CN111521754A - Preliminary investigation and stationing method for soil pollution in coking enterprise site - Google Patents

Preliminary investigation and stationing method for soil pollution in coking enterprise site Download PDF

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CN111521754A
CN111521754A CN202010319831.0A CN202010319831A CN111521754A CN 111521754 A CN111521754 A CN 111521754A CN 202010319831 A CN202010319831 A CN 202010319831A CN 111521754 A CN111521754 A CN 111521754A
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万小铭
顾高铨
雷梅
曾伟斌
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Abstract

The invention relates to the technical field of soil pollution analysis, and provides a preliminary investigation and stationing method for soil pollution in a coking enterprise site, which comprises the following steps: determining the number range of main pollutants and sampling points based on the concentration of the pollutants according to the technological process, the pollutant diffusion model and the sampling point distribution scale specification of a coking enterprise; establishing a sampling cost model of the pollutants according to the sampling necessary cost, and determining the sampling point number range based on the cost; establishing a model of 'sampling point number-interpolation prediction precision' of the pollutants by using an interpolation simulation method, and determining a sampling point number range based on precision; adjusting the number range of the sampling points based on the pollutant concentration, the cost and the precision; and (3) analyzing the sampling effect by combining the sampling scale, the soil heavy metal characteristics and the local space variability, and determining the number n of sampling points. The invention provides a definite sampling number calculation method, which can better control the sampling cost.

Description

Preliminary investigation and stationing method for soil pollution in coking enterprise site
Technical Field
The invention relates to the technical field of soil pollution analysis, in particular to a preliminary investigation and stationing method for soil pollution in a coking enterprise site.
Background
In the existing site survey, the design of a preliminary sampling scheme is mainly based on the standard requirements of the technical guide for site environment survey, and based on the existing data collection and analysis, site survey and personnel interview, the layout of preliminary sampling points, the determination of sampling quantity, the determination of a sample collection method and the like are carried out, and the main flow is shown in fig. 1. The analysis of the preliminary sampling data has very important guiding value for detailed sampling analysis and pollution risk assessment. Therefore, the reasonable design of the preliminary sampling scheme can improve the accuracy of the site pollution model and plays a key role in starting and stopping in the site investigation process.
In the current research and guidance, common sampling point distribution methods include a judgment point distribution method, a random point distribution method, a partition point distribution method and a system point distribution method. Under the guidance of existing point placement methods, guidelines dictate that the number of samples required should be determined based on the survey objective and the type of contaminant present. In the current investigation, a diffusion model of pollutants is combined, an inverse distance weighting method, a kriging method, a radial basis function method, a multiple regression method, a simulated annealing method and the like are utilized to carry out related sample point quantity distribution, an optimal method is determined by comparing various interpolation methods, and the method is widely applied to guidance of sampling design. However, the existing site preliminary investigation sampling point arrangement technology still has the following problems:
1. qualitative is greater than quantitative. In the existing site preliminary survey sampling point arrangement technology, the guide does not give detailed guidance to point arrangement, the operability is not provided, the number of samples depends on survey targets and the types of pollution, certain subjective will and qualitative analysis exist, and model specifications for quantifying the number of samples are lacked.
2. There is a lack of cost control. The existing research mainly focuses on the research of the operational processes of optimizing the sampling space, improving the sampling precision, improving the sampling efficiency and the like, a clear sampling cost-prediction precision model is not provided, and the cost performance of the preliminary investigation sampling technology cannot be improved based on the sampling benefit.
Disclosure of Invention
The invention aims to provide a method for preliminarily investigating and distributing soil pollution on a coking enterprise site, which aims to solve the technical problems in the prior art.
In order to achieve the purpose, the invention adopts the technical scheme that: a soil pollution preliminary investigation and point distribution method in a coking enterprise site is characterized by comprising the following steps:
the method comprises the following steps: determining the number range of main pollutants and sampling points based on the concentration of the pollutants according to the technological process, the pollutant diffusion model and the sampling point distribution scale specification of a coking enterprise;
step two: establishing a sampling cost model of the pollutants according to the sampling necessary cost, and determining the sampling point number range based on the cost;
step three: establishing a model of 'sampling point number-interpolation prediction precision' of the pollutants by using an interpolation simulation method, and determining a sampling point number range based on precision;
step four: adjusting the number range of the sampling points based on the pollutant concentration, the cost and the precision;
step five: and (3) removing sampling points which do not meet the requirements by combining the sampling scale, the soil heavy metal characteristics and the local space variability, analyzing the sampling effect, and determining the number n of the sampling points.
Optionally, the first step includes:
determining main pollutants according to the process flow of a coking enterprise, wherein the number of point pollution sources, linear pollution sources, area pollution sources and bulk pollution sources is n respectively1、n2、n3、n4；
Establishing a diffusion model of the main pollutants according to the formula (1):
Figure BDA0002460917770000021
wherein Q represents the contaminant concentration at a certain location X over a certain period of time, QP、qL、qA、qVRespectively represents the concentration of the diffusion point, line, surface and body pollutants at the X position, HP、HL、HA、HVRespectively showing the effective source heights of a point pollution source, a linear pollution source, an area pollution source and a body pollution source;
according to a formula (2), calculating the number N1 of critical sampling points based on the concentration of the pollutants according to the concentration of the screening values in the national standard GB36600-2018, wherein the number range of the sampling points based on the concentration of the pollutants is that N is not more than N1:
N1＝S/Sdimension(2)
Wherein S represents the area of the region where Q reaches the concentration of the selected value, and SDimensionIndicating the sampling scale specified by the national standard GB/T36200-2018.
Optionally, the diffusion model of the main pollutants is calculated according to a continuous point source diffusion formula (3), a continuous surface source diffusion formula (4), a continuous line source diffusion formula (5) and a continuous source diffusion formula (6) of the atmospheric diffusion model of pollutants:
Figure BDA0002460917770000031
Figure BDA0002460917770000032
Figure BDA0002460917770000033
Figure BDA0002460917770000034
wherein x, y, z represent the three-dimensional position coordinates of the contamination source, QP、QL、QA、QVRespectively representing the concentrations of a pollution source, a linear pollution source, a surface pollution source and a body pollution source at a certain time period, u represents the wind speed, sigma represents a diffusion parameter, and L represents0Indicating the length of the line source of contamination.
Optionally, the sampling necessary cost in the second step includes a pollutant analysis cost and a sampling instrument cost, and then the second step includes:
according to the formula (7), calculating the sampling cost f of the main pollutants through various instruments and test fees required in the sampling process:
f＝fM(x1,x2,...,xn)+fT(y1,y2,...,yn) (7)
wherein f isMRepresents the total cost of use of each type of apparatus, x1、x2、...xnRespectively representing different instruments fTRepresents the total cost of testing, y, for each sample1、y2、...ynRespectively represent different sample test indexes, fTProportional to the number of sampling points;
and (3) calculating the critical sampling point number N2 based on the cost according to the expense quota M and the condition that M is more than or equal to f (x), wherein the sampling point number range based on the cost is N which is less than or equal to N2.
Optionally, the third step includes:
selecting an interpolation prediction method based on the existing survey data to carry out pollution rate prediction analysis;
calculating a prediction error rate by taking the prediction error rate as an indication of interpolation prediction precision, wherein the prediction error rate is the difference between the predicted pollution rate and the assumed pollution rate/the assumed pollution rate;
carrying out data fitting analysis on the 'number of sampling points-interpolation prediction precision' to obtain a fitting equation F (n);
and according to the required prediction precision P, calculating the critical sampling point number N3 based on the precision from 100-P to F (N), wherein the sampling point number range based on the precision is N to N3.
Optionally, the interpolation prediction method is an inverse distance weighting method.
Optionally, the fitting equation f (n) is a power law distribution function f (n) ═ cn-a-1Wherein c and a are fixed constants.
Optionally, in the fourth step, when adjusting the range of the number of sampling points, at least one of the following principles is followed:
under the condition that the cost model and the concentration model both meet the precision requirement, increasing the number of sampling points;
in the case of being limited by the cost model, if the cost cannot be increased, the maximum value of the number of sampling points is N2, otherwise, the number of sampling points is increased;
under the condition of being limited by the precision requirement, the number of sampling points meets the following conditions: the prediction accuracy can be improved while balancing the cost model and the diffusion model.
Optionally, the step five includes:
carrying out layout screening on sampling points according to sampling intervals, soil heavy metal characteristics and local spatial variability which influence interpolation precision, and eliminating sampling points of which the sampling intervals, the soil heavy metal characteristics or the spatial variability do not meet requirements;
and selecting pollution data of different numbers of sampling points to perform interpolation prediction, analyzing the relation between the prediction result of the pollution area and the number of the sampling points, and reducing the number of the sampling points under the condition of ensuring that the change rate of the prediction result meets a specific condition.
Optionally, the rejection rate of the sampling points is 20%, and the specific condition is: the rate of change of rejection/prediction is > 1.
The invention has the beneficial effects that: selecting an inverse distance weighting method, carrying out predictive analysis on an interpolation result of the inspection data, selecting a power law function to fit a basic function of 'sampling point quantity-prediction precision' to obtain a reasonable 'sampling point quantity-prediction precision' relation model; the required sampling point number range is obtained by combining the sampling number range obtained by the pollution source diffusion model and the cost model with the fitting curve of the relation model of the sampling point number-prediction precision, the problems that definite sampling number is not quantitatively given and quantitative definite sampling cost is not provided in the prior art are solved on the basis of combining the prior art and standard limitation, the sampling cost is better controlled on the premise of keeping the prediction precision, and the cost performance of preliminary investigation sampling design is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flow chart of a site survey in the prior art.
Fig. 2 is a flowchart of a method for preliminary investigation and point placement of soil pollution at a site of a coking enterprise according to an embodiment of the present invention.
FIG. 3 is a schematic diagram of a process line of a coke plant according to an embodiment of the present invention.
Fig. 4 is a scatter diagram of the relationship between the number of sampling points and the prediction error rate according to the embodiment of the present invention.
Fig. 5 is a schematic diagram of a selectable range of sampling numbers according to an embodiment of the present invention.
Fig. 6 is a graph showing predicted comparison of Pb contamination at different numbers of sampling points according to the embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment provides a method for primarily surveying and stationing soil pollution on a coking enterprise site, which comprises the following steps:
the method comprises the following steps: determining the number range of main pollutants and sampling points based on the concentration of the pollutants according to the technological process, the pollutant diffusion model and the sampling point distribution scale specification of a coking enterprise;
step two: establishing a sampling cost model of the pollutants according to the sampling necessary cost, and determining the sampling point number range based on the cost;
step three: establishing a model of 'sampling point number-interpolation prediction precision' of the pollutants by using an interpolation simulation method, and determining a sampling point number range based on precision;
step four: adjusting the number range of the sampling points based on the pollutant concentration, the cost and the precision;
step five: and (3) removing sampling points which do not meet the requirements by combining the sampling scale, the soil heavy metal characteristics and the local space variability, analyzing the sampling effect, and determining the number n of the sampling points.
The core idea of the invention is mainly directed to the preliminary sampling distribution of coking enterprises. The steps are described in detail below with reference to the example of a Fujie coke plant.
The area scale (68 hectares) of the Huifeng coke-oven plant and the sampling scale (30m x 30m, 50m x 50m, 100m x100m and the like), therefore, the technical scheme of the invention can be applied to the initial sampling distribution point of the on-production coke-oven plant with the floor area scale of about 10-200 hectares. Fig. 2 is a flowchart of a method for preliminary investigation and point placement of soil pollution at a site of a coking enterprise according to an embodiment of the present invention. As shown in fig. 2, the method comprises the steps of:
the method comprises the following steps: determining the number range of main pollutants and sampling points based on the concentration of the pollutants according to the technological process, the pollutant diffusion model and the sampling point distribution scale specification of a coking enterprise;
step two: establishing a sampling cost model of the pollutants according to the sampling necessary cost, and determining the sampling point number range based on the cost;
step three: establishing a model of 'sampling point number-interpolation prediction precision' of the pollutants by using an interpolation simulation method, and determining a sampling point number range based on precision;
step four: adjusting the number range of the sampling points based on the pollutant concentration, the cost and the precision;
step five: and (3) removing sampling points which do not meet the requirements by combining the sampling scale, the soil heavy metal characteristics and the local space variability, analyzing the sampling effect, and determining the number n of the sampling points.
Optionally, the first step includes:
according to the cokeDetermining main pollutants in the process flow of chemical enterprises, wherein the number of point pollution sources, linear pollution sources, area pollution sources and bulk pollution sources is n respectively1、n2、n3、n4；
Establishing a diffusion model of the main pollutants according to the formula (1):
Figure BDA0002460917770000071
wherein Q represents the contaminant concentration at a certain location X over a certain period of time, QP、qL、qA、qVRespectively represents the concentration of the diffusion point, line, surface and body pollutants at the X position, HP、HL、HA、HVRespectively showing the effective source heights of a point pollution source, a linear pollution source, an area pollution source and a body pollution source;
according to a formula (2), calculating the number N1 of critical sampling points based on the concentration of the pollutants according to the concentration of the screening values in the national standard GB36600-2018, wherein the number range of the sampling points based on the concentration of the pollutants is that N is not more than N1:
N1＝S/Sdimension(2)
Wherein S represents the area of the region where Q reaches the concentration of the selected value, and SDimensionIndicating the sampling scale specified by the national standard GB/T36200-2018.
Optionally, the diffusion model of the main pollutants is calculated according to a continuous point source diffusion formula (3), a continuous surface source diffusion formula (4), a continuous line source diffusion formula (5) and a continuous source diffusion formula (6) of the atmospheric diffusion model of pollutants:
Figure BDA0002460917770000072
Figure BDA0002460917770000073
Figure BDA0002460917770000074
Figure BDA0002460917770000075
wherein x, y, z represent the three-dimensional position coordinates of the contamination source, QP、QL、QA、QVRespectively representing the concentrations of a pollution source, a linear pollution source, a surface pollution source and a body pollution source at a certain time period, u represents the wind speed, sigma represents a diffusion parameter, and L represents0The length of the line pollution source is shown, and the effective source height can be calculated according to the national standard GB/T13201-91.
In the example of a Fuhui coke plant, FIG. 3 is a coke plant process diagram. According to the process flow and the emission characteristics, the pollution sources of the method comprise 7 continuous point pollution sources, 1 continuous surface pollution source and 1 continuous body pollution source, and the concentration Q can be calculated by the formula (1), the formula (3), the formula (5) and the formula (6).
Optionally, the sampling necessary cost in the second step includes a pollutant analysis cost and a sampling instrument cost, and then the second step includes:
according to the formula (7), calculating the sampling cost f of the main pollutants through various instruments and test fees required in the sampling process:
f＝fM(x1,x2,...,xn)+fT(y1,y2,...,yn) (7)
wherein f isMRepresents the total cost of use of each type of apparatus, x1、x2、...xnRespectively representing different instruments fTRepresents the total cost of testing, y, for each sample1、y2、...ynRespectively represent different sample test indexes, fTProportional to the number of sampling points;
and (3) calculating the critical sampling point number N2 based on the cost according to the expense quota M and the condition that M is more than or equal to f (x), wherein the sampling point number range based on the cost is N which is less than or equal to N2.
In the example of the hui-feng coke-oven plant, a sampling instrument is not used in the sampling process, 102 samples are collected in total, and according to different test indexes,comprises total heavy metal (￥ 80), effective state of heavy metal (￥ 80), physicochemical properties of soil (￥ 240), and organic compound content (￥ 2000) fT24.48 ten thousand yuan.
In the interpolation method of geostatistics, the interpolation precision has obvious positive correlation with soil heavy metal characteristics (variation coefficient), local spatial variability and interpolation model theoretical perfection. This further illustrates that soil sampling amount, various point intervals and interpolation models are the main reasons for influencing the pollution judgment accuracy. But with limited cost, the sampling of large samples is not practical. Therefore, according to the main factors influencing the pollution judgment accuracy, the sampling points are reasonably reduced, and a sampling point-prediction accuracy model is constructed, so that the method has very important significance. The specific implementation is divided into the following two parts: firstly, determining a relation model of prediction error and sampling point quantity; and II, judging the sampling prediction effect.
The first part of building a sampling point-prediction precision model is characterized in that a relation graph of sampling quantity and prediction accuracy is built.
Optionally, the third step includes:
selecting an interpolation prediction method based on the existing survey data to carry out pollution rate prediction analysis;
calculating a prediction error rate by taking the prediction error rate as an indication of interpolation prediction precision, wherein the prediction error rate is the difference between the predicted pollution rate and the assumed pollution rate/the assumed pollution rate;
carrying out data fitting analysis on the 'number of sampling points-interpolation prediction precision' to obtain a fitting equation F (n);
and according to the required prediction precision P, calculating the critical sampling point number N3 based on the precision from 100-P to F (N), wherein the sampling point number range based on the precision is N to N3.
Optionally, the interpolation prediction method is an inverse distance weighting method.
Optionally, the fitting equation f (n) is a power law distribution function f (n) ═ cn-a-1Wherein c and a are fixed constants.
In this embodiment, the error rate is used to perform the prediction accuracyAnd (4) showing. The error rate is calculated as follows: by selecting a suitable interpolation prediction method, the difference between the predicted pollution probability and the assumed pollution probability is calculated, and the predicted error rate is equal to the difference/assumed value. And (3) carrying out data fitting analysis on the 'quantity-precision' to obtain a fitting equation of the 'quantity-precision' data fitting analysis. In the embodiment, the existing survey data is used for simulation analysis, the number of sampling points and the error prediction rate data are obtained as shown in table 1, and a relation scatter diagram of the number of sampling points and the error prediction rate is obtained by plotting as shown in fig. 4. As can be roughly understood from fig. 4, the number of sample points and the interpolation prediction accuracy conform to the power law distribution function f (n) ═ cn-a-1Wherein c and a are fixed constants. The number of critical point samples N3 can be calculated from 100-P ≦ F (N) depending on the required accuracy P.
Fitting analysis is carried out on the data in the table 1, and the fitting equation is obtained as follows: f (n) ═ 2156.88 · n-1.02. Therefore, when the number of sampling points is in the range of 0-100, the prediction error rate is rapidly reduced from 100% to about 20%; when the number of the sampling points is within the range of 100-200, the prediction error rate is reduced from 20% to about 5%; when the number of sampling points is more than 200, the variation amplitude of the prediction error rate is extremely small. In this embodiment, if the cost is sufficient, the number of sampling points may be set to about 200 to ensure sufficient accuracy; otherwise, about 100 samples can be selected. Meanwhile, according to the fitting degree of the model and the actual data, it can be found that: when the number of samples is more than 70, the model prediction result basically has no deviation from the existing result.
TABLE 1 relationship between number of spots and prediction accuracy data (simulation for example, contamination rate of 10%)
Figure BDA0002460917770000101
Optionally, in the fourth step, when adjusting the range of the number of sampling points, at least one of the following principles is followed:
under the condition that the cost model and the concentration model both meet the precision requirement, increasing the number of sampling points;
in the case of being limited by the cost model, if the cost cannot be increased, the maximum value of the number of sampling points is N2, otherwise, the number of sampling points is increased;
under the condition of being limited by the precision requirement, the number of sampling points meets the following conditions: the prediction accuracy can be improved while balancing the cost model and the diffusion model.
The number range of the sampling points is adjusted based on the pollutant concentration, the cost and the precision. In the first step, the number of critical sampling points calculated based on the pollutant concentration is N1, and the number range of the sampling points is N1 or less; in the second step, the number of the critical sampling points obtained based on the cost calculation is N2, and the number range of the sampling points is N2; in the third step, the critical sampling point number obtained based on the precision calculation is N3, and the sampling point number range is N equal to or larger than N3. The required sampling number range can be obtained by integrating the 3 inequalities. Fig. 5 is a schematic diagram of a selectable range of sampling numbers according to an embodiment of the present invention. As shown in fig. 5, under the condition that the cost model and the concentration model can meet the accuracy requirement, the number of sampling points can be as large as possible; under the condition of being limited by the precision requirement, the number of sampling points should be as close as possible to the sampling numbers N1 and N2 specified by the concentration model and the cost model, so that the progress is ensured to be as close as possible to the precision requirement; in the case of being limited to the cost model, if the expense cannot be increased, the N2 calculated according to the cost model is sampled, and conversely, the sampling point can be increased.
The second step of constructing the "sampling point-prediction accuracy" model requires analysis of the sampling prediction effect.
Optionally, the step five includes:
carrying out layout screening on sampling points according to sampling intervals, soil heavy metal characteristics and local spatial variability which influence interpolation precision, and eliminating sampling points of which the sampling intervals, the soil heavy metal characteristics or the spatial variability do not meet requirements;
and selecting pollution data of different numbers of sampling points to perform interpolation prediction, analyzing the relation between the prediction result of the pollution area and the number of the sampling points, and reducing the number of the sampling points under the condition of ensuring that the change rate of the prediction result meets a specific condition.
Optionally, the rejection rate of the sampling points is 20%, and the specific condition is: the rate of change of rejection/prediction is > 1.
After the sampling quantity range is determined according to the model, the quantity of sampling points is selected, and distribution and screening of sampling points can be performed according to sampling intervals, soil heavy metal characteristics (coefficient of variation CV) and local space variability which influence interpolation precision. Based on the above influence factors, the sampling points with smaller sampling intervals, smaller CV and smaller spatial variability are removed. The heavy metal Pb pollution data of the soil of the sampling points of different numbers of the Huifeng coke-oven plants are selected for interpolation analysis, and FIG. 6 is a Pb pollution prediction comparison graph under the sampling points of different numbers provided by the embodiment of the invention. As shown in fig. 6, as the number of sampling points decreases, no significant difference in the prediction results occurs. Area calculation is carried out according to a Spatial Analysis tool of Arcgis, a 1.4-time background value is used as a judgment boundary value, the area occupation ratios of the polluted areas with the predicted pollutant concentration being more than 1.4-time background value are respectively 22.4%, 28.3% and 40.6%, and the corresponding sampling points are respectively 37%, 30 and 23. Table 2 shows the Pb pollution area ratio estimation and sampling point comparison data, and it can be seen from the data in table 2 that, with a rejection rate of about 20%, when data with small space and small variability is rejected, the pollution prediction area change rate is about 5%, and the rejection rate/change rate is greater than 1, which indicates that when a certain proportion of sampling points are rejected, the prediction effect is not linearly affected in equal proportion.
The embodiment can prove that after the sampling quantity range obtained by model prediction is adjusted, the quantity of sampling points can be further reduced (the quantity of reduction is about 20% of the original sampling points) under the condition of ensuring that the prediction accuracy is not greatly changed based on factors such as sampling intervals, soil heavy metal characteristics, local space variability and the like, so that higher sampling cost performance is achieved.
TABLE 2 area ratio estimation and sampling point comparison data of heavy metal Pb pollution area in soil
Figure BDA0002460917770000121
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. A soil pollution preliminary investigation and point distribution method in a coking enterprise site is characterized by comprising the following steps:
the method comprises the following steps: determining the number range of main pollutants and sampling points based on the concentration of the pollutants according to the technological process, the pollutant diffusion model and the sampling point distribution scale specification of a coking enterprise;
step two: establishing a sampling cost model of the pollutants according to the sampling necessary cost, and determining the sampling point number range based on the cost;
step three: establishing a model of 'sampling point number-interpolation prediction precision' of the pollutants by using an interpolation simulation method, and determining a sampling point number range based on precision;
step four: adjusting the number range of the sampling points based on the pollutant concentration, the cost and the precision;
step five: and (3) removing sampling points which do not meet the requirements by combining the sampling scale, the soil heavy metal characteristics and the local space variability, analyzing the sampling effect, and determining the number n of the sampling points.
2. The method for preliminary investigation and point placement of soil pollution at the site of coking enterprises according to claim 1, wherein the step one comprises the following steps:
determining main pollutants according to the process flow of a coking enterprise, wherein the number of point pollution sources, linear pollution sources, area pollution sources and bulk pollution sources is n respectively1、n2、n3、n4；
Establishing a diffusion model of the main pollutants according to the formula (1):
Figure FDA0002460917760000011
wherein Q represents the contaminant concentration at a certain location X over a certain period of time, QP、qL、qA、qVRespectively represents the concentration of the diffusion point, line, surface and body pollutants at the X position, HP、HL、HA、HVRespectively showing the effective source heights of a point pollution source, a linear pollution source, an area pollution source and a body pollution source;
according to a formula (2), calculating the number N1 of critical sampling points based on the concentration of the pollutants according to the concentration of the screening values in the national standard GB36600-2018, wherein the number range of the sampling points based on the concentration of the pollutants is that N is not more than N1:
N1＝S/Sdimension(2)
Wherein S represents the area of the region where Q reaches the concentration of the selected value, and SDimensionIndicating the sampling scale specified by the national standard GB/T36200-2018.
3. The method for preliminary investigation and distribution of soil pollution on the site of coking enterprises according to claim 2, wherein the diffusion model of the main pollutants is calculated according to a continuous point source diffusion formula (3), a continuous surface source diffusion formula (4), a continuous line source diffusion formula (5) and a continuous source diffusion formula (6) of the atmospheric diffusion model of pollutants:
Figure FDA0002460917760000021
Figure FDA0002460917760000022
Figure FDA0002460917760000023
Figure FDA0002460917760000024
wherein x, y and z represent contaminationThree-dimensional position coordinates of the source, QP、QL、QA、QVRespectively representing the concentrations of a pollution source, a linear pollution source, a surface pollution source and a body pollution source at a certain time period, u represents the wind speed, sigma represents a diffusion parameter, and L represents0Indicating the length of the line source of contamination.
4. The method for preliminary investigation and point placement of soil pollution at a coking enterprise site as claimed in claim 1, wherein the necessary sampling cost in the second step includes a pollutant analysis cost and a sampling instrument cost, and the second step includes:
according to the formula (7), calculating the sampling cost f of the main pollutants through various instruments and test fees required in the sampling process:
f＝fM(x1,x2,...,xn)+fT(y1,y2,...,yn) (7)
wherein f isMRepresents the total cost of use of each type of apparatus, x1、x2、...xnRespectively representing different instruments fTRepresents the total cost of testing, y, for each sample1、y2、...ynRespectively represent different sample test indexes, fTProportional to the number of sampling points;
and (3) calculating the critical sampling point number N2 based on the cost according to the expense quota M and the condition that M is more than or equal to f (x), wherein the sampling point number range based on the cost is N which is less than or equal to N2.
5. The method for preliminary investigation and point distribution of soil pollution on the site of coking enterprises in claim 1, wherein the third step comprises:
selecting an interpolation prediction method based on the existing survey data to carry out pollution rate prediction analysis;
calculating a prediction error rate by taking the prediction error rate as an indication of interpolation prediction precision, wherein the prediction error rate is the difference between the predicted pollution rate and the assumed pollution rate/the assumed pollution rate;
carrying out data fitting analysis on the 'number of sampling points-interpolation prediction precision' to obtain a fitting equation F (n);
and according to the required prediction precision P, calculating the critical sampling point number N3 based on the precision from 100-P to F (N), wherein the sampling point number range based on the precision is N to N3.
6. The method for preliminary investigation and stationing of soil pollution at the site of coking enterprises in claim 5, wherein the interpolation prediction method is an inverse distance weighting method.
7. The method for preliminary investigation and stationing of soil pollution at site of coking enterprise as claimed in claim 5, wherein said fitting equation F (n) is power law distribution function F (n) ═ cn-a-1Wherein c and a are fixed constants.
8. The method for preliminary investigation and distribution of soil pollution on the site of coking enterprises according to claim 1, wherein in the fourth step, when the number range of sampling points is adjusted, at least one of the following principles is followed:
under the condition that the cost model and the concentration model both meet the precision requirement, increasing the number of sampling points;
in the case of being limited by the cost model, if the cost cannot be increased, the maximum value of the number of sampling points is N2, otherwise, the number of sampling points is increased;
under the condition of being limited by the precision requirement, the number of sampling points meets the following conditions: the prediction accuracy can be improved while balancing the cost model and the diffusion model.
9. The method for preliminary investigation and point distribution of soil pollution on the site of coking enterprises in claim 1, wherein the fifth step comprises the following steps:
carrying out layout screening on sampling points according to sampling intervals, soil heavy metal characteristics and local spatial variability which influence interpolation precision, and eliminating sampling points of which the sampling intervals, the soil heavy metal characteristics or the spatial variability do not meet requirements;
and selecting pollution data of different numbers of sampling points to perform interpolation prediction, analyzing the relation between the prediction result of the pollution area and the number of the sampling points, and reducing the number of the sampling points under the condition of ensuring that the change rate of the prediction result meets a specific condition.
10. The method for preliminary investigation and stationing of soil pollution at the site of coking enterprises according to claim 9, wherein the rejection rate of sampling points is 20%, and the specific conditions are as follows: the rate of change of rejection/prediction is > 1.
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