comprehensively analyze and accurately evaluate the perfluorinated compound data in the collected water samples, surrounding environment and sediments through data analysis technology. Through data collection and processing, detection and analysis, emergency response and control measures and other links, the health and stability of the lake ecosystem is ensured, and the sustainable use of water resources is promoted. At the same time, the method meets the urgent needs of environmental protection departments for lake pollution prevention and control, and realizes the effective monitoring and management of new pollutants such as perfluorinated compounds.

[0011] Furthermore, the process of setting the sampling time interval and dividing the acquisition area into two-dimensional grids includes:

[0012] Set the sampling interval to ; where the time interval is determined based on the fluidity of the lake, the diffusion rate of pollutants, seasonal changes, and the limitations of the sampling equipment;

[0013] Divide the acquisition area into two-dimensional grids according to its shape and size, that is, grids; each grid represents a potential collection location, Respectively represent the positions of the grid points in the east-west direction and the north-south direction. The collection area is the lake. Indicates the number of grids in the east-west direction, Indicates the number of grids in the north-south direction;

[0014] The coordinates of the grid points are expressed as:

[0015]

[0016] In the formula, Indicates the coordinates of the lower left corner of the acquisition area or any selected starting point, Represents the width of the grid in the east-west and north-south directions respectively; Represents an index;

[0017] Water samples were collected in the collection area (i.e., in the lake) in combination with preset time intervals and divided two-dimensional grids.

[0018] Furthermore, the process of integrating water sample data with environmental data includes:

[0019] Obtain water sample data and environmental data and mark them as ; Among them, water sample data is a collection of multiple water samples, each of which contains the sampling time , sampling location and water sample physicochemical properties ,Right now ,and Indicates the total number of water samples; environmental data is a collection of multiple time points, each of which Corresponding to a set of environmental parameters , including temperature, humidity, wind speed, etc., namely ,and Indicates the total number of environmental parameters;

[0020] Among them, water sample data and environmental data are collected and recorded within a specific time and space range through sampling equipment and environmental monitoring equipment respectively; it is understandable that water sample data is obtained by setting sampling points in lakes, rivers or other waters, and using sampling equipment (such as automatic sampling robots or buoys) to collect water at preset time intervals, and the sampling points are preset according to the research needs and the characteristics of the research area, and recorded in the sampling data, including the sampling time and sampling location; environmental data covers geographical location (such as longitude and latitude), weather conditions (such as temperature, humidity, wind speed, wind direction, precipitation, etc.) and seasonal changes (such as month, season identification) and other information;

[0021] Integrate water sample data with environmental data; the specific process of integration is as follows:

[0022] For each water sample , matching the environmental parameters closest to the time ;

[0023] Define the time difference function , and determine that Smallest ,Right now ; In the formula, Is a function that represents the time matching index, which is used to convert the index of the water sample Index that maps to environment parameters ;

[0024] It can be understood that matching environmental parameters according to water samples is achieved by calculating the time difference and selecting the index with the minimum time difference, that is, first calculating the time difference between each candidate environmental parameter and the water sample data point, and then selecting the environmental parameter with the minimum time difference as the matching result;

[0025] Use the selected time to match the index , linking water sample data with environmental data and generating an integrated dataset , the dataset contains the complete environmental parameters of each water sample and its corresponding time point, namely

[0026] .

[0027] Further, the process of optimizing the adsorption conditions and elution efficiency of the target perfluorinated compound includes:

[0028] From the integrated dataset The features that affect the adsorption conditions are selected as input variables;

[0029] Understandably, the features extracted from the integrated dataset that are relevant to enrichment optimization include the physicochemical properties of water samples (such as dissolved oxygen, conductivity, etc.) and the environmental parameters at the corresponding time points (such as temperature, pH value, light intensity, etc.) and any other factors that may affect the enrichment efficiency;

[0030] Define the adsorption condition as a vector ;in, It represents the contact time, i.e. the length of time the sample is in contact with the adsorbent (or other treatment medium);

[0031] Using comprehensive objective function Measure the enrichment effect and purity under the preset adsorption conditions:

[0032]

[0033] In the formula, represents the weight coefficient, and , used to adjust the relative importance of enrichment efficiency and purity; represents the enrichment efficiency; Indicates purity; where enrichment efficiency refers to the efficiency of enriching the target perfluorinated compounds from the water sample by optimizing the adsorption conditions and elution steps, and is used to measure the proportion of the target perfluorinated compounds that are effectively captured and enriched on the adsorbent or other treatment media. High enrichment efficiency means that under the same conditions, more target perfluorinated compounds can be captured, thereby improving the sensitivity and accuracy of subsequent analysis and detection; purity refers to the purity of the target perfluorinated compounds after enrichment, and is used to measure the degree of separation of the target perfluorinated compounds from other impurities or unwanted compounds during the enrichment process;

[0034] It is understandable that during the enrichment optimization process, the purity of the target perfluorinated compound can be increased as much as possible and the impurity content can be reduced by adjusting parameters such as adsorption conditions and elution steps;

[0035] Update the vector by iterative formula until the stopping criterion is met:

[0036]

[0037] In the formula, It is an identifier of the iteration number, which is used to track or represent the variable of the current iteration round; Represents the learning rate, which is a hyperparameter that determines the size of the step taken in the gradient direction; express The gradient of Represents the current vector value; Represents the updated vector value;

[0038] The stopping criterion is that the change of the comprehensive objective function value is less than the change threshold. When the change of the comprehensive objective function value during the iteration process is less than the change threshold, it indicates that the function value has stabilized and the iteration is stopped. The change threshold is used to judge whether the change of the comprehensive objective function value is small enough, so that the algorithm is considered to have converged or is close to convergence.

[0039] The current elution efficiency is calculated using a formula, and the elution efficiency is optimized based on the calculation result; wherein, the elution efficiency calculation formula is: , where It indicates the elution efficiency. denote the flow rate and volume of the eluent, respectively. represents the elution amount of the target perfluorinated compound, represents the total amount of adsorbed target perfluorinated compounds; the result of optimizing elution efficiency is expressed as:

[0040]

[0041] In the formula, represents the optimized eluent flow rate and volume; represents the feasible domain of elution conditions; is an operator that returns the parameter value that maximizes the elution efficiency, that is, to find the best elution conditions (consisting of flow rate and volume) to maximize the elution efficiency.

[0042] Furthermore, the process of obtaining the optimal separation conditions by using the sensitivity analysis method in combination with the optimized adsorption conditions and elution efficiency includes:

[0043] Design a predictive model whose output is the input parameter vector The function of ;in, represents any combination of enrichment efficiency and purity, Contains optimized parameters adsorption conditions and elution efficiency;

[0044] Choose an initial input parameter vector As the basic condition, represents the total number of parameters in the input parameter vector;

[0045] For each input parameter , perform the following steps, where Indicates the index of the input parameter:

[0046] J1. Fix all other parameters In its corresponding basic conditions The value of Represents the index of all other parameters;

[0047] J2. Input parameters The single variable change is denoted as ,in, Indicates the total number of changes of the parameter;

[0048] J3. For each , calculate the corresponding output

[0049] ,in, Indicated in On the input parameters, The parameter value after the change is An index indicating the number of times the parameter has changed;

[0050] Draw a sensitivity diagram to perform sensitivity analysis, that is, Scatter plot or curve graph;

[0051] Determine the output The parameters with the greatest impact, and the resulting positive or negative impact;

[0052] Based on the results of the sensitivity analysis, the selection results in the output Significantly increase (or reach the desired target) the parameter value as the optimal separation condition, thereby providing better quality test samples for analytical testing;

[0053] It is understandable that the optimal separation conditions are intended to optimize the process of separating and purifying the target perfluorinated compounds from water samples, aiming to improve the enrichment efficiency and purity of the target perfluorinated compounds and ensure the effectiveness of the separation and purification process so as to facilitate subsequent detection of whether the concentration of the target perfluorinated compounds exceeds the standard after purification, and the optimal separation conditions may be a combination of multiple parameters rather than the optimal value of a single parameter.

[0054] Furthermore, the process of detecting and analyzing the separated target perfluorinated compounds includes:

[0055] Use high-precision analytical instruments to test the pollution concentration of the separated target perfluorinated compounds to determine the actual pollution concentration of the target perfluorinated compounds ;

[0056] Setting pollution concentration thresholds ;

[0057] The concentration of the target perfluorinated compounds detected Perform comparative analysis, where the comparative analysis formula is specifically:

[0058]

[0059] In the formula, It represents the pollution degree assessment index; It is an adjustment factor used to control the sensitivity of the pollution index to changes in concentration; To adjust the parameters, it is used to introduce the exponential influence of the degree of deviation of pollution concentration from the average concentration, so that the concentration that deviates extremely from the average value contributes more to the pollution index; It represents the average pollution concentration in the collection area; Indicates the standard deviation corresponding to the pollution concentration, which is used to standardize the concentration deviation; represents the number of other factors affecting pollution assessment considered, Represents an index; Indicates The weight of each factor; Indicates The value of a factor that affects pollution assessment.

[0060] Furthermore, the process of determining whether the concentration of the target perfluorinated compound exceeds the standard after detection and analysis, and taking adjustment measures according to the determination result includes:

[0061] When assessing the degree of pollution, if the pollution assessment index , it is determined that the target perfluorinated compound concentration exceeds the standard, and the collection area corresponding to the target perfluorinated compound concentration is marked;

[0062] For sampling frequency where pollution level exceeds the standard, according to the pollution level assessment index Adjust the sampling frequency of this area, that is , where represents the adjusted sampling frequency, represents the initial sampling frequency, is a control parameter used to control the amplitude and speed of the sampling frequency increase, and are greater than 0, when the pollution degree assessment index When the value of is large, due to , The growth rate will be faster than the pollution assessment index itself, resulting in a more substantial increase in the sampling frequency;

[0063] Combined with the obtained , adjust the subsequent monitoring plan of the collection area to ensure that water samples can be collected for testing more frequently when pollution is serious.

[0064] Compared with the existing technology, the advantages of the method for detecting lake perfluorinated compound pollution provided by the present invention are:

[0065] 1. The present invention divides the collection area into two-dimensional grids by setting the sampling time interval, and integrates the water sample data with the environmental data to form a complete data set, providing multi-dimensional information for subsequent analysis, which helps to accurately control the distribution and change law of the target perfluorinated compounds under different environmental conditions, ensure the validity and representativeness of the data, and provide high-quality input data for subsequent steps;

[0066] 2. The present invention optimizes the adsorption conditions and elution efficiency of the target perfluorinated compounds, effectively adsorbs the target perfluorinated compounds from the water sample, reduces losses, improves the enrichment efficiency, ensures that impurities are removed to the maximum extent during the separation process, and improves the purity of the target perfluorinated compounds. By combining the optimized adsorption conditions and elution efficiency, the sensitivity analysis method is used to obtain the best separation conditions, which can maximize the separation efficiency and detection accuracy, help provide high-quality samples for subsequent detection and analysis, and ensure the reliability of the results;

[0067] 3. The present invention separates the target perfluorinated compounds from the water sample under the optimal separation conditions, detects and analyzes the separated target perfluorinated compounds, and determines whether the concentration of the target perfluorinated compounds exceeds the standard based on the detected and analyzed target perfluorinated compounds. Once it is found that the concentration of the target perfluorinated compounds exceeds the standard, necessary adjustment measures can be taken immediately according to the test results, which helps to promptly curb the further deterioration of environmental pollution.

[0068] In summary, the present invention, through data integration and preprocessing, optimization of separation conditions, precise detection and analysis, and timely response and adjustment, these steps are interrelated and complementary, together forming a complete and efficient process for the detection and analysis of target perfluorinated compounds in water samples, which not only improves the analysis efficiency and data quality, but also enhances the detection accuracy and decision-making support capabilities, provides a strong guarantee for environmental protection and governance work, and ensures the normal implementation of a subsequent method for detecting perfluorinated compound pollution in lakes. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a flow chart of a method for detecting perfluorinated compound pollution in lakes proposed by the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Reference Figure 1 , a method for detecting perfluorinated compound pollution in lakes, comprising:

[0072] Step 1: Set the sampling time interval, divide the collection area into two-dimensional grids, and integrate the water sample data with the environmental data to form a complete data set to provide multi-dimensional information for subsequent analysis;

[0073] Step 2: Optimize the adsorption conditions and elution efficiency of the target perfluorinated compound, and use the sensitivity analysis method to obtain the optimal separation conditions based on the optimized adsorption conditions and elution efficiency;

[0074] Step 3: Separate the target perfluorinated compounds from the water sample using the optimal separation conditions, detect and analyze the separated target perfluorinated compounds, determine whether their concentration exceeds the standard based on the detected and analyzed target perfluorinated compounds, and take adjustment measures based on the determination results.

[0075] It should be noted that the method for detecting lake perfluorinated compound pollution proposed in the present invention can be widely used in ecological monitoring and management or water resource control in the field of environmental protection. The method can be used to monitor the water quality of lake water bodies or environmental pollution in sediments and other aspects. Specifically, it can be used to comprehensively analyze and accurately evaluate the perfluorinated compound data in the collected water samples, surrounding environment and sediments through data analysis technology. Through data collection and processing, detection and analysis, emergency response and control measures and other links, the health and stability of the lake ecosystem is ensured, and the sustainable use of water resources is promoted. At the same time, the method meets the urgent needs of environmental protection departments for lake pollution prevention and control, and realizes the effective monitoring and management of new pollutants such as perfluorinated compounds.

[0076] See also Figure 1 The present invention provides a method for detecting lake perfluorinated compound pollution. In step 1, the steps of setting a sampling time interval, dividing the sampling area into two-dimensional grids, and integrating water sample data with environmental data include:

[0077] Step 101, set the sampling time interval to ;

[0078] In step 101, the time interval is determined based on the mobility of the lake, the diffusion rate of pollutants, seasonal changes, and the limitations of the sampling equipment; if water samples need to be collected once a day, then days; if the sampling frequency is higher, such as once every 4 hours, then sky;

[0079] Step 102: Divide the acquisition area into two-dimensional grids according to the shape and size of the acquisition area. A grid;

[0080] In step 102, each grid represents a potential collection location, Respectively represent the positions of the grid points in the east-west direction and the north-south direction. The collection area is the lake. Indicates the number of grids in the east-west direction, Indicates the number of grids in the north-south direction;

[0081] Step 103, the coordinates of the grid points are expressed as:

[0082]

[0083] In the formula, Indicates the coordinates of the lower left corner of the acquisition area or any selected starting point, Represents the width of the grid in the east-west and north-south directions respectively; Represents an index;

[0084] Step 104, collecting water samples in the collection area (i.e., the lake) in combination with the preset time interval and the divided two-dimensional grid;

[0085] Step 105: Obtain water sample data and environmental data, and mark them as ; Among them, water sample data is a collection of multiple water samples, each of which contains the sampling time , sampling location and water sample physicochemical properties ,Right now

[0086] ,and Indicates the total number of water samples; environmental data is a collection of multiple time points, each of which Corresponding to a set of environmental parameters , including temperature, humidity, wind speed, etc., namely ,and Indicates the total number of environmental parameters;

[0087] In step 105, water sample data and environmental data are collected and recorded by sampling equipment and environmental monitoring equipment within a specific time and space range respectively; it is understandable that water sample data is obtained by setting sampling points in lakes, rivers or other waters, and using sampling equipment (such as automatic sampling robots or buoys) to collect water sample data within a preset time interval, and the sampling points are preset according to the research needs and the characteristics of the research area, and recorded in the sampling data, including the sampling time and sampling location; the environmental data covers information such as geographical location (such as longitude and latitude), weather conditions (such as temperature, humidity, wind speed, wind direction, precipitation, etc.) and seasonal changes (such as month, season identification);

[0088] Step 106: Integrate the water sample data with the environmental data; the specific process of the integration is as follows:

[0089] For each water sample , matching the environmental parameters closest to the time ;

[0090] Define the time difference function , and determine that Smallest ,Right now ; In the formula, Is a function that represents the time matching index, which is used to convert the index of the water sample Index that maps to environment parameters ;

[0091] In step 106, matching the environmental parameters according to the water sample is achieved by calculating the time difference and selecting the index of the minimum time difference, that is, first calculating the time difference between each candidate environmental parameter and the water sample data point, and then selecting the environmental parameter with the minimum time difference as the matching result;

[0092] Step 107: Use the selected time matching index , linking water sample data with environmental data and generating an integrated dataset , the dataset contains the complete environmental parameters of each water sample and its corresponding time point, namely

[0093] .

[0094] See also Figure 1 The present invention provides a method for detecting lake perfluorinated compound pollution. In the step 2, the adsorption conditions and elution efficiency of the target perfluorinated compound are optimized, and the steps of obtaining the optimal separation conditions by using a sensitivity analysis method in combination with the optimized adsorption conditions and elution efficiency include:

[0095] Step 201: From the integrated data set The features that affect the adsorption conditions are selected as input variables;

[0096] In step 201, features relevant to enrichment optimization are extracted from the integrated data set, including physicochemical property parameters of the water sample. (such as dissolved oxygen, conductivity, etc.) and the environmental parameters at the corresponding time points (such as temperature, pH value, light intensity, etc.) and any other factors that may affect the enrichment efficiency;

[0097] Step 202: Define the adsorption condition as a vector ;in, It represents the contact time, i.e. the length of time the sample is in contact with the adsorbent (or other treatment medium);

[0098] Step 203: Using the comprehensive objective function Measure the enrichment effect and purity under the preset adsorption conditions:

[0099]

[0100] In the formula, represents the weight coefficient, and , used to adjust the relative importance of enrichment efficiency and purity; represents the enrichment efficiency; Indicates purity;

[0101] In step 203, the enrichment efficiency refers to the efficiency of enriching the target perfluorinated compound from the water sample by optimizing the adsorption conditions and elution steps, which is used to measure the proportion of the target perfluorinated compound that is effectively captured and enriched on the adsorbent or other processing medium. A high enrichment efficiency means that under the same conditions, more target perfluorinated compounds can be captured, thereby improving the sensitivity and accuracy of subsequent analysis and detection; purity refers to the purity of the target perfluorinated compound after enrichment, which is used to measure the degree of separation of the target perfluorinated compound from other impurities or unwanted compounds during the enrichment process; in the process of enrichment optimization, by adjusting parameters such as adsorption conditions and elution steps, the purity of the target perfluorinated compound can be increased as much as possible and the impurity content can be reduced;

[0102] Step 204: Update the vector by iterative formula until the stopping criterion is met:

[0103]

[0104] In the formula, It is an identifier of the iteration number, which is used to track or represent the variable of the current iteration round; Represents the learning rate, which is a hyperparameter that determines the size of the step taken in the gradient direction; express The gradient of Represents the current vector value; Represents the updated vector value;

[0105] In step 204, the stopping criterion is that the change of the comprehensive objective function value is less than the change threshold. When the change of the comprehensive objective function value during the iteration process is less than the change threshold, it indicates that the function value has stabilized and the iteration is stopped. The change threshold is used to determine whether the change of the comprehensive objective function value is small enough, so that it is considered that the algorithm has converged or is close to convergence.

[0106] Step 205: Calculate the current elution efficiency using a formula, and optimize the elution efficiency based on the calculation result; wherein the elution efficiency calculation formula is: , where It indicates the elution efficiency. denote the flow rate and volume of the eluent, respectively. represents the elution amount of the target perfluorinated compound, represents the total amount of adsorbed target perfluorinated compounds; the result of optimizing elution efficiency is expressed as:

[0107]

[0108] In the formula, represents the optimized eluent flow rate and volume; represents the feasible domain of elution conditions; is an operator used to return the parameter value that maximizes the elution efficiency, that is, to find the best elution conditions (composed of flow rate and volume) to maximize the elution efficiency;

[0109] Step 206: Design a prediction model whose output is the input parameter vector The function of ;in, represents any combination of enrichment efficiency and purity, Contains optimized parameters adsorption conditions and elution efficiency;

[0110] Step 207: Select an initial input parameter vector As the basic condition, represents the total number of parameters in the input parameter vector;

[0111] Step 208: For each input parameter , perform the following steps, where Indicates the index of the input parameter:

[0112] J1. Fix all other parameters In its corresponding basic conditions The value of Represents the index of all other parameters;

[0113] J2. Input parameters The single variable change is denoted as ,in, Indicates the total number of changes of the parameter;

[0114] J3. For each , calculate the corresponding output

[0115] ,in, Indicated in On the input parameters, The parameter value after the change is An index indicating the number of times the parameter has changed;

[0116] Step 209: Draw a sensitivity diagram to perform sensitivity analysis, that is, Scatter plot or curve graph;

[0117] Step 210: Determine the output The parameters with the greatest impact, and the resulting positive or negative impact;

[0118] Step 211: Based on the results of the sensitivity analysis, select the output Significantly increase (or reach the desired target) the parameter value as the optimal separation condition, thereby providing better quality test samples for analytical testing;

[0119] In step 211, the optimal separation conditions are to optimize the process of separating and purifying the target perfluorinated compound from the water sample, aiming to improve the enrichment efficiency and purity of the target perfluorinated compound and ensure the effectiveness of the separation and purification process so as to facilitate subsequent detection of whether the concentration of the target perfluorinated compound exceeds the standard after purification, and the optimal separation conditions may be a combination of multiple parameters rather than the optimal value of a single parameter.

[0120] See also Figure 1 The present invention provides a method for detecting lake perfluorinated compound pollution. In the step 3, the target perfluorinated compound is separated from the water sample under the optimal separation conditions, and the separated target perfluorinated compound is detected and analyzed. According to the detected and analyzed target perfluorinated compound, whether its concentration exceeds the standard is judged, and the adjustment measures are taken according to the judgment result. The steps include:

[0121] Step 301: Use a high-precision analytical instrument to detect the pollution concentration of the separated target perfluorinated compound to determine the actual pollution concentration of the target perfluorinated compound. ;

[0122] Step 302: Setting the pollution concentration threshold ;

[0123] Step 303: The concentration of the detected target perfluorinated compound Perform comparative analysis, where the comparative analysis formula is specifically:

[0124]

[0125] In the formula, It represents the pollution degree assessment index; It is an adjustment factor used to control the sensitivity of the pollution index to changes in concentration; To adjust the parameters, it is used to introduce the exponential influence of the degree of deviation of pollution concentration from the average concentration, so that the concentration that deviates extremely from the average value contributes more to the pollution index; It represents the average pollution concentration in the collection area; Indicates the standard deviation corresponding to the pollution concentration, which is used to standardize the concentration deviation; represents the number of other factors affecting pollution assessment considered, Represents an index; Indicates The weight of each factor; Indicates The value of factors that affect pollution assessment;

[0126] Step 304: When evaluating the pollution level, if the pollution level evaluation index , it is determined that the target perfluorinated compound concentration exceeds the standard, and the collection area corresponding to the target perfluorinated compound concentration is marked;

[0127] Step 305: For sampling frequencies where the pollution level exceeds the standard, the pollution level assessment index Adjust the sampling frequency of this area, that is , where represents the adjusted sampling frequency, represents the initial sampling frequency, is a control parameter used to control the amplitude and speed of the sampling frequency increase, and are greater than 0, when the pollution degree assessment index When the value of is large, due to , The growth rate will be faster than the pollution assessment index itself, resulting in a more substantial increase in the sampling frequency;

[0128] Step 306: Combine the acquired , adjust the subsequent monitoring plan of the collection area to ensure that water samples can be collected for testing more frequently when pollution is serious.

[0129] In the embodiment of the present invention, by setting the sampling time interval, the continuity and representativeness of the data are ensured, which helps to capture the impact of the dynamic changes of environmental factors on the concentration of perfluorinated compounds in water samples. The collection area is systematized by two-dimensional grid division, which is convenient for spatial analysis of data and helps to identify pollution trends later. The water sample data and environmental data are integrated through data integration to provide comprehensive background information for analysis. By optimizing the adsorption conditions and elution efficiency of the target perfluorinated compounds, the enrichment efficiency is improved, so that the optimized adsorption conditions can more effectively capture the target perfluorinated compounds and reduce losses. At the same time, optimizing the elution efficiency helps to reduce impurity interference and improve the target compound. The purity of the substance is determined by using a sensitivity analysis method to ensure separation under optimal conditions, improve the accuracy and reliability of the analysis, separate the target perfluorinated compounds from the water sample under the optimal separation conditions, detect and analyze the separated target perfluorinated compounds, obtain the pollution level assessment index, and assess the concentration level of the target perfluorinated compounds. By judging whether the concentration of the target perfluorinated compounds after detection and analysis exceeds the standard, when the pollution level assessment index exceeds the threshold, it is automatically determined that the concentration of the target perfluorinated compounds exceeds the standard, and the sampling frequency of the area is adjusted. This dynamic adjustment mechanism can ensure that the monitoring frequency is increased when the pollution is serious, thereby more effectively controlling the pollution. In summary, the examples of the present invention involve data processing, comprehensive analysis, and intelligent optimization decision-making to solve the technical problems of insufficient accuracy of water sampling and detection and analysis for water resource management in existing solutions. In actual situations, more data and contextual information may be required to make specific decisions and optimization plans.

[0130] In addition, the formulas involved in the above are all calculated by removing dimensions and taking their numerical values. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The proportional coefficient in the formula and the various preset thresholds in the analysis process are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data; the size of the proportional coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the proportional coefficient depends on the amount of sample data and the preliminary setting of the corresponding processing coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0131] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically based on the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0132] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0133] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0135] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0136] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0137] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0138] Finally: The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for detecting perfluorinated compound pollution in lakes, characterized in that: Step 1: Set the sampling time interval, divide the collection area into two-dimensional grids, and integrate the water sample data with the environmental data to form a complete data set; The process of setting the sampling time interval, dividing the sampling area into two-dimensional grids, and integrating the water sample data with the environmental data to form a complete data set includes: Set the sampling time interval to Δt; Divide the acquisition area into two-dimensional grids according to its shape and size, i.e., M×N grids; each grid (x r ,y r ) represents a potential collection location, x and y represent the positions of the grid points in the east-west direction and the north-south direction, respectively. The collection area is the lake, M represents the number of grids in the east-west direction, and N represents the number of grids in the north-south direction; The coordinates of the grid points are expressed as: xr = xmin +(r-1)·Δx y r =y min +(r-1)·Δy In the formula, x min ,y min represents the coordinates of the lower left corner of the acquisition area or any selected starting point, Δx and Δy represent the width of the grid in the east-west and north-south directions respectively; r represents the index; Collecting water samples in the collection area in combination with the preset time interval and the divided two-dimensional grid; Obtain water sample data and environmental data, and mark them as D respectively wat , D env ; Among them, water sample data D wat is a collection of multiple water samples, each of which contains the sampling time t c , sampling position (x c ,y c ) and water sample physical and chemical property parameters w c ,Right now D wat ={(t c ,x c ,y c ,w c )|c=1,2,...,C}, and C represents the total number of water samples; environmental data D env is a set of multiple time points, each time point t l Corresponding to a set of environmental parameters e l , that is, D env ={(t l ,e l )l=1,2,...,L}, and L represents the total number of environmental parameters; Integrate water sample data with environmental data; the specific process of integration is as follows: For each water sample (t c ,x c ,y c ,w c ), matching the environmental parameter e that is closest to the time l ; Define the time difference function δ(t c ,t l )=|t c -t l |, and determine such that δ(t c ,t l(c) )The smallest l(c), that is, l(c) = argmint c -t l |; where l(c) is a function representing the time matching index, which is used to map the index c of the water sample to the index l of the environmental parameter; Using the selected time matching index l(c), the water sample data are associated with the environmental data and an integrated dataset D is generated. int , the dataset contains the complete environmental parameters of each water sample and its corresponding time point, namely D int ={t c ,x c ,y c ,w c ,e l(c) |c=1,2,...,C}; Step 2: Optimize the adsorption conditions and elution efficiency of the target perfluorinated compound, and use the sensitivity analysis method to obtain the optimal separation conditions based on the optimized adsorption conditions and elution efficiency; The process of optimizing the adsorption conditions and elution efficiency of the target perfluorinated compound in step 2 and obtaining the optimal separation conditions by using a sensitivity analysis method in combination with the optimized adsorption conditions and elution efficiency includes: From the integrated dataset D int The features that affect the adsorption conditions are selected as input variables; The adsorption condition is defined as the vector U = (w c ,e l ,t con ), where t con Indicates contact time; The comprehensive objective function F(U) is used to measure the enrichment effect and purity under the preset adsorption conditions: F(U)=α·Eff(U)+β·Pur(U) In the formula, α and β represent weight coefficients, and α+β=1, which is used to adjust the relative importance of enrichment efficiency and purity; Eff represents enrichment efficiency; Pur ​​represents purity; Update the value of vector U by iterative formula until the stopping criterion is met: IN b+1 =U b +η▽F(U b ) Where b is the identifier of the iteration number, which is used to track or represent the variable of the current iteration round; η represents the learning rate, which is a hyperparameter that determines the size of the step taken in the gradient direction; ▽F(U b ) indicates F(U b )’s gradient; U b Indicates the current vector U value; U b+1 Represents the updated vector U value; The stopping criterion is that the change of the comprehensive objective function value is less than the change threshold. When the change of the comprehensive objective function value during the iteration process is less than the change threshold, it indicates that the function value has stabilized and the iteration is stopped. The current elution efficiency is calculated using a formula, and the elution efficiency is optimized based on the calculation result; wherein, the elution efficiency calculation formula is: In the formula, EE represents the elution efficiency, v and V represent the flow rate and volume of the eluent, respectively, CA represents the elution amount of the target perfluorinated compound, and AT represents the total amount of the adsorbed target perfluorinated compound; the result of optimizing the elution efficiency is expressed as: (v',V')=argmax (v,V)∈B EE(v,V) Where (v', V') represents the optimized eluent flow rate and volume; B represents the feasible domain of elution conditions; argmax is an operator used to return the parameter value that maximizes the elution efficiency; Design a prediction model whose output Y is the input parameter vector X = (a1, a2, ..., a n ), that is, Y=f(X); wherein Y represents any combination of enrichment efficiency and purity, and X includes the optimized parameters adsorption conditions and elution efficiency; Choose an initial input parameter vector As the basic condition, where n represents the total number of parameters in the input parameter vector; For each input parameter a i (i=1,2,…,n), perform the following steps, where i represents the index of the input parameter: J1, fix all other parameters a j (j≠i) in its corresponding basic condition The value of , where j represents the index of all other parameters; J2, input parameter a i The single variable change is denoted as Where m represents the total number of changes of the parameter; J3. For each Calculate the corresponding output in, It represents the parameter value after k changes on the i-th input parameter, where k represents the index of the number of parameter changes; Draw a sensitivity diagram for sensitivity analysis, that is ( Y k ) scatter plot or curve graph; Determine the parameters that have the greatest impact on output Y, and whether the impact is positive or negative; Based on the results of the sensitivity analysis, the parameter value that leads to a significant increase in output Y is selected as the optimal separation condition; Step 3: Separate the target perfluorinated compounds from the water sample under the optimal separation conditions, detect and analyze the separated target perfluorinated compounds, determine whether their concentration exceeds the standard based on the detected and analyzed target perfluorinated compounds, and take adjustment measures based on the determination results; The process of step 3, detecting and analyzing the separated target perfluorinated compounds, judging whether the concentration of the target perfluorinated compounds after detection and analysis exceeds the standard, and taking adjustment measures according to the judgment results, includes: Use high-precision analytical instruments to detect the pollution concentration of the separated target perfluorinated compounds and determine the actual pollution concentration C of the target perfluorinated compounds. meas ; Set the pollution concentration threshold C thre ; The concentration of the detected target perfluorinated compound C meas Perform comparative analysis, where the comparative analysis formula is specifically: Where I represents the pollution degree assessment index; ε is the adjustment factor, which is used to control the sensitivity of the pollution index to changes in concentration; K is the adjustment parameter, which is used to introduce the exponential influence of the degree of deviation of the pollution concentration from the average concentration, so that the concentration that deviates from the average value contributes more to the pollution index; C avg Represents the average pollution concentration in the collection area; C std It represents the standard deviation corresponding to the pollution concentration, which is used to standardize the concentration deviation; H represents the number of other factors affecting the pollution assessment, and h represents the index; W h represents the weight of the hth factor; A h represents the value of the hth factor affecting pollution assessment; When evaluating the pollution degree, if the pollution degree evaluation index I ≥ 1, it is determined that the target perfluorinated compound concentration exceeds the standard, and the collection area corresponding to the target perfluorinated compound concentration is marked; For sampling frequencies where the pollution level exceeds the standard, the sampling frequency of the area is adjusted according to the pollution level assessment index I, that is, T new =T0·(1+μ·(I γ -1)), where T new represents the adjusted sampling frequency, T0 represents the initial sampling frequency, μ and γ are control parameters used to control the amplitude and speed of the sampling frequency increase, and μ and γ are both greater than 0; Combined with the obtained T new , adjust the subsequent monitoring plan of the collection area.

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