Soil environment quality monitoring method based on data analysis

Abstract

The invention relates to the technical field of soil monitoring, and particularly discloses a soil environment quality monitoring method based on data analysis, which comprises the steps of soil environment parameter monitoring and acquisition, index parameter preprocessing, index weight calculation, soil environment quality analysis, soil pollution correlation analysis and soil ecological risk assessment. A complete system from monitoring data acquisition to quality evaluation, pollution analysis and ecological risk early warning is formed, all the steps are correlated and progressive layer by layer, powerful support is provided for scientific management of the soil environment, the monitoring data are used for quality evaluation, a basis is provided for pollution analysis and ecological risk evaluation, and the method is suitable for popularization and application. And the quality evaluation result also guides the selection of remediation treatment measures, and the risk early warning guides the further monitoring and research direction, so that the systematic and dynamic management of the soil environment can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of soil monitoring, and in particular to a soil environmental quality monitoring method based on data analysis. Background Art

[0002] With the acceleration of industrialization and urbanization, soil pollution is becoming increasingly serious, and accurate and efficient monitoring of soil environmental quality has become crucial. Traditional soil environmental quality monitoring methods often rely on laboratory analysis, which has disadvantages such as long sampling cycle, complex analysis process, and untimely data acquisition, making it difficult to meet the needs of real-time and dynamic monitoring of soil environmental quality. For example, in agricultural production, changes in soil fertility will directly affect the growth and yield of crops, but traditional monitoring methods cannot provide farmers with dynamic information on soil nutrients in a timely manner, resulting in inaccurate fertilization decisions, which may cause waste of resources or worsen soil pollution. In industrial pollution sites, due to the lack of rapid and effective monitoring methods, it is difficult to detect the spread of soil pollution in a timely manner, increasing the potential threat to the surrounding ecological environment and human health.

[0003] Existing soil environmental quality monitoring technology has deficiencies in many aspects. On the one hand, the monitoring indicators are relatively simple, mostly focusing on the chemical properties of the soil, such as conventional heavy metal content and pH, while paying less attention to the physical properties and biological indicators of the soil, ignoring the integrity and complexity of the soil ecosystem. For example, judging the degree of soil pollution based solely on the heavy metal content in the soil may not be able to fully reflect the soil environmental quality status, because physical indicators such as soil texture and porosity will affect the migration and transformation of heavy metals and their bioavailability, thereby affecting the function of the soil ecosystem; on the other hand, the data processing and analysis methods are relatively simple, lacking in systematicity and scientificity. In terms of indicator weight determination and comprehensive evaluation, subjective assignment methods are often used, lacking objective basis, resulting in inaccurate and unreliable evaluation results; moreover, in the monitoring process, the handling of outliers is not rigorous enough and is easily affected by extreme values, which greatly reduces the authenticity and representativeness of the monitoring data.

[0004] Therefore, a soil environmental quality monitoring method based on data analysis is urgently needed. Summary of the invention

[0005] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides a soil environmental quality monitoring method based on data analysis to solve the above-mentioned technical defects.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a soil environmental quality monitoring method based on data analysis, comprising the following steps:

[0007] Step 1: Monitoring and collecting soil environmental parameters: various monitoring instruments are used to monitor and collect the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment in real time, so as to obtain the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0008] Step 2: Preprocessing of indicator parameters: Use the box plot method to identify abnormal values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, replace the identified abnormal values ​​with the mean, and perform standardized calculations on various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, and obtain the standardized values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, which are recorded as

[0009] Step 3: Calculation of indicator weights: First, establish a standardized indicator data matrix for each monitoring point in each quality monitoring area corresponding to the soil environment. Then according to the formula Calculate the information entropy e of the jth monitoring and analysis indicator j Finally, according to the formula Calculate the weight coefficient w corresponding to each monitoring analysis index in each monitoring point in each quality monitoring area of ​​the soil environment j ;

[0010] Step 4: Soil environment quality analysis: Obtain the weight coefficient w corresponding to each monitoring and analysis indicator in each monitoring point in each quality monitoring area of ​​the soil environment j Standardized values ​​of various monitoring and analysis indicators at each monitoring point in each quality monitoring area corresponding to the soil environment The above parameters are calculated according to the formula Calculate the soil environment quality comprehensive coefficient TQ of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0011] According to the soil environment quality standards and monitoring and analysis purposes, the interval levels of the soil environment corresponding to each monitoring point in each quality monitoring area are pre-set, and the corresponding soil environment remediation and management measures are implemented according to the interval level division of the soil environment corresponding to each monitoring point in each quality monitoring area;

[0012] Step 5. Soil pollution correlation analysis: The pollutant load of each monitoring point in each quality monitoring area corresponding to the soil environment is obtained by multiplying the three parameters of pollutant concentration, soil bulk density and soil layer thickness at each monitoring point in each quality monitoring area corresponding to the soil environment;

[0013] Then, several sampling points are set around each monitoring point in each quality monitoring area corresponding to the soil environment, and the distances from the sampling points to the monitoring points are recorded, which are recorded as x. h, and obtain the pollutant load of several sampling points, denoted as f h , where h = 1, 2, ..., g, h represents the number of sampling points, g represents the total number of sampling points, and the average distance of several sampling points from the monitoring point and the average pollutant load are calculated, which are recorded as and

[0014] Step 6. Soil ecological risk assessment: By selecting two sampling points at different distances from the pollution source, setting the skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years, soil exposure frequency, adult weight and time of contact with carcinogens, the pollutant load, skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years and soil exposure frequency of sampling points at different distances are multiplied, and the product is divided by the product of adult weight and time of contact with carcinogens. Finally, the soil ecological risk coefficient of sampling points at different distances is obtained. If the soil ecological risk coefficient of the short distance is greater than that of the long distance, it means that the farther the distance from the pollution source, the lower the soil ecological risk. Otherwise, it means that there are other pollution sources or special transmission mechanisms, and an abnormal result warning is issued. At the same time, additional monitoring points are added near the sampling point for further soil environmental quality monitoring and analysis.

[0015] Furthermore, in the step one, the monitoring and analysis indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include physical indicators and chemical indicators. The physical indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include soil bulk density, soil porosity, soil texture, soil moisture content and soil temperature. The chemical indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include soil pH value, organic matter content, nutrient content, cation exchange capacity and heavy metal content.

[0016] Furthermore, in the step 2, i=1, 2, ..., n, i represents the number of each monitoring point, n represents the total number of the detection point numbers, j=1, 2, ..., m, j represents the number of each analysis indicator, and m represents the total number of the analysis indicator numbers.

[0017] Furthermore, in the step 2, the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment are divided into positive indicators and negative indicators according to their benefits and disadvantages to the soil environment quality, and the standard deviation values ​​of the positive indicators and negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment are calculated respectively. The specific calculation method is as follows:

[0018] For the positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the normalized value of positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0019] For the negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the standardized value of negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment.

[0020] Furthermore, in the step 2, if the data point exceeds the interquartile range of 1.5 times the upper and lower quartiles of the box plot, the data of the parameter is determined to be an outlier, wherein the positive indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators whose larger values ​​indicate better soil environment quality, such as organic matter content; the negative indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators whose larger values ​​indicate worse soil environment quality, such as heavy metal content.

[0021] Furthermore, in step three, the smaller the information entropy is, the greater the amount of information provided by the monitoring and analysis indicator is, and the greater the weight is.

[0022] Furthermore, in the step 4, if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is greater than 0.8, it is classified as an excellent grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.6-0.8, it is classified as a defective grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.4-0.6, it is classified as a light pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.2-0.4, it is classified as a moderate pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is less than 0.2, it is classified as a heavy pollution grade; according to the interval grade division of each monitoring point in each quality monitoring area corresponding to the soil environment, corresponding soil environment remediation and management measures are performed.

[0023] Furthermore, in step 5, the soil pollution correlation coefficient of each monitoring point in each quality monitoring area corresponding to the soil environment is calculated as follows:

[0024] The relationship between the distance from the pollution source and the pollutant load is fitted by a linear regression equation, and the formula Indicates, where a is the intercept and b is the slope, and the values ​​of a and b are determined by the least squares method;

[0025] According to the formula The soil pollution correlation coefficient R of each monitoring point in each quality monitoring area corresponding to the soil environment is calculated. When R>0, it indicates a positive correlation. As the distance from the pollution source increases, the pollutant load also increases. When R<0, it indicates a negative correlation. As the distance from the pollution source increases, the pollutant load also decreases. If R=0, it means that there is no linear correlation between the pollutant load and the distance from the pollution source.

[0026] Beneficial effects of the present invention:

[0027] 1. In the present invention, various physical and chemical indicators of the soil environment are monitored and collected in real time, covering soil bulk density, porosity, texture, water content and temperature. Chemical indicators include pH value, organic matter, nutrients, cation exchange capacity and heavy metal content. This comprehensive parameter monitoring can fully describe the soil environmental quality status and avoid the one-sidedness of soil quality assessment due to single parameter monitoring. By simultaneously monitoring soil texture and nutrient content, it is possible to more accurately judge whether the soil is suitable for specific plant growth, because soil texture affects the retention and release of nutrients. In the indicator parameter preprocessing stage, the box plot method is used to identify outliers and replace them with the mean, which helps to reduce the interference of abnormal data on subsequent analysis. At the same time, the indicators are standardized and calculated to distinguish positive and negative indicators, so that indicators of different properties and dimensions can be compared and analyzed under the same standard. The standardized soil organic matter content (positive indicator) and heavy metal content (negative indicator) can more reasonably participate in the comprehensive quality assessment to ensure the accuracy of the assessment results.

[0028] 2. By calculating the indicator weights, it is possible to assign reasonable weight coefficients to each monitoring and analysis indicator based on the amount of information it provides, fully considering the characteristics of the indicator itself and avoiding excessive interference from subjective factors. The soil environmental quality comprehensive coefficient TQ is calculated by combining the weight coefficient and the standardized indicator value, and then different interval levels are divided, such as excellent, defective, lightly polluted, moderately polluted and heavily polluted. This provides a scientific and quantitative assessment result for soil environmental quality, which is helpful to take targeted soil remediation and management measures of different degrees. In addition, the assessment system can be adjusted according to different soil environmental quality standards and monitoring and analysis purposes. In the soil quality assessment of agricultural land and construction land, different grade division standards and key focus indicators can be set respectively, so that the assessment results are more in line with actual application scenarios and management needs.

[0029] 3. The pollutant load of each monitoring point is calculated through chemical analysis, soil bulk density measurement and soil layer thickness selection, which can intuitively reflect the accumulation of pollutants in the soil. For areas that have been polluted by industry for a long time, calculating the pollutant load can help determine the severity of the pollution and provide basic data for subsequent pollution control. Further linear regression analysis of the pollutant load and the distance from the pollution source is performed, and the soil pollution correlation coefficient R is calculated. This can reveal the spatial distribution pattern of pollutants and determine the transmission trend of pollutants. When R is positive or negative and has different sizes, different pollution situations can be inferred. For example, R < 0 conforms to the general law of pollution diffusion, while R > 0 indicates that there may be special pollution sources or transmission mechanisms, which is helpful for in-depth research on the causes and processes of pollution.

[0030] 4. In the soil ecological risk assessment step, by setting multiple parameters related to human contact with soil, the soil ecological risk coefficients of sampling points at different distances are calculated. Through the risk assessment method based on actual exposure pathways and parameters, the soil ecological risk at different distances from the pollution source can be effectively judged. When the soil ecological risk coefficient at a short distance is greater than that at a long distance, it conforms to the normal risk distribution law; otherwise, abnormal situations can be discovered in time, early warnings can be issued, and additional monitoring points can be added for in-depth analysis, so as to take measures in advance to prevent soil pollution from causing greater harm to human health and the ecosystem. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present invention will be further described below in conjunction with the accompanying drawings.

[0032] Figure 1 The present invention is a flowchart of a method for monitoring soil environmental quality based on data analysis according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0034] As shown in the present invention and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list, and the method or device may also include other steps or elements.

[0035] Although the present invention has made various references to certain modules in the system according to an embodiment of the present invention, any number of different modules can be used and run on a user terminal and / or server. The modules are only illustrative, and different aspects of the system and method can use different modules.

[0036] The present invention uses a flow chart to illustrate the operations performed by the system according to an embodiment of the present invention. It should be understood that the preceding or following operations are not necessarily performed precisely in order. On the contrary, various steps may be processed in reverse order or simultaneously as required. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0037] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0038] Embodiment 1:

[0039] See also Figure 1 As shown, a soil environmental quality monitoring method based on data analysis includes the following steps:

[0040] Step 1: Monitoring and collecting soil environmental parameters: various monitoring instruments are used to monitor and collect the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment in real time, so as to obtain the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0041] Among them, the monitoring and analysis indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include physical indicators and chemical indicators. The physical indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include soil bulk density, soil porosity, soil texture, soil moisture content and soil temperature. The chemical indicators of the soil environment corresponding to each monitoring point in each quality monitoring area include soil pH value, organic matter content, nutrient content, cation exchange capacity and heavy metal content.

[0042] Step 2: Preprocessing of indicator parameters: Use the box plot method to identify abnormal values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, replace the identified abnormal values ​​with the mean, and perform standardized calculations on various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, and obtain the standardized values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, which are recorded as Where i = 1, 2, ..., n, i represents the number of each monitoring point, n represents the total number of each detection point number, j = 1, 2, ..., m, j represents the number of each analysis index, m represents the total number of each analysis index number;

[0043] Specifically, the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment are divided into positive indicators and negative indicators according to their benefits and disadvantages to the soil environment quality, and the standard deviation of the positive indicators and negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment is calculated respectively. The specific calculation method is as follows:

[0044] For the positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the normalized value of positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0045] For the negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the normalized value of negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0046] It should be noted that if the data point exceeds the interquartile range of 1.5 times the upper and lower quartiles of the box plot, the data of this parameter is judged to be an outlier. The positive indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators with larger values, indicating better soil environment quality, such as organic matter content; the negative indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators with larger values, indicating worse soil environment quality, such as heavy metal content.

[0047] Step 3: Calculation of indicator weights: First, establish a standardized indicator data matrix for each monitoring point in each quality monitoring area corresponding to the soil environment. Then according to the formula Calculate the information entropy e of the jth monitoring and analysis indicator j Finally, according to the formula Calculate the weight coefficient w corresponding to each monitoring analysis index in each monitoring point in each quality monitoring area of ​​the soil environment j ; Among them, the smaller the information entropy, the greater the amount of information provided by the monitoring and analysis indicator, and the greater the weight.

[0048] Step 4: Soil environment quality analysis: Obtain the weight coefficient w corresponding to each monitoring and analysis indicator in each monitoring point in each quality monitoring area of ​​the soil environment j Standardized values ​​of various monitoring and analysis indicators at each monitoring point in each quality monitoring area corresponding to the soil environment The above parameters are calculated according to the formula Calculate the soil environment quality comprehensive coefficient TQ of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0049] According to the soil environment quality standards and the purpose of monitoring and analysis, the interval grade of each monitoring point in each quality monitoring area corresponding to the soil environment is pre-set. Specifically, if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is greater than 0.8, it is classified as an excellent grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.6-0.8, it is classified as a defective grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.4-0.6, it is classified as a light pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.2-0.4, it is classified as a moderate pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is less than 0.2, it is classified as a heavy pollution grade. According to the interval grade division of each monitoring point in each quality monitoring area corresponding to the above-mentioned soil environment, corresponding soil environment restoration and control measures are implemented.

[0050] Step 5. Soil pollution related analysis: obtain the pollutant concentration of each monitoring point in each quality monitoring area corresponding to the soil environment through chemical analysis methods, obtain the soil bulk density of each monitoring point in each quality monitoring area corresponding to the soil environment through a soil bulk density meter, select the soil layer thickness of each monitoring point in each quality monitoring area corresponding to the soil environment according to the purpose of monitoring research, and finally multiply the three parameters of pollutant concentration, soil bulk density and soil layer thickness of each monitoring point in each quality monitoring area corresponding to the soil environment to obtain the pollutant load of each monitoring point in each quality monitoring area corresponding to the soil environment;

[0051] Then, several sampling points are set around each monitoring point in each quality monitoring area corresponding to the soil environment, and the distances from the sampling points to the monitoring points are recorded, which are recorded as x. h , and obtain the pollutant load of several sampling points, denoted as f h , where h = 1, 2, ..., g, h represents the number of sampling points, g represents the total number of sampling points, and the average distance of several sampling points from the monitoring point and the average pollutant load are calculated, which are recorded as and

[0052] The relationship between the distance from the pollution source and the pollutant load is fitted by a linear regression equation, and the formula Indicates, where a is the intercept and b is the slope, and the values ​​of a and b are determined by the least squares method;

[0053] According to the formula Calculate the soil pollution correlation coefficient R of each monitoring point in each quality monitoring area corresponding to the soil environment. When R>0, it indicates a positive correlation. As the distance from the pollution source increases, the pollutant load also increases. When R<0, it indicates a negative correlation. As the distance from the pollution source increases, the pollutant load also decreases. If R=0, it means that there is no linear correlation between the pollutant load and the distance from the pollution source.

[0054] Step 6. Soil ecological risk assessment: By selecting two sampling points at different distances from the pollution source, setting the skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years, soil exposure frequency, adult weight and time of contact with carcinogens, the pollutant load, skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years and soil exposure frequency of sampling points at different distances are multiplied, and the product is divided by the product of adult weight and time of contact with carcinogens. Finally, the soil ecological risk coefficient of sampling points at different distances is obtained. If the soil ecological risk coefficient of the short distance is greater than that of the long distance, it means that the farther the distance from the pollution source, the lower the soil ecological risk. Otherwise, it means that there are other pollution sources or special transmission mechanisms, and an abnormal result warning is issued. At the same time, additional monitoring points are added near the sampling point for further soil environmental quality monitoring and analysis.

[0055] In a specific embodiment, the present invention collects and monitors a variety of physical and chemical indicators of the soil environment in real time, including soil bulk density, porosity, texture, water content and temperature. Chemical indicators include pH value, organic matter, nutrients, cation exchange capacity and heavy metal content. This comprehensive parameter monitoring can fully describe the soil environmental quality status and avoid the one-sidedness of soil quality assessment due to single parameter monitoring. By simultaneously monitoring soil texture and nutrient content, it is possible to more accurately determine whether the soil is suitable for the growth of specific plants, because soil texture affects the retention and release of nutrients.

[0056] In the indicator parameter preprocessing stage, the box plot method is used to identify outliers and replace them with the mean, which helps to reduce the interference of abnormal data on subsequent analysis. At the same time, the indicators are standardized and calculated to distinguish positive and negative indicators, so that indicators of different properties and dimensions can be compared and analyzed under the same standard. The standardized soil organic matter content (positive indicator) and heavy metal content (negative indicator) can participate in the comprehensive quality assessment more reasonably to ensure the accuracy of the assessment results.

[0057] By calculating the indicator weights, we can assign reasonable weight coefficients to the indicators according to the amount of information they provide, taking full account of the characteristics of the indicators themselves and avoiding excessive interference from subjective factors. We can calculate the soil environmental quality comprehensive coefficient TQ by combining the weight coefficients and the standardized indicator values, and then divide the soil into different interval levels, such as excellent, defective, lightly polluted, moderately polluted and heavily polluted. This provides a scientific and quantitative assessment result for soil environmental quality, which helps to take targeted soil remediation measures of different degrees. The assessment system can be adjusted according to different soil environmental quality standards and monitoring and analysis purposes. In the soil quality assessment of agricultural land and construction land, different grade classification standards and key indicators can be set to make the assessment results more in line with actual application scenarios and management needs.

[0058] Through chemical analysis, soil bulk density measurement and soil layer thickness selection, the pollutant load of each monitoring point is calculated, which can intuitively reflect the accumulation of pollutants in the soil. For areas that have been polluted by industry for a long time, the calculation of pollutant load can help determine the severity of pollution and provide basic data for subsequent pollution control. Further linear regression analysis of pollutant load and distance from pollution source is performed, and the soil pollution correlation coefficient R is calculated, which can reveal the spatial distribution law of pollutants and judge the propagation trend of pollutants. When the positive and negative values ​​and sizes of R are different, different pollution situations can be inferred. For example, R < 0 conforms to the general law of pollution diffusion, while R > 0 indicates that there may be special pollution sources or transmission mechanisms, which is helpful for in-depth research on the causes and processes of pollution.

[0059] Finally, in the soil ecological risk assessment step, by setting multiple parameters related to human contact with soil, the soil ecological risk coefficients of sampling points at different distances are calculated. Through the risk assessment method based on actual exposure pathways and parameters, the soil ecological risk at different locations from the pollution source can be effectively judged. When the soil ecological risk coefficient at a short distance is greater than that at a long distance, it conforms to the normal risk distribution law; otherwise, abnormal situations can be discovered in time, early warnings can be issued, and additional monitoring points can be added for in-depth analysis, so as to take measures in advance to prevent soil pollution from causing greater harm to human health and the ecosystem;

[0060] In summary, the entire plan forms a complete system from monitoring data collection to quality assessment, pollution analysis and ecological risk warning. The various steps are interrelated and progressive, providing strong support for the scientific management of the soil environment. The monitoring data is not only used for quality assessment, but also provides a basis for pollution analysis and ecological risk assessment. The quality assessment results guide the selection of restoration and control measures, and risk warnings guide further monitoring and research directions, which helps to achieve systematic and dynamic management of the soil environment.

[0061] The above formulas are all dimensionless and numerical calculations. The formula is a formula that is obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The size of the coefficient is to quantify each parameter to obtain a specific value. Regarding the size of the coefficient, it is acceptable as long as it does not affect the proportional relationship between the parameter and the quantified value.

[0062] In addition, those skilled in the art will appreciate that various aspects of the present invention may be illustrated and described by a number of patentable categories or situations, including any new and useful process, machine, product or combination of substances, or any new and useful improvements thereto. Accordingly, various aspects of the present invention may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may all be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". In addition, various aspects of the present invention may be represented as a computer product located in one or more computer-readable media, which includes computer-readable program code.

[0063] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. It should also be understood that terms such as those defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology and should not be interpreted in an idealized or extremely formal sense, unless explicitly defined as such herein.

[0064] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A soil environmental quality monitoring method based on data analysis, characterized in that: The following steps are involved: Step 1: Monitoring and collecting soil environmental parameters: various monitoring instruments are used to monitor and collect the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment in real time, so as to obtain the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment; Step 2: Preprocessing of indicator parameters: Use the box plot method to identify abnormal values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, replace the identified abnormal values ​​with the mean, and perform standardized calculations on various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, and obtain the standardized values ​​of various monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, which are recorded as Step 3: Calculation of indicator weights: First, establish a standardized indicator data matrix for each monitoring point in each quality monitoring area corresponding to the soil environment. Then according to the formula Calculate the information entropy e of the jth monitoring and analysis indicator j Finally, according to the formula Calculate the weight coefficient w corresponding to each monitoring and analysis indicator in each monitoring point in each quality monitoring area of ​​the soil environment j ; Step 4: Soil environment quality analysis: Obtain the weight coefficient w corresponding to each monitoring and analysis indicator in each monitoring point in each quality monitoring area of ​​the soil environment j Standardized values ​​of various monitoring and analysis indicators at each monitoring point in each quality monitoring area corresponding to the soil environment The above parameters are calculated according to the formula Calculate the soil environment quality comprehensive coefficient TQ of each monitoring point in each quality monitoring area corresponding to the soil environment; According to the soil environment quality standards and monitoring and analysis purposes, the interval levels of the soil environment corresponding to each monitoring point in each quality monitoring area are pre-set, and the corresponding soil environment remediation and management measures are implemented according to the interval level division of the soil environment corresponding to each monitoring point in each quality monitoring area; Step 5. Soil pollution correlation analysis: The pollutant load of each monitoring point in each quality monitoring area corresponding to the soil environment is obtained by multiplying the three parameters of pollutant concentration, soil bulk density and soil layer thickness at each monitoring point in each quality monitoring area corresponding to the soil environment; Then, several sampling points are set around each monitoring point in each quality monitoring area corresponding to the soil environment, and the distances from the sampling points to the monitoring points are recorded, which are recorded as x. h , and obtain the pollutant load of several sampling points, denoted as f h , where h = 1, 2, ..., g, h represents the number of sampling points, g represents the total number of sampling points, and the average distance of several sampling points from the monitoring point and the average pollutant load are calculated, which are recorded as and According to the formula Calculate the soil pollution correlation coefficient R of each monitoring point in each quality monitoring area corresponding to the soil environment; Step 6. Soil ecological risk assessment: By selecting two sampling points at different distances from the pollution source, setting the skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years, soil exposure frequency, adult weight and time of contact with carcinogens, the pollutant load, skin contact area, soil adsorption coefficient to skin, skin absorption coefficient, soil exposure years and soil exposure frequency of sampling points at different distances are multiplied, and the product is divided by the product of adult weight and time of contact with carcinogens. Finally, the soil ecological risk coefficient of sampling points at different distances is obtained. If the soil ecological risk coefficient of the short distance is greater than that of the long distance, it means that the farther the distance from the pollution source, the lower the soil ecological risk. Otherwise, it means that there are other pollution sources or special transmission mechanisms, and an abnormal result warning is issued. At the same time, additional monitoring points are added near the sampling point for further soil environmental quality monitoring and analysis.

2. The soil environmental quality monitoring method based on data analysis according to claim 1, characterized in that: In the step 1, the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment include physical indicators and chemical indicators. The physical indicators of each monitoring point in each quality monitoring area corresponding to the soil environment include soil bulk density, soil porosity, soil texture, soil moisture content and soil temperature. The chemical indicators of each monitoring point in each quality monitoring area corresponding to the soil environment include soil pH value, organic matter content, nutrient content, cation exchange capacity and heavy metal content.

3. The soil environmental quality monitoring method based on data analysis according to claim 1, characterized in that: In the step 2, i=1, 2, ..., n, i represents the number of each monitoring point, n represents the total number of the detection point numbers, j=1, 2, ..., m, j represents the number of each analysis indicator, and m represents the total number of the analysis indicator numbers.

4. The soil environmental quality monitoring method based on data analysis according to claim 1 is characterized in that: In the step 2, the monitoring and analysis indicators of each monitoring point in each quality monitoring area corresponding to the soil environment are divided into positive indicators and negative indicators according to the benefits and disadvantages to the soil environment quality, and the standard deviation values ​​of the positive indicators and negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment are calculated respectively. The specific calculation method is as follows: For the positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the normalized value of positive indicators of each monitoring point in each quality monitoring area corresponding to the soil environment; For the negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment, the formula Calculate the standardized value of negative indicators of each monitoring point in each quality monitoring area corresponding to the soil environment.

5. The soil environmental quality monitoring method based on data analysis according to claim 1 is characterized in that: In the step 2, if the data point exceeds the interquartile range of 1.5 times the upper and lower quartiles of the box plot, the data of the parameter is determined to be an outlier, wherein the positive indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators whose larger values ​​indicate better soil environment quality, such as organic matter content; the negative indicators of the soil environment corresponding to each monitoring point in each quality monitoring area refer to those indicators whose larger values ​​indicate worse soil environment quality, such as heavy metal content.

6. A soil environmental quality monitoring method based on data analysis according to claim 1, characterized in that: In step three, the smaller the information entropy is, the greater the amount of information provided by the monitoring and analysis indicator is, and the greater the weight is.

7. The soil environmental quality monitoring method based on data analysis according to claim 1 is characterized in that: In the step 4, if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is greater than 0.8, it is classified as an excellent grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.6-0.8, it is classified as a defective grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.4-0.6, it is classified as a light pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is between 0.2-0.4, it is classified as a moderate pollution grade; if the comprehensive coefficient of soil environment quality of each monitoring point in each quality monitoring area corresponding to the soil environment is less than 0.2, it is classified as a heavy pollution grade. According to the interval grade division of each monitoring point in each quality monitoring area corresponding to the soil environment, corresponding soil environment remediation and control measures are performed.

8. The soil environmental quality monitoring method based on data analysis according to claim 1 is characterized in that: In step 5, the soil pollution correlation coefficient of each monitoring point in each quality monitoring area corresponding to the soil environment is calculated as follows: The relationship between the distance from the pollution source and the pollutant load is fitted by a linear regression equation, and the formula Indicates, where a is the intercept and b is the slope, and the values ​​of a and b are determined by the least squares method; When R>0, it indicates a positive correlation. As the distance from the pollution source increases, the pollutant load also increases. When R<0, it indicates a negative correlation. As the distance from the pollution source increases, the pollutant load also decreases. If R=0, it means that there is no linear correlation between the pollutant load and the distance from the pollution source.

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