CN111553588B - Method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil - Google Patents
Method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil Download PDFInfo
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Abstract
The invention discloses a method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil, which comprises the following steps: acquiring a soil background value of a mining area research area and heavy metal content, coordinate information and environmental influence factors of a plurality of sampling points; obtaining a heavy metal pollution characteristic value according to the content of the heavy metal; analyzing the heavy metal pollution characteristic values and the soil background values of a plurality of sampling points of various land utilization types to obtain the heavy metal pollution condition of the soil; and processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points of various land use types by using a space autoregressive analysis model to obtain the correlation between the heavy metal content and the environmental influence factors. By the scheme, reliable basis can be provided for heavy metal pollution research and influence factor analysis in the future, the pollution rule of the heavy metal in the mining area soil is disclosed, and supporting conditions are provided for decision makers in the aspects of mineral exploitation and heavy metal pollution management in the future.
Description
Technical Field
The invention belongs to the technical field of environment, and particularly relates to a method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil.
Background
The long-term stacking of mine waste rocks and tailings generated by mineral product collection, processing and other activities easily enables heavy metals contained in the mine waste rocks and tailings to continuously diffuse and migrate in soil bodies under the natural effects of surface runoff, rainwater leaching, wind and the like, and meanwhile, Pb, Zn, As and associated elements Cd, Cr and Cu in the tailings generated by mining the mineral deposits enter the soil through surface water scouring and rainwater leaching and are accumulated, so that the pollution of surrounding soil and water environment is caused. The main sources of heavy metals in the mining area soil are mine acid wastewater, dust and tailings. The soil is used as a medium for crops to live, the content or residual quantity of various pollutants in the soil and the pollution degree directly influence the quality and edible safety of the crops, and the accumulation of heavy metals in the soil can be absorbed by the negative electrode of the crops, so that potential risks are generated to the health of people through food chain indirect connection, the influence of the heavy metals on the soil in a mining area needs to be analyzed, and support conditions are provided for mining and heavy metal pollution management.
Disclosure of Invention
In order to solve the problems, the invention provides a method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil, which comprises the following steps: acquiring a soil background value of a mining area research area and heavy metal content, coordinate information and environmental influence factors of a plurality of sampling points, wherein the sampling points are sampling points for collecting mining area soil corresponding to various land utilization types, the land utilization types are land utilization types of the mining area research area, the environmental influence factors comprise natural factors and human factors, and the heavy metal content comprises: the content of various heavy metals; obtaining a heavy metal pollution characteristic value according to the heavy metal content, wherein the heavy metal pollution characteristic value comprises: mean, standard deviation, and coefficient of variation; analyzing the heavy metal pollution characteristic values and the soil background values of the plurality of sampling points of various land utilization types to obtain the heavy metal pollution condition of the soil; and processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points of various land use types by using a space autoregressive analysis model to obtain the correlation between the heavy metal content and the environmental influence factors.
In the analysis method as described above, optionally, the obtaining a characteristic value of heavy metal pollution according to the content of heavy metal includes: identifying and eliminating abnormal values in the obtained heavy metal content by adopting a box plot method, then carrying out K-S normal distribution test, and carrying out logarithmic transformation on data which are not in normal distribution until the data are in normal distribution; and calculating the characteristic value of the normally distributed data to obtain the heavy metal pollution characteristic value.
In the analysis method as described above, optionally, the analysis method further includes: and analyzing the correlation among the heavy metals in each land utilization type to obtain the homologous relation among the heavy metal elements and whether the composite pollution exists.
In the analysis method as described above, optionally, the analyzing the heavy metal pollution characteristic values and the soil background values of the plurality of sampling points to obtain the soil heavy metal pollution condition includes: judging whether the characteristic value of heavy metal pollution in various land utilization types is higher than a soil background value or not, and if so, determining that the heavy metal corresponding to the characteristic value of heavy metal pollution in the land utilization type is a primary pollutant; judging whether different land utilization types have the same primary pollutants, if so, comparing the heavy metal characteristic values corresponding to the primary pollutants in the different land utilization types to obtain the total pollution condition of the different land utilization types; and judging whether the variation coefficient in each land utilization type is higher than a preset variation coefficient threshold value, and if so, determining that the heavy metal pollution condition corresponding to the variation coefficient in the land utilization type is serious.
In the analysis method as described above, optionally, the heavy metal content comprises: ni content, Pb content, Cr content, Cu content, Zn content and Cd content; the land use types include: rice soil and vegetable soil; the natural factors include: organic matter, pH, slope, elevation, the human factors include: residential distance, river distance, and mine distance.
In the analysis method as described above, optionally, the processing, by using a spatial autoregressive analysis model, the heavy metal content, the coordinate information, and the environmental influence factor of the plurality of sampling points to obtain a correlation between the heavy metal content and the environmental influence factor includes: if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Cd, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial error model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Cu, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Ni, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Pb, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Zn, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; and if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Cr, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
two types of land use in a mine area research area: the method comprises the steps of taking rice soil and vegetable soil as research objects, analyzing the heavy metal pollution condition of the soil in a mining area, exploring the correlation between the heavy metal content in the soil and environmental influence factors by applying a space autoregressive analysis model, finding out the heavy metal pollution rule and trying to analyze the possible causes of the heavy metal pollution rule. The research result can provide reliable basis for the research of heavy metal pollution and the analysis of the influence factors thereof in the future, simultaneously reveal the pollution rule of the heavy metal in the mining area soil, and provide support conditions for decision makers in the aspects of mineral exploitation and heavy metal pollution management in the future.
Drawings
Fig. 1 is a schematic flow chart of a method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention provides a method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil, including the following steps:
The mining area research area takes the place of mineral resources as a research area and comprises a mining area and a mining area peripheral area. Mineral resources are non-ferrous mineral resources that contain a variety of heavy metals, such as Ni, Pb, Cr, Cu, Zn, Cd. In application, the collection work of soil sampling points can be completed according to a random uniform point distribution mode. For accurate data acquisition, the closer to the mining area, the denser the sampling points are, the farther away from the mining area, the sparser the sampling points are, that is, the density of the sampling points in the first area is greater than that of the sampling points in the second area, and the first area is formed by taking the mining area as the center and taking the first distance threshold as the radius. The second region is a region other than the first region. When the sampling point is located in the field, the sampling point needs to be far away from the edge of the field block and the roadside. Investigation is carried out before sampling, and fertilizer and pesticide application points are avoided. And 4-5 sampling points are arranged in the range of 3m × 3m around each sampling point, and 90-110 g, such as 90g, 100g and 110g, of surface soil is shoveled by plastic at each sampling point. The thickness range of the surface soil is 0-20 cm, such as 5cm, 10cm, 15cm and 20cm, then the surface soil is uniformly mixed and then is packaged into a sample bag, and the point position, the sampling date, the soil type and the sample point number are marked for storage. Before soil is detected, part of sampling points are randomly selected from the stored multiple sampling points, so that the randomness of the sampling points can be further improved. In application, 311 samples can be stored, and 166 samples can be randomly selected from the 311 samples for detection. The land utilization type is a land utilization mode. The types of land utilization in the mining area research area are mostly rice soil and vegetable soil, and may be other types, which is not limited in this embodiment.
The heavy metal content of the soil is mainly influenced by environmental influence factors, including: the method comprises two major factors of human and nature, wherein the soil formation process, the soil matrix and other natural factors have great influence on the heavy metal content of the soil, but in a smaller space range, the difference of the soil formation factors (climate, matrix and the like) is often reflected by the topographic factors such as elevation, gradient and the like. Because the collected and analyzed samples are vegetable field soil and rice soil, and the difference of soil types is small, the elevation and the gradient are selected as the influence factors. In addition, the physical and chemical properties of the soil are also main factors influencing the content and the form of the heavy metal in the soil, the relation between the content of the heavy metal in the soil and the physical and chemical properties of the soil is reflected by the selected pH value and the organic matter content, the leaching rate of elements is obviously influenced by the pH value, and meanwhile, the content of the organic matter in the soil has important influence on the heavy metal in the soil by controlling the geochemical behavior of the heavy metal in the soil. Aiming at the selection of human factors, according to the pollution characteristics of a mining area, such as mineral acquisition, transportation, processing, slag waste liquid flowing and the like, the distance between a sampling point and the mining area, a river and a residential site is selected as a consideration factor, and the influence factors of the heavy metal pollution of the soil are analyzed macroscopically. In addition, the distribution of heavy metal content in soil affected by human activities is often in a more complex situation, and in order to make heavy metal research more pertinent, the distribution of heavy metal content in two soil types (rice soil and vegetable soil) and the difference of influencing factors are compared, to sum up, natural factors include: organic matter (unit g/Kg), pH, gradient (unit degree), elevation (unit m), human factors including: residential distance (in km), river distance (in km), and mine distance (in km).
102, obtaining a heavy metal pollution characteristic value according to the content of the heavy metal, wherein the heavy metal pollution characteristic value comprises: mean, standard deviation, and coefficient of variation.
The detected data may have abnormal values which are far larger than most of numerical values, in order to avoid the result accuracy reduction caused by the abnormal values, the abnormal values are identified and removed by adopting a box line graph method, then K-S normal distribution test is carried out, data which are not in normal distribution are subjected to logarithmic conversion until the data are in normal distribution, characteristic value calculation is carried out on the data which meet the requirements, and the used tool can be SPSS 17.0. The heavy metal pollution characteristic values include: mean, standard deviation, and coefficient of variation. And (3) analyzing the distance, gradient, elevation and the like between the sample point and the selected heavy metal influence factors by applying ArcGIS10.0 software to determine whether the distance is suitable and uniformly distributed, whether the gradient meets the requirement of point selection and whether the point selection at the same elevation is a group, thereby realizing the accurate selection of the sampling point.
And 103, analyzing the heavy metal pollution characteristic values and the soil background values of the plurality of sampling points of various land utilization types to obtain the heavy metal pollution condition of the soil.
Specifically, judging whether the characteristic value of heavy metal pollution in various land utilization types is higher than a soil background value, and if so, determining that the heavy metal corresponding to the characteristic value of heavy metal pollution in the land utilization type is a primary pollutant; judging whether different land utilization types have the same primary pollutants, if so, comparing the heavy metal characteristic values corresponding to the primary pollutants in the different land utilization types to obtain the total pollution condition of the different land utilization types; and judging whether the variation coefficient in each land utilization type is higher than a preset variation coefficient threshold value, and if so, determining that the heavy metal pollution condition corresponding to the variation coefficient in the land utilization type is serious.
Referring to table 1, the heavy metal pollution characteristic values of the two land use types were obtained by calculation.
TABLE 1
The table shows that the average content of the six heavy metals in the vegetable field soil is higher than that of the heavy metals in the rice soil. In the two kinds of soil, except Ni and Cr, the content of the rest heavy metals is higher than the background value. Wherein, the content of Cd, Pb and Zn is far higher than the background value. Showing that Pb and Zn show an integral accumulation trend in the range of the research area of the mining area, which is a primary pollutant. The main harmful substances causing significant pollution to agricultural soil around the mining area research area for a long time are Pb and Zn, and Cd and Cu are accompanied with pollutants. Indicating that the heavy metal pollution condition caused by frequent mining activities in the area is severe. In addition, the Pb content of vegetable field soil and rice soil is 159.93mg/Kg, 76.21Kg/Kg respectively; the Zn content is 201.71mg/Kg,124.69, which have larger difference times, 2.1 times and 1.6 times respectively. Cd. Pb and Zn are main heavy metals, and the total pollution condition of vegetable field soil is more serious than that of rice soil.
The average value of the heavy metal can only indicate the overall level of the heavy metal content in the research area, and the variation of the local content can be qualitatively researched through the variation coefficient. The values of the coefficient of variation for several heavy metal contents can be seen in the table, and it is generally considered that a coefficient of variation greater than 75% achieves a strong variation. The variation of six heavy metals in both soils reached strong variation (CV > 75%). The variation coefficients of Pb in vegetable field soil and rice soil are 164.7% and 148.0% respectively, the variation coefficient of Cu in vegetable field soil is 142.7%, and the variation coefficient of Cu is extremely strong when the variation coefficient is more than 100%, so that the most serious pollution condition of Pb and Cu in vegetable field soil can be revealed, and the most obvious pollution condition of Pb in rice soil can be revealed.
To sum up: analyzing the characteristic values of two kinds of soil heavy metals: cd. Pb and Zn are main pollution heavy metals in a mining area research area, the overall pollution condition of vegetable field soil is more serious than that of rice soil, and the Pb and Zn contents of the vegetable field soil are obviously higher than that of the rice soil. The variation of six heavy metals in both soils reached strong variation (CV > 75%).
And 104, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points of various land use types by using a space autoregressive analysis model to obtain the correlation between the heavy metal content and the environmental influence factors.
Aiming at heavy metals Cd, Cu, Ni, Pb, Zn and Cr, respectively adopting a spatial error model, a spatial lag model and a spatial lag model for processing, namely: the influence factors of the heavy metal content distribution obtained by performing space autoregressive analysis on six heavy metals can be obtained. The data relating to vegetable soil are shown in Table 2.
TABLE 2
In table 2, the distribution of the heavy metals, except Zn, is affected by pH. The pH value is taken as a key index for researching the heavy metal in the soil, and is closely related to the migration, bioavailability and the like of the heavy metal. After exogenous heavy metals such as Cd, Cu and Pb enter soil, the competition effect of various heavy metal cations is possible to occur, so that the adsorption quantity of partial heavy metals in the soil is reduced, and the bioavailability and activity of the heavy metals are increased. In addition, when the pH value is increased, negative charges on the surfaces of hydrated oxides, organic matters and clay minerals in the soil are increased, so that the adsorption capacity of ions such as Cd and Zn is increased.
The elements which are obviously influenced by the river distance comprise Cd and Pb, and the content of the two heavy metals is in negative correlation with the river distance from the correlation coefficient, namely the content of Cd and Pb is higher as the heavy metals are closer to the river. The vegetable field soil is usually irrigated by sewage as a main water using mode, and because the mining area of a mining area research area is more, the activities of mining, dressing and smelting wastewater discharge and the like cause the pollution of water resources, and the water resources are irrigated by the sewage or directly discharged into farmlands, so that the heavy metal content is increased. In addition, the research area is located at the upstream of the water flow, and the water flow and stirring easily scour the sediment with the heavy metals to the research area, so that the area has the risk of heavy metal pollution. Therefore, the Cd and Pb pollution of vegetable field soil may be related to sewage irrigation or direct discharge of polluted water.
The heavy metals Cu, Pb and Zn are in significant relationship with their location from the population. The closer to the population, the higher the content of these three heavy metals. Vegetable field soil is usually close to residential areas, and application of organic fertilizers, pesticides and phosphate fertilizers made of town garbage and sludge easily causes increase of heavy metal content of the soil. In addition, the contents of Cu, Zn and Pb in soil are increased due to transportation and the like, a traffic network exists in a residential area, and the emission of automobile exhaust and tire wear are main sources of the heavy metal elements.
The correlation between the heavy metal Ni and Cr and the distance of the mining area is in negative correlation, namely, the content of the heavy metal is gradually reduced along with the increase of the distance, and the high content trend appears near the mining area. Mineral exploitation activities have the greatest impact on the Ni and Cr pollution of the soil, which may be caused by incomplete exploitation, smelting and extraction of the two elements in the tailings pond.
Through the spatial autoregressive analysis of the contents of several heavy metals in the soil and the influence factors, the source influence of different types of heavy metals in the vegetable field soil is inconsistent, and composite sources exist, such as significant correlation between the Pb content and the distance between residences and river distance. Cu, Pb and Zn are greatly influenced by artificial activities, and the content is higher when the Cu, Pb and Zn are closer to residents; cd and Pb can be influenced by pollution irrigation, direct discharge of beneficiation wastewater and the like, and are obviously related to river distance; ni and Cr are greatly influenced by mineral exploitation, and the content is higher when the value is closer to the mining area. The data relating to the soil of rice are shown in Table 3
TABLE 3
It can be seen from the above table that unlike vegetable field soil, rice soil has a tendency to be far from residential areas in spatial distribution. Cd and Cr do not have a significant relevant influence. The heavy metal Ni is obviously negatively correlated with the distance between a residential site and a mining area, and the Ni in the rice soil is subjected to composite pollution and dual influences of human activities and mining of mineral resources, so that the Ni content in the soil is increased.
As can be seen from the table, the average content of organic matters in the rice soil is 33.90g/Kg, and the content of organic matters is higher. The contents of heavy metals Cu, Pb and Zn are obviously and positively correlated with the content of organic matters, and the content of the organic matters has larger influence on the activity of the heavy metals in the soil. The possible reason is that the complex formed by the heavy metal ions and the organic matters reduces the heavy metal migration and bioavailability, thereby leading to the increase of the heavy metal content in the soil body.
Gradient factors influence the migration of heavy metals in the soil. Generally speaking, the large gradient is strongly washed by water flow, which is beneficial to heavy metal migration, and the smaller gradient is deposited. However, Pb and Zn show positive correlation, i.e., the Pb and Zn contents are high at the place with larger gradient. However, the Pb and Zn contents do not show a significant correlation with the distance from the mining area, which indicates that other reasons can exist for causing the phenomenon. In addition, the closer to the river, the higher the Pb content, indicating that Pb in the rice soil is greatly affected by irrigation. The heavy metal Ni shows correlation with both the residential distance and the mining distance, which indicates that Ni in the paddy soil is not only influenced by mining activities, but also has other migration paths. The data can be subjected to spatial regression analysis using GeoDa0.9.5-software.
In conclusion, 1) the spatial regression analysis shows that the spatial regression model of Cd in the vegetable field soil is a spatial error model, and the rest heavy metals accord with a spatial lag model; the spatial regression analysis of Cd and Cr in rice soil is to detect environmental factors which have significant influence on the content of Cd and Cr in rice soil, a fitting model of Cu is a spatial error model, and the rest heavy metals accord with a spatial lag model. 2) The relevance between the vegetable field soil heavy metal and the environmental factors is as follows: elements that are significantly affected by river distance include Cd and Pb; the heavy metals Cu, Pb and Zn are significantly related to the location from the residential site; the correlation between Ni and Cr and the distance between the mining area shows negative correlation. 3) The contents of Cu, Pb and Zn in the paddy soil and the organic matter content show obvious positive correlation, and in addition, the contents of Pb and Zn show positive correlation with the gradient.
In order to further research the heavy metals in the soil, the method also comprises the following steps: and analyzing the correlation among the heavy metals in each land utilization type to obtain the homologous relation among the heavy metal elements and whether the composite pollution exists. The correlation analysis among elements can laterally analyze the homologous relation among the elements and whether the composite pollution exists. This correlation is usually caused by similar geochemical conditions in the soil or by coexisting metals that contribute to soil contamination. The data processed by the correlation analysis is the content value of each heavy metal in the soil, and the obtained result is the value of the correlation among the content values of each heavy metal. Table 4 shows the correlation analysis data between the six heavy metals in the vegetable field soil and the rice soil:
TABLE 4
As can be seen from the table, the correlation between the different elements is the same in both soil types. Besides Cd, Cu has obvious correlation with the other four elements, wherein the correlation coefficient of the rice soil is larger than that of the vegetable soil; zn is also highly related to four heavy metals except Cd. The related coefficients of Zn and Pb in the vegetable field soil reach 0.864, and the related coefficients of Ni and Cr are 0.858, which indicates that the possibility that the two pairs of heavy metals have the same source is higher; in the paddy soil, the correlation coefficients of Cr, Cu, Ni, Zn and Pb are all larger than 0.8 and have the same source respectively. The possibility that multiple heavy metals in the research area have the same source is high, and combined pollution exists, namely, pollution of some soil caused by at least more than 2 heavy metals exists. In table 4, indicates significant correlation at the 0.01 level (double-sided); indicates significant correlation at the 0.05 level (bilateral). In conclusion, the correlation condition between elements is the same for the two types of soil. Besides Cd, Cu has obvious correlation with the other four elements, wherein the correlation coefficient of the rice soil is larger than that of the vegetable soil; zn is also highly related to four heavy metals except Cd.
Through analyzing the relationship between six heavy metals in vegetable land soil and rice soil and influencing factors, the influence factors of the heavy metal content are different in different soil utilization types of soil. The comparison shows that the influence factors of vegetable field soil heavy metal pollution are more complex and the influence of artificial factors is strong compared with that of rice soil. In vegetable field soil, elements which are obviously related to the distance between residents are as follows: the contents of Cu, Pb, Zn, Cd and Pb are significantly negatively related to the river distance, and Ni and Cr are significantly negatively related to the mine distance. In rice soil, elements which are obviously related to the content of organic matters comprise Ni, Pb and Zn; the Ni content is negatively related to the distance between a mining area and a residential site, and the Pb content is remarkably related to the distance between rivers. Therefore, vegetable field soil in a mining area research area is more seriously polluted compared with rice soil, influence factors are more complex, and influence of artificial factors is strong. Meanwhile, the heavy metal pollution conditions of the rice soil and the vegetable field soil in the mining area research area are diversified in source, and compound pollution exists. That is, two types of land use for a region are studied in a mine: the method comprises the steps of taking rice soil and vegetable soil as research objects, analyzing the heavy metal pollution condition of the soil in a mining area, exploring the correlation between the heavy metal content in the soil and environmental influence factors by applying a space autoregressive analysis model, finding out the heavy metal pollution rule and trying to analyze the possible causes of the heavy metal pollution rule. The research result can provide reliable basis for the research of heavy metal pollution and the analysis of the influence factors thereof in the future, simultaneously reveal the pollution rule of the heavy metal in the mining area soil, and provide support conditions for decision makers in the aspects of mineral exploitation and heavy metal pollution management in the future.
It will be appreciated by those skilled in the art that the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiments disclosed above are therefore to be considered in all respects as illustrative and not restrictive. All changes which come within the scope of or equivalence to the invention are intended to be embraced therein.
Claims (4)
1. A method for analyzing heavy metal pollution characteristics and environmental influence factors of mining area soil is characterized by comprising the following steps:
acquiring a soil background value of a mining area research area and heavy metal content, coordinate information and environmental influence factors of a plurality of sampling points, wherein the sampling points are sampling points for collecting mining area soil corresponding to various land utilization types, the land utilization types are land utilization types of the mining area research area, the environmental influence factors comprise natural factors and human factors, and the heavy metal content comprises: the content of various heavy metals;
obtaining a heavy metal pollution characteristic value according to the heavy metal content, wherein the heavy metal pollution characteristic value comprises: mean, standard deviation, and coefficient of variation;
analyzing the heavy metal pollution characteristic values and the soil background values of the plurality of sampling points of various land utilization types to obtain the heavy metal pollution condition of the soil;
processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points of various land use types by using a spatial autoregressive analysis model to obtain the correlation between the heavy metal content and the environmental influence factors;
the heavy metal content comprises: ni content, Pb content, Cr content, Cu content, Zn content and Cd content; the land use types include: rice soil and vegetable soil; the natural factors include: organic matter, pH, slope, elevation, the human factors include: residential distance, river distance, and mining area distance;
the method comprises the following steps of processing the heavy metal content, the coordinate information and the environmental influence factors of a plurality of sampling points by utilizing a space autoregressive analysis model to obtain the correlation between the heavy metal content and the environmental influence factors, and comprises the following steps:
when the land utilization type is vegetable land soil, if the obtained heavy metal content is Cd, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial error model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Cu, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Ni, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Pb, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Zn, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model; if the obtained heavy metal related to the correlation between the heavy metal content and the environmental influence factors is Cr, processing the heavy metal content, the coordinate information and the environmental influence factors of the plurality of sampling points by adopting a spatial lag model;
when the land utilization type is paddy soil, respectively processing heavy metals Cu, Ni, Pb and Zn by using a spatial error model, a spatial lag model and a spatial lag model, and processing heavy metals Cd and Cr by using a spatial autoregressive analysis model;
the closer the sampling points are to the mining area, the denser the sampling points are, the farther the sampling points are, the sparser the sampling points are, when the sampling points are located in the field, the sampling points need to be far away from the edges of the field blocks and the roadside, investigation is carried out before sampling, and fertilizer and pesticide application points are avoided.
2. The analysis method according to claim 1, wherein the obtaining of the heavy metal pollution characteristic value according to the heavy metal content comprises:
identifying and eliminating abnormal values in the obtained heavy metal content by adopting a box plot method, then carrying out K-S normal distribution test, and carrying out logarithmic transformation on data which are not in normal distribution until the data are in normal distribution;
and calculating the characteristic value of the normally distributed data to obtain the heavy metal pollution characteristic value.
3. The analytical method of claim 1, further comprising:
and analyzing the correlation among the heavy metals in each land utilization type to obtain the homologous relation among the heavy metal elements and whether the composite pollution exists.
4. The analysis method according to claim 1, wherein the analyzing the heavy metal pollution characteristic values and the soil background values of the plurality of sampling points to obtain the soil heavy metal pollution condition comprises:
judging whether the characteristic value of heavy metal pollution in various land utilization types is higher than a soil background value or not, and if so, determining that the heavy metal corresponding to the characteristic value of heavy metal pollution in the land utilization type is a primary pollutant;
judging whether different land utilization types have the same primary pollutants, if so, comparing the heavy metal characteristic values corresponding to the primary pollutants in the different land utilization types to obtain the total pollution condition of the different land utilization types;
and judging whether the variation coefficient in each land utilization type is higher than a preset variation coefficient threshold value, and if so, determining that the heavy metal pollution condition corresponding to the variation coefficient in the land utilization type is serious.
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