In-situ analysis method for discriminating spatial distribution and occurrence form of heavy metals in soil of construction site

Abstract

This invention discloses an in-situ analytical method for determining the spatial distribution and occurrence forms of heavy metals in soil. This method can analyze the distribution characteristics of heavy metals in soil in situ, quantify the dynamic changes in the distribution of heavy metals on soil organic-mineral components under the influence of external conditions such as moisture and organic matter input, and the changes in distribution within soil aggregates of different particle sizes. This in-situ analytical method has advantages such as being environmentally friendly, rapid, cost-effective, and non-destructive to soil properties. Compared with traditional continuous extraction methods, it can eliminate cumbersome pretreatment steps, save chemical reagents, shorten testing time, and improve analytical accuracy. It can provide a scientific basis for the precise prevention and control of heavy metals in contaminated soil and risk management, and has broad application prospects.

Description

Technical Field

[0001] This invention relates to the field of heavy metal pollution technology, specifically to an in-situ analysis method for determining the spatial distribution and occurrence form of heavy metals in soil. Background Technology

[0002] With the rapid pace of socio-economic development, industrialization, and urbanization, many industrial enterprises, after relocation or closure, cause severe heavy metal pollution in their soil sites. This not only severely damages the ecological environment but also threatens human survival and health. Heavy metal pollution is characterized by high concentrations and complex forms, and its bioavailability, chemical behavior, and fate are influenced by soil minerals, organic matter, and microorganisms. Changes in natural environmental conditions, such as moisture and the input of exogenous organic matter, affect the form and redistribution of heavy metals by influencing soil composition. Furthermore, soil aggregates of different particle sizes exhibit variations in surface structure, specific surface area, and surface potential, leading to differences in the form, content, and distribution of heavy metals. Therefore, effective management and remediation of heavy metal-contaminated soil necessitates understanding the dynamic changes of heavy metals at the interfaces of soil solid components and within aggregates of different particle sizes under the influence of natural conditions. However, current domestic and international methods typically employ Tessier or BCR continuous extraction combined with ICP-MS to indirectly reflect the distribution of dissolved heavy metals. These methods, due to the use of large amounts of chemical reagents during extraction, alter the physical structure and chemical properties of the soil, failing to accurately reflect the actual metal occurrence and spatial distribution. Therefore, developing non-destructive and environmentally friendly in-situ analytical techniques or methods is crucial for research on the environmental behavior of heavy metals, pollution control, and remediation.

[0003] In view of the current situation, this invention will propose an in-situ method for analyzing the occurrence of heavy metals in contaminated soil in a certain city by combining scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) with image segmentation, and characterize the dynamic changes of heavy metal speciation under the influence of moisture and organic matter and in different particle sizes. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide an in-situ analysis method for determining the spatial distribution and occurrence form of heavy metals in soil. This method can analyze the distribution and morphological characteristics of heavy metals in situ, quantify the dynamic changes in the morphology of heavy metals on soil organic-mineral components under the influence of external conditions such as moisture and organic matter input, and the morphological changes in soil aggregates of different particle sizes. This provides a scientific basis for the precise prevention and control of heavy metals in contaminated soil and risk management.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] In a first aspect, the present invention provides an in-situ analytical method for heavy metal speciation in soil from heavily polluted sites, the method comprising the following steps:

[0007] S1: Select heavily polluted sites to collect soil samples and perform pretreatment on the samples, including air-drying the collected samples, crushing them, sieving them, and bagging them.

[0008] S2: Apply exogenous substances to the sample, culture for a certain period of time, and take samples periodically;

[0009] S3: Determine the basic physicochemical properties of soil samples, including pH, organic matter, clay mineral identification, carbonate content, conventional element content, heavy metal content, etc.; Determine the heavy metal speciation using conventional chemical methods, including extracting the content of six soil heavy metal speciations—surface-bound, carbonate-bound, humic acid-bound, amorphous iron oxide-bound, crystalline iron oxide-bound, and residual—using the improved Tessier sequential extraction method.

[0010] S4: Carefully adhere the air-dried and sieved sample from step S1 onto conductive adhesive and directly perform SEM-EDS testing to obtain the sample morphology and the spatial distribution of common soil elements C, O, Al, Fe, Ca, Si, and heavy metal elements Cu and Pb. The contents of all eight elements measured were higher than the EDS limit of detection (mass percentage concentration ~0.1%).

[0011] S5: Based on the fundamental knowledge of soil heavy metals and the analysis of the soil solid phase composition and heavy metal speciation defined by chemical extraction methods in step S3 above, the heavy metal speciation in the site soil is mainly classified into four categories: organic-bound, iron oxide-bound, carbonate-bound, and aluminosilicate-bound. That is, heavy metals are mainly found in four soil components composed of six elements: C, O, Fe, Ca, Al, and Si. This corresponds to the elemental distribution results obtained from EDS testing in step S4 above. Therefore, this invention will use Cu and Pb as examples, representing the distribution of the four speciations by the overlapping portion with the spatial distribution of these six conventional soil elements.

[0012] S6: Perform image segmentation on the sample morphology obtained in step S4 to distinguish between the background region and the sample region.

[0013] S7: Apply the sample area divided in step S6 to the distribution of the six elements in step S4 to obtain the distribution of soil elements within the sample area.

[0014] S8: Based on the distribution of the six elements in the sample area in step S7 above, calculate the percentage of the pixel area of ​​the overlapping part in step S5 above to the total pixel area of ​​Cu / Pb, thereby quantifying the relative content of each form of Cu / Pb in the total Cu / Pb.

[0015] S9: The sample area and the distribution of the six elements corresponding to that area are image-segmented again in steps S6 and S7 to obtain soil particles of different sizes. Steps S5 and S8 are repeated to obtain the relative contents of the four Cu / Pb forms in soil particles of different sizes;

[0016] S10: Perform the above steps S4-S9 on the samples before and after organic matter culture in steps S1 and S2 to obtain the variation of the four forms of Cu / Pb with culture time and the distribution pattern in different particle sizes.

[0017] By analyzing the physicochemical properties of organic matter before and after cultivation and samples of different particle sizes, and by combining data from other instruments, the rationality of the change pattern of this data is confirmed, thereby demonstrating the effectiveness of the method described in this invention.

[0018] Secondly, this invention provides a model for the distribution of heavy metals in different solid phase components of soil, which is constructed by classifying and calculating the occurrence forms of heavy metals.

[0019] The heavy metal occurrence forms are classified as follows: heavy metals in the site soil are classified into four categories: carbonate-bound, humic acid-bound, iron oxide-bound, and aluminosilicate-bound. The SEM-EDS elemental test results will be used to illustrate these four heavy metal forms and their dynamic changes over time. Specifically: the C-Ca-O heavy metal element superposition area in the EDS surface scan results is classified as carbonate-bound heavy metal, i.e., inorganic carbon-bound heavy metal; the CO-heavy metal superposition area of ​​all carbon-bound heavy metals in the soil is subtracted from the C-Ca-O-heavy metal superposition area, which is classified as organic matter-bound heavy metal; Fe-O-heavy metal is classified as iron oxide-bound; and Al-Si-O-heavy metal minus Fe-containing silicate minerals, i.e., Al-Si-Fe-O-heavy metal, is classified as aluminosilicate-bound.

[0020] The calculation of heavy metal occurrence formats involves: quantifying heavy metal formats by using ImageJ software to digitize elemental surface scans of pre-defined sample regions or regions of interest with different particle sizes; then, the digitized surface scans of each elemental surface scan are used in an Excel spreadsheet to quantify four types of heavy metal formats: organic-bound, iron oxide-bound, carbonate-bound, and aluminosilicate-bound. Specifically, the COUNTIFS function calculates the number of pixels in combinations of CO-heavy metal, C-Ca-O-heavy metal, Fe-O-heavy metal, Al-Si-O-heavy metal, and Al-Si-Fe-O-heavy metal where all common soil elements are simultaneously greater than 0 (or a specific value) and heavy metals are also greater than 0 (or a specific value). The percentage of each combination's pixel count to the total number of heavy metal pixels is then calculated.

[0021] Thirdly, this invention provides an application of the method described above in farmland soil contaminated with high concentrations of heavy metals. The method enables in-situ analysis of the distribution and speciation of heavy metals, quantifies the dynamic changes in the speciation of heavy metals on soil organic-mineral components under the influence of external conditions such as moisture and organic matter input, and examines the speciation changes in soil aggregates of different particle sizes.

[0022] The advantages and beneficial effects of this invention are as follows:

[0023] Compared with existing technologies, this invention discloses an in-situ analysis method for the occurrence of heavy metal speciation in soils of heavily polluted sites based on SEM-EDS. This method can effectively quantify the dynamic changes in heavy metal speciation on soil organic-mineral components under the influence of external conditions such as moisture and organic matter input, distinguish the degree of influence of exogenous additives such as moisture and organic matter on heavy metal speciation, and analyze the speciation changes in soil aggregates of different particle sizes. It has advantages such as being green and environmentally friendly, fast, affordable, and non-destructive to soil properties. Compared with traditional continuous extraction methods, it can eliminate cumbersome pretreatment steps, save chemical reagents, and shorten testing time. Attached Figure Description

[0024] Figure 1 The morphologies of Cu and Pb in the improved Tessier six-stage continuous extraction according to this invention are: F1-F6, which are surface-bound, carbonate-bound, humic acid-bound, amorphous iron oxide-bound, crystalline iron oxide-bound, and residue-bound, respectively.

[0025] Figure 2 These are the SEM-EDS test results of this invention;

[0026] Wherein: (1): SEM morphology image corresponding to a certain test area; (2): EDS spectrum and mass percentage concentration (wt%) of conventional elements and heavy metals in soil corresponding to the test area in (1).

[0027] Figure 3 A schematic diagram illustrating image segmentation to distinguish the background region and the sample region in this invention;

[0028] Among them: (1): Figure 2 The sample area after the test area is segmented (within the yellow circle); (2) and (3): Comparison of Al element distribution before and after segmentation.

[0029] Figure 4 This is a diagram illustrating the process by which soil particles of different sizes are distinguished according to the present invention.

[0030] Wherein: (1): SEM morphology image corresponding to a certain test area; (2), (3) and (4) are respectively: 20-53um soil aggregates, 2-20um soil aggregates and 0-2um soil particles after image segmentation.

[0031] Figure 5 This is a graph showing the changes in the speciation of heavy metals in the three organic materials RS, LF, and BC before and after cultivation over time.

[0032] Among them, (1) and (2) are the graphs showing the changes of the four forms of Cu and Pb over time.

[0033] Figure 6 The graph shows the changes in the speciation of heavy metals over time before and after culturing with three water contents of 30%, 60%, and 200% according to the present invention.

[0034] Among them, (1) and (2) are the graphs showing the changes of the four forms of Cu and Pb over time.

[0035] Figure 7 This is a graph showing the changes in the speciation of heavy metals in different particle sizes over time after culturing the three organic materials RS, LF, and BC of this invention.

[0036] Among them: (1) and (2) are the graphs showing the changes of four forms of Cu and Pb over time in three particle sizes of 0-2um, 2-20um and 20-53um, respectively.

[0037] Figure 8 The results of X-ray absorption fine structure spectroscopy experiments of Cu after soil culture of three organic matter types (CK, RS, LF, BC) before soil culture are presented in this invention.

[0038] Wherein: (1): solid line and dashed line represent the sample and fitting result respectively; (2): percentage content after linear fitting (LCF).

[0039] Figure 9This is a flowchart of the method of the present invention. Detailed Implementation

[0040] The technical solution of the present invention will be further described clearly and completely below with reference to the accompanying drawings and specific embodiments.

[0041] Example 1

[0042] Sample collection and pretreatment: Soil from the top 0-20cm layer of a heavily polluted site in a city in Hubei Province was selected. After natural air drying, grinding, sieving, and bagging, basic physicochemical properties such as pH, organic matter, carbonate content, and mineral composition were determined (as shown in Tables 1 and 2), as well as the total amounts of the main heavy metal pollutants Cu, Pb, As, Cr, Cd, and common elements Ca, Al, and Fe. The improved Tessier six-stage continuous extraction method (Table 3) was used to determine six forms of heavy metals Cu and Pb: surface-bound, carbonate-bound, humic acid-bound, amorphous iron oxide-bound, crystalline iron oxide-bound, and residual states (e.g., surface-bound, carbonate-bound, humic acid-bound, amorphous iron oxide-bound, crystalline iron oxide-bound, and residual states). Figure 1 (As shown).

[0043] Sample cultivation: After the soil was naturally air-dried, it was ground through a 10-mesh sieve. (1) Three organic matter culture groups were set up, namely 5% leaf, rice straw and biochar (basic physicochemical properties are shown in Table 1), with the moisture content maintained at 60%, and cultured for 60 days. Samples were taken on the 1st, 30th and 60th days, and freeze-dried for later use; (2) Three water content culture groups were set up, namely 30%, 60% and 200% water content, and cultured for 90 days. Samples were taken on the 1st and 90th days, and freeze-dried for later use.

[0044] Sample testing: Both native and cultured soil samples were first sieved through a 10-mesh sieve and then through a 100-mesh sieve to ensure the soil particle size was suitable for scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS, TESCAN Clara, Oxford Instruments Xplore 30). Soil powder was evenly sprinkled onto a special carbon conductive tape for SEM, excess powder was blown away, and the surface was uniformly coated with gold. The sample was then placed in the instrument's sample chamber and a vacuum was applied. Morphological imaging was performed on a region containing both large and small soil particles evenly distributed under 20keV voltage, 1nA current, and 1000x magnification. The same region was then subjected to EDS for area scanning of O, Al, Si, Fe, C, Ca, Cu, and Pb elements. The testing time was approximately 6 minutes. Figure 2 As shown, the contents of all eight elements in the test area were higher than the EDS minimum detection limit (wt%, 0.1%), and the heavy metals in the soil of the site used in this invention were only Cu and Pb with contents higher than 0.1% (approximately 0.2% and 0.1% after conversion to wt% concentration according to Table 1, and the contents of the other heavy metals were all lower than 0.1%).

[0045] Image segmentation of background and sample regions: To eliminate the interference of the carbon conductive tape background region on the subsequent analysis of heavy metal morphology, such as... Figure 3 As shown, ImageJ software was used to segment the SEM-EDS test results, dividing the sample region and the corresponding element distribution, while discarding the background region. Figure 3 Taking the AI ​​element as an example, it can be seen that the background pixels have been eliminated.

[0046] The specific steps are as follows: Open the SEM morphology test results, use the Rectangle tool to select the area within the white border and scale bar, and click Edit - Selection - Make Inverse to invert the selected area to remove the border and scale bar. Click Image - Type to set the image to 8-bit format, and Image - Adjust - Threshold to adjust the appropriate image threshold. Then click Apply to divide the background and sample areas in the SEM image. Click Edit - Selection - Create selection to select the divided sample area (e.g., ...). Figure 2 (As shown), open Analyze-Tools-ROI manager, add the region to ROImanager and save. Open the EDS area scan test results of 8 elements, click Image-Stack-Images to stack to put all elements into a stack for batch image processing, click the sample region saved in ROI manager to apply to the stack, click Eidt-Selection-Make Inverse again to invert the selected area and select the background area, then delete the background area of ​​each image to obtain the distribution of 8 elements in the sample area.

[0047] Image segmentation of soil aggregates of different particle sizes: This is to enable further analysis of the morphological characteristics of heavy metals on the surface of soil aggregates of different particle sizes, such as... Figure 4 As shown, the SEM-EDS test results were first segmented using ImageJ software to obtain soil aggregates with particle sizes of 20-53µm and 2-20µm, and soil particles with a particle size of 0-2µm.

[0048] The specific steps are as follows: Open the SEM topography image in ImageJ, click the Straight tool to select the scale bar length on the image, open Analyze-Tools-ROI manager, add the scale bar length to the ROI manager and save. Click Analyze-Set Scale, and enter the corresponding scale bar length and unit in Known distance and Unit of length respectively to complete the conversion of the image pixel units. Open the SEM image after dividing the sample area in the previous step, click Analyze-Analyze Particles, enter the area or area range corresponding to the desired particle size aggregate in Size (um^2), and select Overlay Masks in the Show option to display the distribution location of aggregates of the set size on the image, as well as the specific area size and other parameters of each aggregate in Results. At this time, the ROI manager will automatically display the region of all aggregates of the particle size of interest. After selecting all, right-click and select Save to save the region. Open the Stack containing the 8 element area scans from the above steps. In the ROI manager, right-click the selected area again and select OR (Combine) to display the region of aggregates of the particle size of interest in the element area scan. Similarly, click Eidt-Selection-MakeInverse to invert the selected area and select the background area. Then delete the background area in each image to obtain the distribution of the 8 elements in the region of interest.

[0049] Classification of heavy metal occurrence formats: By analyzing the solid phase composition of the example soil samples of this invention through Tables 1 and 2, it can be seen that:

[0050] (1) The soil contains a large amount of carbonates. The soil has a pH greater than 7 and is considered alkaline, which makes it easy to form carbonate minerals. The test result of calcium carbonate content of 33.13 g / kg also supports this.

[0051] (2) The topsoil contained abundant organic matter (SOC, 18.6 g / kg). After the addition of exogenous organic matter, the organic matter content increased (to 27.77 g / kg, 34.23 g / kg, and 39.19 g / kg, respectively). The dissolved organic carbon (DOC) in the four samples was only in the mg / kg range, indicating that the soil organic matter mainly existed in the solid phase.

[0052] (3) The soil is rich in crystalline and amorphous Fe (15843.67 mg / kg and 2517.05 mg / kg, respectively);

[0053] (4) The clay minerals in the soil mainly exist in the form of four silicate minerals, including hydromica containing Al and Si.

[0054] In summary, based on fundamental knowledge of soil heavy metals and the improved Tessier six-level continuous extraction definition of heavy metal speciation, this invention classifies heavy metals in the soil of this site into four categories: carbonate-bound, humic acid-bound, iron oxide-bound, and aluminosilicate-bound. Furthermore, the SEM-EDS elemental analysis results will demonstrate these four heavy metal speciations and their dynamic changes over incubation time. Specifically, the C-Ca-O-Cu / Pb elemental superposition region in the EDS surface scan results is classified as carbonate-bound Cu(Pb) (i.e., inorganic carbon-bound); the Cu / Pb superposition region of all carbon-bound elements in the soil (i.e., CO-Cu / Pb superposition region) minus the inorganic carbon-bound Cu / Pb superposition region (i.e., C-Ca-O-Cu / Pb superposition region) is classified as organic matter-bound Cu / Pb; Fe-O-Cu / Pb is classified as iron oxide-bound; and Al-Si-O-Cu / Pb minus Fe-containing silicate minerals (i.e., Al-Si-Fe-O-Cu / Pb) is classified as aluminosilicate-bound.

[0055] Calculation of heavy metal occurrence speciation: To quantify heavy metal speciation, open the stack of the eight elemental surface scans (with the sample area divided or the particle size region of interest further divided in the previous steps), and click Image-Stack-Stack toimages to restore the stack to a single elemental surface scan image. For each elemental surface scan image, click Image-Transform-Image to Results to obtain the digitized surface scan image (theoretically, a larger number indicates a higher content of the element, and a number of 0 indicates the absence of the element). Copy the digitized surface scan of each element obtained to an Excel spreadsheet, delete the first two header columns, and use the COUNTIFS function to calculate the number of pixels where each element in the CO-Cu(Pb), C-Ca-O-Cu(Pb), Fe-O-Cu(Pb), Al-Si-O-Cu(Pb), and Al-Si-Fe-O-Cu(Pb) combinations is simultaneously greater than 0 (or a specific value), as well as the number of heavy metals Cu and Pb being greater than 0 (or a specific value). Use the percentage of the number of pixels obtained for each combination to the number of Cu(Pb) pixels to quantify the four heavy metal forms: organic bound state, iron oxide bound state, carbonate bound state, and aluminosilicate bound state.

[0056] Experimental Example 1

[0057] Effects of heavy metal speciation over time and particle size: The method mentioned in this invention can effectively obtain the effects of organic matter culture time on the four speciations of Cu and Pb. Figure 5 ), water incubation time ( Figure 6 ) and particle size variation ( Figure 7 The effect is as follows:

[0058] like Figure 5 As shown, after adding three types of organic matter (BC, LF, and RS) for 60 days of cultivation, the organically bound and carbonate-bound Cu and Pb increased (10.16%-12.49% and 11.37%-13.88%, respectively), while the iron oxide and silicate-bound Cu and Pb decreased (9.28%-11.30% and 11.01%-12.53%, respectively). This trend is reasonable, primarily because of the increase in soil organic matter. As shown in Table 1, the soil organic matter content increased from 18.6 g / kg to 34.23 g / kg after adding rice straw, which may have led to a corresponding increase in organically bound Cu and Pb. Furthermore, to further illustrate the effectiveness of this method, samples before and after cultivation with the three types of organic matter were tested using synchrotron X-ray absorption fine spectroscopy (Beijing XAFS1W1B experimental station), and linear fitting (LCF) analysis was performed on the data using Athena software provided at the experimental station, yielding the following results: Figure 8 The results are shown in Table 4. These experimental results indicate that organically bound Cu increased after culturing, while iron oxide-bound Cu decreased, consistent with the conclusions obtained using the method of this invention. Figure 8 The fitted spectra are shown in Table 4 (where R-factor < 0.01 and χ² < 0.002 indicate a good fit). This suggests that during cultivation, Cu and Pb may have transferred from the iron oxide and aluminosilicate components to the newly added organic matter.

[0059] like Figure 6 As shown, after culturing with the addition of three types of water, the method of this invention reveals that the organically bound Cu and Pb increased (7.00%-8.33%) after 90 days of culture, while the iron oxide-bound Cu and Pb decreased (5.69%-10.22%) after 90 days of culture. Clearly, the changes in these two forms of bound Cu and Pb after 90 days of culture with the three types of water were smaller than those after 60 days of culture with the three types of organic matter. Furthermore, the changes in carbonate and silicate-bound Cu and Pb before and after culture were minimal. This indicates that the method used in this invention can distinguish the degree of influence of exogenously added organic matter and water on the heavy metals Cu and Pb; that is, the effect of exogenously added water on the form of Cu and Pb is smaller than that of exogenously added organic matter.

[0060] like Figure 7As shown, the method of this invention reveals the differences in the four forms of Cu and Pb among soil particles of three sizes in uncultured soil and four groups of samples (CK, BC-60, LF-60, and RS-60) after 60 days of culture with three types of organic matter. For example, in all four groups of samples, the content of organically bound Cu was highest in 0-2 μm particles, followed by 2-20 μm, and finally 20-53 μm. This pattern is consistent with the pattern of organic matter content in soil particles of these three sizes, i.e., the smaller the particle size, the higher the organic matter content (Table 5), indicating that the results analyzed by the method of this invention are reasonable to a certain extent. Furthermore, after 60 days of culture with organic matter, the content of organically bound Cu increased the most in 0-2 μm particles (from 38.7% to 44.5%, 52.2%, and 54.4%, respectively), indicating that the method of this invention can further clarify... Figure 5 The increase in organically bound Cu reflected after cultivation is mainly observed in soil particles with a diameter of 0-2 μm.

[0061] Table 1. Basic physicochemical properties of original soil and soil after cultivation.

[0062]

[0063] Table 2. Mineral Composition Analysis by X-ray Diffraction

[0064]

[0065] Table 3. Operational steps of the improved Tessier continuous extraction method.

[0066]

[0067] Table 4 shows the linear fitting values ​​of organically bound Cu and iron-bound Cu before and after culture of RS, LF, and BC organic matter.

[0068]

[0069] Table 5 Organic matter content of three particle sizes in uncultured native soil

[0070]

Claims

1. An in-situ analytical method for determining the spatial distribution and occurrence forms of heavy metals in soil, characterized in that: The method includes the following steps: S1: Select heavily polluted sites to collect soil samples and perform pretreatment, including air-drying the collected samples and then crushing and sieving them; S2: After applying exogenous organic matter and water to the sample and culturing it, samples are taken periodically; S3: Determine the basic physicochemical properties of the sample and the heavy metal speciation extracted by chemical reagents; S4: Perform SEM-EDS testing on the air-dried and sieved sample from step S1 above to obtain the sample morphology and the surface distribution of various common soil elements and heavy metals; the common elements measured are C, O, Al, Fe, Ca, and Si; the heavy metals are Cu and Pb. S5: Analyze the soil solid phase composition and the definition of heavy metal speciation by chemical extraction methods in step S3 above, and classify the heavy metal speciation in the site soil into four categories: organic-bound, iron oxide-bound, carbonate-bound, and aluminosilicate-bound. Among them, the C-Ca-O-heavy metal element superposition area in the EDS surface scan results is classified as carbonate-bound heavy metal, i.e., inorganic carbon-bound heavy metal; the CO-heavy metal superposition area of ​​all carbon-bound heavy metals in the soil is subtracted from the C-Ca-O-heavy metal superposition area of ​​inorganic carbon-bound heavy metal, and is classified as organic-bound heavy metal; Fe-O-heavy metal is classified as iron oxide-bound; Al-Si-O-heavy metal minus Fe-containing silicate minerals is classified as aluminosilicate-bound. S6: Perform image segmentation on the sample morphology obtained in step S4 to distinguish between the background region and the sample region. S7: Apply the sample area divided in step S6 to the surface distribution of conventional elements and heavy metal elements measured in step S4 to obtain the surface distribution of soil elements within the sample area. S8: Based on the distribution of the six elements in the sample area in step S7 above, calculate the percentage of the pixel area of ​​the overlapping part in step S5 above to the area of ​​the heavy metal pixels, thereby quantifying the relative content of each form of heavy metal element to the total heavy metal elements. S9: Perform image segmentation again on the sample area and the distribution of the six elements corresponding to the area in steps S6 and S7 above to obtain soil particles of different sizes; repeat the steps described in steps S5 and S8 above to obtain the relative content of the four heavy metal element forms in soil particles of different sizes. S10: Perform the above steps S4-S9 on the samples before and after the culture of exogenous organic matter and water in step S2 to obtain the variation of the four forms of heavy metals with culture time and the distribution pattern in different particle sizes.

2. The method according to claim 1, characterized in that: In step S3: the basic physicochemical properties of the soil sample are determined, including pH, organic matter, clay mineral identification, carbonate content, conventional element content, and heavy metal content; the heavy metal speciation is determined using conventional chemical methods, including the continuous extraction of six soil heavy metal speciations—surface-bound, carbonate-bound, humic acid-bound, amorphous iron oxide-bound, crystalline iron oxide-bound, and residual—using appropriate chemical reagents through an improved Tessier sequential extraction method.

3. The method according to claim 2, characterized in that: The content of heavy metal elements was higher than the EDS minimum detection limit, which is about 0.1% by mass.

4. The method according to claim 3, characterized in that: In step S5: the four types of heavy metals, namely organic bound state, iron oxide bound state, carbonate bound state and aluminosilicate bound state, are mainly present in the four soil components composed of six elements: C, O, Fe, Ca, Al and Si. This corresponds to the element distribution results obtained by EDS test in step S4 above. The distribution of the four forms is represented by the overlapping part of the spatial distribution of heavy metals and these six elements.

5. The application of the method as described in any one of claims 1 to 4 in farmland soil contaminated with high concentrations of heavy metals.

6. The application according to claim 5, characterized in that: The method can analyze the distribution and morphological characteristics of heavy metals in situ, quantify the dynamic changes of heavy metal morphology on soil organic-mineral components under the influence of water and organic matter input, and the morphological changes in soil aggregates of different particle sizes.

Images