Soil pollution condition sampling monitoring data analysis method

Abstract

The invention discloses a soil pollution condition sampling monitoring data analysis method, which belongs to the technical field of data processing, and comprises the following steps of: classifying sampling points according to a latest sampling analysis result, and dividing a region according to the aggregation of high-risk sampling points; the next sampling time is further adjusted according to the average value of the comprehensive change rates of the high-risk sampling points in the inspection sub-regions, so that high-frequency detection of regions with large change amplitude and abnormal pollution is ensured, timely monitoring of soil pollution of the corresponding regions is realized, sampling analysis resources can be reasonably utilized, and the detection efficiency is improved. And abnormal conditions can be found in time. In addition, compared with a traditional large-scale troubleshooting mode for the polluted area, the method has the advantages that the position of the pollution source can be locked more quickly by analyzing the concentration change distribution of different pollutants, the troubleshooting space of the pollution source is effectively and quickly reduced by analyzing the components of the pollutants, and the pollution source can be quickly locked.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and specifically relates to a method for analyzing soil pollution status sampling and monitoring data. Background Art

[0002] Soil pollutants can be roughly divided into two categories: inorganic pollutants and organic pollutants. Inorganic pollutants mainly include acids, alkalis, heavy metals, salts, compounds of radioactive elements cesium and strontium, compounds containing arsenic, selenium, and fluorine. Organic pollutants mainly include organic pesticides, phenols, cyanide, petroleum, synthetic detergents, 3,4-benzopyrene, and harmful microorganisms brought by urban sewage, sludge, and manure. When there are too many harmful substances in the soil, exceeding the self-purification capacity of the soil, it will cause changes in the composition, structure, and function of the soil, and microbial activity will be inhibited. Harmful substances or their decomposition products gradually accumulate in the soil and are indirectly absorbed by the human body through "soil → plant → human body" or through "soil → water → human body", reaching a level that endangers human health. This is soil pollution.

[0003] Soil pollution is easy to accumulate, difficult to control, and has strong concealment and hysteresis. After discovering abnormal soil pollution, it takes a long time to investigate and sample to lock the source of pollution, which leads to further deepening and spread of pollution. In order to solve the above problems, a method is provided to timely discover abnormal soil pollution conditions and quickly trace and lock the source of pollution. The present invention provides the following technical solutions. Summary of the invention

[0004] The purpose of the present invention is to provide a soil pollution status sampling monitoring data analysis method to solve the problems in the prior art that soil pollution has serious hysteresis, affects the timely discovery of pollution anomalies and has low efficiency in locking pollution sources.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A soil pollution status sampling monitoring data analysis method comprises the following steps:

[0007] For a sampling point, the concentration data of a pollutant at the sampling point is obtained in time series, and the abnormal change point and the time when the abnormal change occurs are obtained;

[0008] The abnormal change point refers to the position where the concentration of the corresponding pollutant changes by a value b greater than a preset change value threshold by;

[0009] For the same pollutant, a set of sampling points that produce abnormal change points at the same time is obtained, and the sampling points in the sampling point set are divided into several change groups according to the change value b. The change value b of the sampling points in each change group is in the same value range, and the value ranges corresponding to different change groups do not overlap;

[0010] The area covered by each variation group is obtained, and the area covered by the variation group with the largest value and at least e sampling points is marked as the source area of ​​the pollutant; e is a preset value,

[0011] The source areas corresponding to other pollutants at the same time are obtained in sequence, the source areas of each pollutant are analyzed, and the pollutant source areas of each sampling point are obtained;

[0012] For a sampling point, when it is in one or more pollutant source areas at the same time, the corresponding pollutant is used as the pollution component of the sampling point, so as to obtain all the pollution components of the sampling point;

[0013] Sampling points that contain the same pollutant components or whose pollutant component similarity exceeds the preset proportional coefficient θ2 are regarded as a traceability group. When tracing the source of pollution, the pollution source is focused on checking within the range corresponding to the sampling points covered by each traceability group.

[0014] As a further solution of the present invention, the spatial distribution of each change group and the change value b of each change group are displayed on a human-computer interaction device.

[0015] As a further solution of the present invention, when tracing the source of pollution, firstly a list of pollutants corresponding to different pollution sources is established;

[0016] After the tracing team is determined, the pollution source is investigated and determined according to the pollutant components corresponding to the tracing team within the corresponding range of the sampling points covered by the tracing team.

[0017] As a further solution of the present invention, a method for screening and determining the pollution source according to the pollutant components corresponding to the source tracing team is as follows:

[0018] S1. Obtain the pollutant components corresponding to the source tracing team and the list of pollutants contained in each pollution source in the corresponding area;

[0019] S2. Compare the pollutant components corresponding to the source tracing group with the pollutant lists contained in each pollution source, obtain the pollutant type overlap between the pollutant components corresponding to the source tracing group and the pollutant lists contained in each pollution source, and investigate each corresponding pollution source in descending order of overlap;

[0020] S3. After the first pollution source is found, the distinguished pollutant components between the pollution source and the pollutant components corresponding to the source tracing group are obtained, and the pollutant type overlap between the distinguished pollutant component set and the pollutant list contained in each pollution source is obtained, and then the corresponding pollution sources are checked in descending order of overlap;

[0021] S4. Repeat step S3 until all pollution sources are found.

[0022] As a further solution of the present invention, the sampling frequency is also adjusted, specifically:

[0023] Step 1: Set up sampling points in the area to be monitored and obtain the concentration of different pollutants at each sampling point;

[0024] Step 2: Set a test period, the duration of the test period is T = t*k, k is a positive integer greater than or equal to 1, and t is the time interval between two samplings;

[0025] Obtain the concentration change difference c1 of a pollutant at the beginning and end of a test cycle and the concentration c2 of the pollutant at the beginning of the test cycle, and calculate the first change rate c of the corresponding pollutant in a test cycle according to c=c1 / c2;

[0026] Obtain the sum cz of the first change rates c of all pollutants at a sampling point in a test period, where cz is recorded as the comprehensive change rate of the sampling point in the corresponding test period;

[0027] Step 3: Calculate the comprehensive change rate cz corresponding to each sampling point in a test cycle. When the corresponding comprehensive change rate cz is greater than the preset change rate threshold cy, the corresponding sampling point is considered to be a high-risk sampling point.

[0028] Delineate inspection sub-areas based on the distribution of high-risk sampling points;

[0029] The area of ​​a test sub-region is larger than the preset area threshold M, and the ratio of the number of high-risk sampling points or non-high-risk sampling points contained therein to the number of all sampling points in the test sub-region is larger than the preset proportional coefficient θ1;

[0030] For an inspection sub-area that mainly contains high-risk sampling points, the average value czp of the comprehensive change rate cz of each high-risk sampling point is calculated, and the next sampling time of the inspection sub-area is determined based on czp. Specifically, the larger the average value czp is, the smaller the time interval t between two samplings is.

[0031] As a further solution of the present invention, the interval time t between two samplings is calculated according to the formula t=1 / (k1*czp), where k1 is a preset positive coefficient.

[0032] As a further solution of the present invention, the sampling point density of the inspection sub-area mainly containing high-risk sampling points is adjusted according to the average value czp. Specifically, the larger the average value czp, the greater the sampling point density.

[0033] Beneficial effects of the present invention:

[0034] 1. The present invention classifies the sampling points according to the most recent sampling and analysis results, divides the areas according to the clustering of high-risk sampling points, and further adjusts the next sampling time according to the average value of the comprehensive change rate of high-risk sampling points in each inspection sub-area, thereby ensuring high-frequency detection of areas with large changes and abnormal pollution, and realizing timely monitoring of soil pollution in corresponding areas. For areas with stable pollution status, the set sampling frequency is appropriately reduced or maintained, so that sampling and analysis resources can be reasonably utilized to ensure timely monitoring and discovery of abnormal conditions.

[0035] 2. Compared with the traditional method of large-scale investigation of polluted areas, the present invention can locate the location of pollution sources more quickly by analyzing the concentration change distribution of different pollutants, and can effectively and quickly reduce the investigation space of pollution sources by analyzing the pollutant components, which is conducive to quickly locking the pollution sources, thereby achieving rapid governance to reduce the further expansion of soil pollution and avoid further deepening of negative impacts. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] Figure 1 The present invention is a flow chart of a soil pollution status sampling and monitoring data analysis method. DETAILED DESCRIPTION

[0038] 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 described embodiments 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.

[0039] Embodiment 1

[0040] A soil pollution status sampling monitoring data analysis method, such as Figure 1 As shown, the following steps are included:

[0041] Step 1: Set up sampling points ai in the area to be monitored, analyze the soil at the sampling points, and obtain the pollutant concentration, where i ranges from 1 to n, and n is the number of sampling points;

[0042] Step 2: Set a test period, the duration of the test period is T = t*k, k is a positive integer greater than or equal to 1, and t is the time interval between two samplings;

[0043] Obtain the concentration change difference c1 of a pollutant at the beginning and end of a test cycle and the concentration c2 of the pollutant at the beginning of the test cycle, and calculate the first change rate c of the corresponding pollutant in a test cycle according to c=c1 / c2;

[0044] Calculate and obtain the sum cz of the first change rates c of all types of pollutants to be tested at a sampling point ai within a test period, and mark cz as the comprehensive change rate of the corresponding sampling point ai within a corresponding test period;

[0045] Step 3: Calculate the comprehensive change rate cz corresponding to each sampling point in a test cycle. When the corresponding comprehensive change rate cz is greater than the preset change rate threshold cy, the corresponding sampling point is considered to be a high-risk sampling point.

[0046] Obtain the distribution of each high-risk sampling point in the area to be monitored, and define the inspection sub-area according to the distribution of the high-risk sampling points;

[0047] For a test sub-region, its area should be greater than the preset area threshold M, and the ratio of the number of high-risk sampling points or non-high-risk sampling points contained therein to the number of all sampling points in the test sub-region should be greater than the preset proportional coefficient θ1;

[0048] For an inspection sub-area mainly containing high-risk sampling points, the average value czp of the comprehensive change rate cz of each high-risk sampling point is calculated, and the next sampling time of the inspection sub-area is determined according to czp. Specifically, the larger the average value czp is, the smaller the time interval t between two samplings is.

[0049] Specific examples are as follows:

[0050] The interval time t between two samplings is calculated according to the formula t=1 / (k1*czp), where k1 is a preset positive coefficient;

[0051] The present invention classifies sampling points according to the most recent sampling and analysis results, divides the area according to the clustering of high-risk sampling points, and further adjusts the next sampling time according to the average value of the comprehensive change rate of high-risk sampling points in each inspection sub-area, thereby ensuring high-frequency detection of areas with large changes and abnormal pollution, and realizing timely monitoring of soil pollution in corresponding areas. For areas with stable pollution status, the set sampling frequency is appropriately reduced or maintained, so that sampling and analysis resources can be reasonably utilized to ensure timely monitoring and discovery of abnormal conditions.

[0052] Preferably, the sampling point density of the inspection sub-area mainly containing high-risk sampling points can also be adjusted according to the average value czp. Specifically, the larger the average value czp is, the greater the sampling point density is.

[0053] Embodiment 2

[0054] For a sampling point ai, the concentration data of a pollutant at the sampling point is obtained in time sequence, and the corresponding change curve q of the pollutant at the sampling point is established with time as the horizontal axis and concentration as the vertical axis;

[0055] Obtain the mutation point in the change curve q and the time when the mutation occurs (this time is generally determined as the sampling time, with a time accuracy of days);

[0056] The abnormal change point refers to the position in the change curve q where the concentration of the corresponding pollutant at the sampling point ai changes by a value b greater than a preset change value threshold by;

[0057] For the same pollutant, a set of sampling points that produce abnormal change points at the same time is obtained, and the sampling points in the sampling point set are divided into several change groups according to the change value b. The change value b of the sampling points in each change group is in the same value range, and the value ranges corresponding to different change groups do not overlap;

[0058] For example, five value ranges are set, namely d1-d2, d2-d3, d3-d4, d4-d5, d5-d6, each range includes the former but not the latter, and d1<d2<d3<d4<d5<d6;

[0059] Obtain the area covered by each variation group, and mark the area covered by the variation group with the largest corresponding value containing at least e sampling points as the source area of ​​the pollutant;

[0060] The setting of e is related to the average area corresponding to each sampling point (i.e. the ratio of the total area of ​​the monitored area to the number of sampling points). Generally, in order to ensure the accuracy of the results, the value of e is 5;

[0061] Preferably, the spatial distribution of each change group and the change value b of each change group can be displayed on the human-computer interaction device, so as to intuitively display the diffusion law of the corresponding pollutant;

[0062] In the later governance process, the diffusion law can be used as a reference for targeted pollution treatment to reduce the impact of soil pollution.

[0063] The source areas corresponding to other pollutants at the same time are obtained in sequence, the source areas of each pollutant are analyzed, and the pollutant source areas of each sampling point are obtained;

[0064] For a sampling point, when it is in one or more pollutant source areas at the same time, the corresponding pollutant is used as the pollution component of the sampling point, so as to obtain all the pollution components of the sampling point;

[0065] The sampling points that contain the same pollution components or the pollution components whose similarity exceeds the preset proportional coefficient θ2 are regarded as a traceability group, and the spatial distribution of the sampling points contained in each traceability group is obtained.

[0066] When tracing the source of pollution, focus on investigating the pollution source within the range corresponding to the sampling points covered by each tracing team;

[0067] Preferably, a pollutant list corresponding to different pollution sources may be established first. The pollutant list may be established based on the local past experience in soil pollution monitoring, and may be further established in combination with the corresponding relationship between common pollution sources and pollutants.

[0068] After determining the traceability team, within the corresponding range of the sampling points covered by the traceability team, the pollution source is investigated and determined according to the pollutant components corresponding to the traceability team, thereby effectively reducing the investigation scope, improving the investigation efficiency, and reducing the negative impact of soil pollution.

[0069] Compared with the traditional method of large-scale investigation of polluted areas, the present invention can locate the location of pollution sources more quickly, and by analyzing the pollutant components, effectively and quickly reduce the investigation space of pollution sources, which is conducive to quickly locking the pollution sources, thereby achieving rapid governance to reduce the further expansion of soil pollution and avoid further deepening of negative impacts.

[0070] Embodiment 3

[0071] Based on Example 1, this example further describes how to identify the pollution source according to the pollutant components corresponding to the source tracing team, as follows:

[0072] S1. When investigating and determining the pollution source, obtain the pollutant components corresponding to the source tracing team and the list of pollutants contained in each pollution source in the corresponding area;

[0073] S2. Compare the pollutant components corresponding to the source tracing group with the pollutant lists contained in each pollution source, obtain the pollutant type overlap between the pollutant components corresponding to the source tracing group and the pollutant lists contained in each pollution source, and investigate each corresponding pollution source in descending order of overlap;

[0074] S3. After the first pollution source is found, the distinguished pollutant components between the pollution source and the pollutant components corresponding to the source tracing group are obtained, and the pollutant type overlap between the distinguished pollutant component set and the pollutant list contained in each pollution source is obtained, and then the corresponding pollution sources are checked in descending order of overlap;

[0075] S4. Repeat step S3 until all pollution sources are found.

[0076] It should be noted that the pollutants in the pollutant list mentioned here are all pollutants that will be detected during the sampling and monitoring process;

[0077] Since there may be two or more pollution sources in the same area, when this happens, the above method can be used to conduct targeted inspections and improve inspection efficiency.

[0078] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A soil pollution status sampling monitoring data analysis method, characterized in that: The steps include: For a sampling point, the concentration data of a pollutant at the sampling point is obtained in time series, and the abnormal change point and the time when the abnormal change occurs are obtained; The abnormal change point refers to the position where the concentration of the corresponding pollutant changes by a value b greater than a preset change value threshold by; For the same pollutant, a set of sampling points that produce abnormal change points at the same time is obtained, and the sampling points in the sampling point set are divided into several change groups according to the change value b. The change value b of the sampling points in each change group is in the same value range, and the value ranges corresponding to different change groups do not overlap; The area covered by each variation group is obtained, and the area covered by the variation group with the largest value and at least e sampling points is marked as the source area of ​​the pollutant; e is a preset value, The source areas corresponding to other pollutants at the same time are obtained in sequence, the source areas of each pollutant are analyzed, and the pollutant source areas of each sampling point are obtained; For a sampling point, when it is in one or more pollutant source areas at the same time, the corresponding pollutant is used as the pollution component of the sampling point, so as to obtain all the pollution components of the sampling point; Sampling points that contain the same pollutant components or whose pollutant component similarity exceeds the preset proportional coefficient θ2 are regarded as a traceability group. When tracing the source of pollution, the pollution source is focused on checking within the range corresponding to the sampling points covered by each traceability group.

2. A soil pollution status sampling monitoring data analysis method according to claim 1, characterized in that: The spatial distribution of each change group and the change value b of each change group are displayed on the human-computer interaction device.

3. A soil pollution status sampling monitoring data analysis method according to claim 1, characterized in that: When tracing the source of pollution, first establish a list of pollutants corresponding to different pollution sources; After the tracing team is determined, the pollution source is investigated and determined according to the pollutant components corresponding to the tracing team within the corresponding range of the sampling points covered by the tracing team.

4. A soil pollution status sampling monitoring data analysis method according to claim 3, characterized in that: The method for identifying the pollution source according to the pollutant components corresponding to the source tracing team is as follows: S1. Obtain the pollutant components corresponding to the source tracing team and the list of pollutants contained in each pollution source in the corresponding area; S2. Compare the pollutant components corresponding to the source tracing group with the pollutant lists contained in each pollution source, obtain the pollutant type overlap between the pollutant components corresponding to the source tracing group and the pollutant lists contained in each pollution source, and investigate each corresponding pollution source in descending order of overlap; S3. After the first pollution source is found, the distinguished pollutant components between the pollution source and the pollutant components corresponding to the source tracing group are obtained, and the pollutant type overlap between the distinguished pollutant component set and the pollutant list contained in each pollution source is obtained, and then the corresponding pollution sources are checked in descending order of overlap; S4. Repeat step S3 until all pollution sources are found.

5. The soil pollution status sampling monitoring data analysis method according to claim 1 is characterized in that: It also includes adjusting the sampling frequency, specifically: Step 1: Set up sampling points in the area to be monitored and obtain the concentration of different pollutants at each sampling point; Step 2: Set a test period, the duration of the test period is T = t*k, k is a positive integer greater than or equal to 1, and t is the time interval between two samplings; Obtain the concentration change difference c1 of a pollutant at the beginning and end of a test cycle and the concentration c2 of the pollutant at the beginning of the test cycle, and calculate the first change rate c of the corresponding pollutant in a test cycle according to c=c1 / c2; Obtain the sum cz of the first change rates c of all pollutants at a sampling point in a test period, where cz is recorded as the comprehensive change rate of the sampling point in the corresponding test period; Step 3: Calculate the comprehensive change rate cz corresponding to each sampling point in a test cycle. When the corresponding comprehensive change rate cz is greater than the preset change rate threshold cy, the corresponding sampling point is considered to be a high-risk sampling point. Delineate inspection sub-areas based on the distribution of high-risk sampling points; The area of ​​a test sub-region is larger than the preset area threshold M, and the ratio of the number of high-risk sampling points or non-high-risk sampling points contained therein to the number of all sampling points in the test sub-region is larger than the preset proportional coefficient θ1; For an inspection sub-area that mainly contains high-risk sampling points, the average value czp of the comprehensive change rate cz of each high-risk sampling point is calculated, and the next sampling time of the inspection sub-area is determined based on czp. Specifically, the larger the average value czp is, the smaller the time interval t between two samplings is.

6. A soil pollution status sampling monitoring data analysis method according to claim 5, characterized in that: The interval time t between two samplings is calculated according to the formula t=1 / (k1*czp), where k1 is a preset positive coefficient.

7. A soil pollution status sampling monitoring data analysis method according to claim 5, characterized in that: The sampling point density of the inspection sub-area mainly containing high-risk sampling points is adjusted according to the average value czp. Specifically, the larger the average value czp, the greater the sampling point density.

Images