CN110836923A - Soil heavy metal concentration estimation method - Google Patents

Soil heavy metal concentration estimation method Download PDF

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CN110836923A
CN110836923A CN201911176546.1A CN201911176546A CN110836923A CN 110836923 A CN110836923 A CN 110836923A CN 201911176546 A CN201911176546 A CN 201911176546A CN 110836923 A CN110836923 A CN 110836923A
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soil
heavy metal
concentration
value
sampling point
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亦如瀚
杨东升
陈铭聪
连逸轩
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Jinan University
University of Jinan
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Abstract

The embodiment of the invention discloses a method for estimating the concentration of heavy metal in soil, which particularly relates to the technical field of soil heavy metal detection and comprises the following specific steps: s1, collecting the pH value, the cation exchange capacity, the organic carbon content and the altitude data of a soil sampling point; s2, establishing a mathematical model by adopting a multiple regression analysis method, and establishing a linear relation between the heavy metal concentration and the soil physicochemical property; s3, inputting the required parameters into a formula to obtain the estimated concentration of the heavy metal at the point; and S4, testing the coincidence between the prediction result and the soil heavy metal measured value. The invention establishes the correlation between the heavy metal content and the environmental factors by integrating the physicochemical properties of sampling points such as soil pH, cation exchange capacity, organic matter content and the like and the altitude of the area as parameters, realizes the prediction of the concentration of the heavy metal around the research area, is more scientific and effective, provides reference for the environmental pollution degree of the area and provides scientific basis for environmental management in the future.

Description

Soil heavy metal concentration estimation method
Technical Field
The embodiment of the invention relates to the technical field of soil heavy metal detection, in particular to a soil heavy metal concentration estimation method.
Background
The heavy metal pollution of the soil refers to the content of trace metal elements in the soil exceeding a background value due to human activities and caused by excessive deposition, the heavy metal refers to the metal with the specific gravity equal to or greater than 5.0, such As Fe, Mn, Zn, Cd, Hg, Ni, Co and the like, As is a metalloid, but because the chemical property and the environmental behavior of the heavy metal are similar to those of the heavy metal, arsenic is often included in the heavy metal discussion, and some heavy metals are directly included in the heavy metal range.
The prior art has the following defects: most of existing soil heavy metal concentration estimation methods take vegetation indexes, sampling point longitudes and original data of the sampling points as parameters, and evaluate the overall pollution condition of an area on a large space scale, for example, an invention patent with the publication number of CN 108563974A, the method can only predict the approximate range of heavy metal content, and the prediction precision needs to be improved; or soil physicochemical properties such as pH and organic matters are taken as parameters, the method does not consider the influence of geographical environmental factors on the migration and transformation of heavy metals, such as obvious influence of altitude on the direction of rainfall runoff, and most of heavy metals can migrate along with rainwater washing, so the prediction accuracy of the method is low.
The linear regression equation is a statistical analysis method for determining the interdependent quantitative relationship between two or more variables by using regression analysis in geographic statistics, and can be used for describing the potential relationship of a plurality of environmental factors in the environmental field and estimating the influence of the environmental factors on pollution.
Disclosure of Invention
Therefore, the embodiment of the invention provides a method for estimating the concentration of heavy metal in soil, which establishes the correlation between the content of heavy metal and environmental factors by integrating the physicochemical properties of sampling points such as soil pH, cation exchange capacity and organic matter content and the altitude of a region as parameters to realize the prediction of the concentration of heavy metal around a research area.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions: a soil heavy metal concentration estimation method comprises the following specific steps:
s1, collecting the pH value, the cation exchange capacity, the organic carbon content and the altitude data of a soil sampling point;
s2, establishing a mathematical model by adopting a multiple regression analysis method, establishing a linear relation between the heavy metal concentration and the soil physicochemical property, and realizing the prediction of the heavy metal concentration;
s3, inputting the required parameters into a formula to obtain the estimated concentration of the heavy metal at the point;
and S4, testing the coincidence between the prediction result and the soil heavy metal measured value.
Further, in step S1, the pH value, the cation exchange capacity, and the organic carbon content of the soil sampling point are all measured through experiments, and the altitude of the sampling point is obtained through google earth query.
Further, in step S2, the multiple regression equation is:
Figure BDA0002290116280000021
Figure BDA0002290116280000022
y＝b0+b1x1+b2x2+b3x3+b4x4
wherein k is the value of the kth environmental parameter related to the concentration of the heavy metal, n is the number of soil heavy metal sampling points, and xikIs the value of the kth environmental parameter, y, of the soil at the ith sampling pointiThe concentration of Ni at the ith soil heavy metal sampling point,
Figure BDA0002290116280000023
is the mean value of the kth environmental parameter of the soil sampling point,
Figure BDA0002290116280000024
and the concentration of Ni in all soil heavy metal sampling points is the average value.
Further, the linear relation equation of the heavy metal concentration and the soil physicochemical property obtained by the multiple regression equation is as follows:
y＝79.916-9.701x1+1.075x2-1.606x3+0.193x4
wherein x is1Is the pH value of the soil, x2Is the total organic carbon content of soil, x3Is the altitude, x, of the sample point4The cation exchange capacity of the soil at the sampling point.
Further, the detailed steps of detecting the soil heavy metal measured value in step S4 are:
1) according to the GPS positioning, when the soil reaches a specific area, collecting about 500g of a 0-20cm soil sample by a five-point sampling method, wrapping the soil sample by kraft paper, and attaching a label;
2) naturally drying the soil sample, grinding the soil sample by using a ceramic mortar, and then sieving the ground soil sample by using a 100-mesh sieve;
3) taking a 0.1g soil sample, putting 5mL of aqua regia and 1mL of hydrofluoric acid which are analytically pure into a Teflon tube, digesting by using a microwave digestion instrument, evaporating to dryness to 1mL by using an acid dispelling instrument, and fixing the volume to 40mL by using ultrapure water to be detected;
4) and (4) loading the sample on a machine, and analyzing the content of the heavy metal by using an inductively coupled plasma mass spectrometer.
The embodiment of the invention has the following advantages:
the invention integrates the physicochemical properties of sampling points such as soil pH, cation exchange capacity, organic matter content and the like and the altitude of the area as parameters, establishes the correlation between the heavy metal content and the environmental factors, realizes the prediction of the concentration of the heavy metal around the research area, saves a large amount of financial resources and material resources in the research process compared with the prior art, is more scientific and effective, provides reference for the environmental pollution degree of the area, and provides scientific basis for the environmental management in the future.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
The structures, ratios, sizes, and the like shown in the present specification are only used for matching with the contents disclosed in the specification, so as to be understood and read by those skilled in the art, and are not used to limit the conditions that the present invention can be implemented, so that the present invention has no technical significance, and any structural modifications, changes in the ratio relationship, or adjustments of the sizes, without affecting the effects and the achievable by the present invention, should still fall within the range that the technical contents disclosed in the present invention can cover.
Fig. 1 is a fitting result graph of the measured value and the predicted value of the heavy metal Ni provided in embodiment 3 of the present invention.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
the invention provides a method for estimating heavy metal concentration in soil, which comprises the following specific steps:
s1, collecting the pH value, the cation exchange capacity, the organic carbon content and the altitude data of the soil sampling point, wherein the pH value, the cation exchange capacity and the organic carbon content of the soil sampling point are measured through experiments, and the altitude of the sampling point is obtained through Google Earth query;
s2, establishing a mathematical model by adopting a multiple regression analysis method, establishing a linear relation between the heavy metal concentration and the soil physicochemical property, realizing the prediction of the heavy metal concentration,
the multiple regression equation is:
Figure BDA0002290116280000041
y＝b0+b1x1+b2x2+b3x3+b4x4
wherein k is the value of the kth environmental parameter related to the concentration of the heavy metal, n is the number of soil heavy metal sampling points, and xikIs the value of the kth environmental parameter, y, of the soil at the ith sampling pointiThe concentration of Ni at the ith soil heavy metal sampling point,
Figure BDA0002290116280000043
is the mean value of the kth environmental parameter of the soil sampling point,
Figure BDA0002290116280000044
the mean value of Ni concentration in all soil heavy metal sampling points is obtained by a multiple regression equation, and the linear relation equation of the heavy metal concentration and the soil physicochemical property is as follows:
y＝79.916-9.701x1+1.075x2-1.606x3+0.193x4
wherein x is1Is the pH value of the soil, x2Is the total organic carbon content of soil, x3Is the altitude, x, of the sample point4The cation exchange capacity of the soil at the sampling point.
S3, inputting the required parameters into a formula to obtain the estimated concentration of the heavy metal at the point;
and S4, testing the coincidence between the prediction result and the soil heavy metal measured value.
Example 2:
the multiple regression equation is:
Figure BDA0002290116280000052
y＝b0+b1x1+b2x2+b3x3+b4x4，
the linear regression equation is one of statistical analysis methods for determining the quantitative relationship of the interdependence between two or more variables by using the regression analysis in mathematical statistics, and is widely applied, and when the linear correlation relationship exists between the random variable and the variable, the points (x, y) obtained from the experimental data are scattered around a certain straight line, so that the type of the regression function is considered to be a linear functionikIs the value of the kth environmental parameter, y, of the soil at the ith sampling pointiThe concentration of Ni at the ith soil heavy metal sampling point,
Figure BDA0002290116280000053
is the mean value of the kth environmental parameter of the soil sampling point,
Figure BDA0002290116280000054
is the mean value of Ni concentration in all soil heavy metal sampling points,
from this, the equation is:
y＝79.916-9.701x1+1.075x2-1.606x3+0.193x4
wherein x is1Is the pH value of the soil, x2Is the total organic carbon content of soil, x3Is the altitude, x, of the sample point4The cation exchange capacity of the soil at the sampling point.
Example 3:
the measured value of the heavy metal in the soil used by the invention is that the soil is sampled in the tidal plus district of Shangshan City of Guangdong province in 2017 for 8 months, and the soil is subjected to microwave digestion and then is measured by an inductively coupled plasma mass spectrometer (ICP-MS), wherein the total number of the heavy metal is 60, and the detailed steps are as follows:
1) according to the GPS positioning, when the soil reaches a specific area, a five-point sampling method is used for collecting about 500g of a 20cm soil sample, the soil sample is wrapped by kraft paper, and a label is attached;
2) naturally drying the soil sample, grinding the soil sample by using a ceramic mortar, and then sieving the ground soil sample by using a 100-mesh sieve;
3) taking a 0.1g soil sample, putting 5mL of aqua regia and 1mL of hydrofluoric acid which are analytically pure into a Teflon tube, digesting by using a microwave digestion instrument, evaporating to dryness to 1mL by using an acid dispelling instrument, and fixing the volume to 40mL by using ultrapure water to be detected;
4) and (4) loading the sample on a machine, and analyzing the content of the heavy metal by using an inductively coupled plasma mass spectrometer.
The pH value, the organic carbon content and the cation exchange capacity of the soil at the 60 sampling points are measured by experiments, and the pH value of the soil can be measured by an acidimeter; the organic carbon content is determined by potassium dichromate oxidation-spectrophotometry; cation exchange capacity according to the formula:
Figure BDA0002290116280000061
measurement, in which: c is the concentration (mol. L) of the hydrochloric acid standard solution-1) V is the amount (mL) of hydrochloric acid standard solution consumed by titrating the sample solution to be tested, V0The amount of hydrochloric acid standard solution consumed (mL) was determined for each blank, m was the air-dried sample mass (g), 10 was the number of cmol in terms of mmol, and 1000 was cmol per kg; the sampling point altitude is obtained by google earth query.
Regression analysis is carried out on 30 values of heavy metal concentration, pH, organic carbon content and cation exchange capacity in the measured values by excel to obtain a fitting curve:
y＝79.916-9.701x1+1.075x2-1.606x3+0.193x4
the remaining 30 points of pH, organic carbon contentSubstituting the values of the amount and cation exchange amount into the above formula to obtain predicted heavy metal concentration y1, comparing y1 with the concentration y of the measured heavy metal value at 30 points, and eliminating abnormal value to obtain fitting result, wherein the correlation coefficient R is shown in Table 12>70%, the predicted result and the measured result have high coincidence.
Mean value of Minimum value Maximum value Standard deviation of
Prediction value 15.09 7.88 24.91 4.37
Measured value 14.44 7.55 25.30 4.82
TABLE 1 result table of measured and predicted values of heavy metal Ni (unit: mg/kg)
Example 4:
in the prior art, when parameters of an equation are soil Cd concentration, organic matters and cation exchange capacity, the equation is used for predicting the Cd content in rice, and the correlation coefficient is 50.9 percent and is lower than the equation provided by the invention.
Although the invention has been described in detail above with reference to a general description and specific examples, it will be apparent to one skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.

Claims (5)

1. A soil heavy metal concentration estimation method is characterized by comprising the following steps: the method comprises the following specific steps:
s1, collecting the pH value, the cation exchange capacity, the organic carbon content and the altitude data of a soil sampling point;
s2, establishing a mathematical model by adopting a multiple regression analysis method, establishing a linear relation between the heavy metal concentration and the soil physicochemical property, and realizing the prediction of the heavy metal concentration;
s3, inputting the required parameters into a formula to obtain the estimated concentration of the heavy metal at the point;
and S4, testing the coincidence between the prediction result and the soil heavy metal measured value.
2. The soil heavy metal concentration estimation method according to claim 1, wherein: in step S1, the pH value, the cation exchange capacity, and the organic carbon content of the soil sampling point are all measured by experiments, and the altitude of the sampling point is obtained by google earth query.
3. The soil heavy metal concentration estimation method according to claim 1, wherein: in step S2, the multiple regression equation is:
Figure FDA0002290116270000011
Figure FDA0002290116270000012
y＝b0+b1x1+b2x2+b3x3+b4x4
wherein k is the value of the kth environmental parameter related to the concentration of the heavy metal, n is the number of soil heavy metal sampling points, and xikIs the value of the kth environmental parameter, y, of the soil at the ith sampling pointiThe concentration of Ni at the ith soil heavy metal sampling point,
Figure FDA0002290116270000013
is the mean value of the kth environmental parameter of the soil sampling point,
Figure FDA0002290116270000014
and the concentration of Ni in all soil heavy metal sampling points is the average value.
4. The soil heavy metal concentration estimation method according to claim 2, wherein: the linear relation equation of the heavy metal concentration and the soil physicochemical property obtained by the multiple regression equation is as follows:
y＝79.916-9.701x1+1.075x2-1.606x3+0.193x4
wherein x is1Is the pH value of the soil, x2Is the total organic carbon content of soil, x3Is the altitude, x, of the sample point4The cation exchange capacity of the soil at the sampling point.
5. The soil heavy metal concentration estimation method according to claim 1, wherein: the detailed steps of the detection of the soil heavy metal measured value in step S4 are as follows:
1) according to the GPS positioning, when the soil reaches a specific area, collecting about 500g of a 0-20cm soil sample by a five-point sampling method, wrapping the soil sample by kraft paper, and attaching a label;
2) naturally drying the soil sample, grinding the soil sample by using a ceramic mortar, and then sieving the ground soil sample by using a 100-mesh sieve;
3) taking a 0.1g soil sample, putting 5mL of aqua regia and 1mL of hydrofluoric acid which are analytically pure into a Teflon tube, digesting by using a microwave digestion instrument, evaporating to dryness to 1mL by using an acid dispelling instrument, and fixing the volume to 40mL by using ultrapure water to be detected;
4) and (4) loading the sample on a machine, and analyzing the content of the heavy metal by using an inductively coupled plasma mass spectrometer.
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CN113299350A (en) * 2021-05-20 2021-08-24 中国科学院东北地理与农业生态研究所 Method for predicting chemical index of soda salt and alkali by using soil pH
CN113624634A (en) * 2021-08-11 2021-11-09 北京师范大学 Method for estimating content of metal elements in buried environment

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Cited By (3)

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Publication number Priority date Publication date Assignee Title
CN113299350A (en) * 2021-05-20 2021-08-24 中国科学院东北地理与农业生态研究所 Method for predicting chemical index of soda salt and alkali by using soil pH
CN113624634A (en) * 2021-08-11 2021-11-09 北京师范大学 Method for estimating content of metal elements in buried environment
CN113624634B (en) * 2021-08-11 2022-04-22 北京师范大学 Method for estimating content of metal elements in buried environment

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