Soil heavy-metal accumulation predicting method employing emission inventory and receptor model

Abstract

The present application relates to the technical field of heavy-metal pollution remediation, and relates in particular to a soil heavy‐metal accumulation predicting method employing an emission inventory and a receptor model. The method comprises: using atmospheric dust deposition, irrigation water, chemical fertilizers and pesticides as input flux sources of heavy metals to farmland soil, using surface runoff and crops as output fluxes, and constructing an input-output flux inventory of heavy-metal pollutants to clarify a dynamic balance relationship of soil heavy-metal accumulation; and continuously collecting and monitoring of soil samples. The invention provides crucial assistance in determining the transport balance of heavy metals in farmland areas impacted by non-ferrous metal smelting and beneficiation slag sites and in identifying sources of soil heavy-metal pollution, and offers theoretical guidance for subsequent soil heavy-metal remediation and targeted control.

Description

A method for predicting soil heavy metal accumulation based on emission inventory and receptor model

[0001] This application claims priority to a Chinese patent application filed with the Patent Office of China on January 10, 2024, with application number 202410036627.6 and invention name “A method for predicting soil heavy metal accumulation based on emission inventory and receptor model”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the technical field of heavy metal pollution control, and specifically to a method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model. Background Art

[0003] Heavy metal concentrations in soils primarily come from two sources: parent materials and human input. Excessive accumulation of heavy metals in soil not only impacts the soil ecosystem but also accumulates in the human environment through the food chain, ultimately endangering human health.

[0004] Major soil pollutants include lead, zinc, arsenic, copper, and some organic pollutants. While researchers currently have detailed information on soil pollution, they lack the ability to identify pollutant sources and predict heavy metal accumulation in soil. Furthermore, the quantitative relationship between these two factors remains largely unexplored. Therefore, developing effective and rational calculation methods to predict heavy metal accumulation in soil and quantitatively identify its sources is crucial for precise remediation and management of farmland soils.

[0005] Identifying the source categories and contribution rates of heavy metals in the soil based on the correlation between the content of heavy metals in the soil and the pollution characteristics is called source apportionment. Source apportionment studies usually use three methods: source list method, receptor model method and diffusion model method. Among them, the source list method estimates the emission flux of different sources based on the emission levels of different pollution sources. This calculation method is simple and clear, but because historical data is difficult to collect, it is impossible to systematically and accurately count various emission sources. The diffusion model method evaluates the contribution of different source categories to soil heavy metals based on the heavy metal emission pollutant list and the pollutant transmission process. However, since the heavy metal emission and migration processes are complex and difficult to count, it is difficult to establish a direct relationship between pollution sources and soil through pollutants, so the application of this method is also subject to great limitations.

[0006] To address the limitations of the previous two methods, the receptor model method uses source-indicating heavy metals in soil samples and pollution sources to qualitatively identify pollution sources and quantitatively calculate the contribution of different pollution sources to soil heavy metal concentrations. Existing receptor models primarily include positive matrix factorization (PMF), the UNMIX model, absolute principal component analysis / multivariate linear regression (APCS-mLR), the isotope ratio method, and advanced statistical algorithms such as the finite mixture distribution model (FMDM) and random forest. Among these models, PMF analysis is widely used because its factor matrix is ​​constrained to non-negative values, yielding more meaningful factors. This model was first applied to the source apportionment of atmospheric particulate matter, and in recent years, researchers have increasingly attempted to apply it to soil and sediment. Compared to the previous two methods, the receptor model method does not require extensive historical information and ignores the transport process of heavy metals, directly measuring soil heavy metal concentrations. Consequently, the receptor model method has gained widespread application in soil heavy metal source apportionment. Although the receptor model has a certain monitoring effect on the content of heavy metals in soil, it cannot dynamically describe the changes of heavy metals in soil from the temporal and spatial levels.

[0007] Establishing an inventory of input and output fluxes is a useful method for studying the dynamics of heavy metals. The main input pathways for heavy metals in farmland soils include atmospheric dust, irrigation water, and pesticides and fertilizers, while the main output pathways are surface runoff, infiltration, and crop output. While heavy metal accumulation is discussed by calculating the input-output flux balance, this approach ignores the contribution of natural sources (soil parent material) to soil heavy metal content and lacks more detailed source analysis, such as the quantitative contribution of transportation and industrial sources. Summary of the Invention

[0008] The purpose of this application is to provide an effective source identification and flux prediction method for farmland soil contaminated by heavy metals, to provide more accurate source analysis results for farmland soil heavy metal pollution, and to make reasonable predictions.

[0009] This application takes heavy metals in farmland soil in the impact area of ​​non-ferrous metal smelting sites as a research example.

[0010] To achieve the above technical objectives and effects, this application is implemented through the following technical solutions:

[0011] This application provides a method for predicting soil heavy metal accumulation based on emission inventory and receptor model, including the following steps:

[0012] S1: By calculating the spatiotemporal variations of the accumulated flux of heavy metals in surface soil, and taking atmospheric dust, irrigation water, fertilizers and pesticides as the input flux sources of heavy metals in farmland soil, and surface runoff water and crops as the output flux sources, an inventory of heavy metal pollutant input and output fluxes was constructed to explore the dynamic equilibrium relationship of heavy metal accumulation in soil; the depth of the surface soil is 0-20 cm.

[0013] S2: The sources of heavy metals in farmland soil in the impact area of ​​non-ferrous metal smelting sites are classified as: atmospheric dust, irrigation water, fertilizers and pesticides;

[0014] The export pathways of heavy metals from farmland soil are: surface runoff and crops;

[0015] Heavy metal input flux and output flux are the mass of heavy metal input and output per unit area of ​​farmland soil in the impact area of ​​non-ferrous metal smelting sites, respectively, in g / y·ha;

[0016] Calculating the heavy metal input flux and the heavy metal output flux of the monitoring area;

[0017] S3: Based on the calculation results of step S2, sort out the input flux and output flux lists, and calculate the annual heavy metal input and output balance per unit area of ​​the surface layer (0-20cm) of the farmland soil in the affected area of ​​the non-ferrous metal smelting site by establishing the list. The specific calculation formula is shown in formula (1): Δsoil=∑inputs-∑outputs Formula (1)

[0018] In formula (1): Δsoil is the annual change of heavy metals in soil per unit area;

[0019] ∑inputs and ∑outputs are the input flux and output flux of heavy metals per unit area of ​​soil calculated in step S2, respectively, in units of g / y·ha;

[0020] S4: Calculate the heavy metal accumulation flux according to the mass balance formula (1) in step S3, and calculate the annual accumulation rate of heavy metals per unit area of ​​farmland soil in the affected area of ​​the non-ferrous metal smelting site by formula (2);

[0021] In formula (2):

[0022] In formula (2): DV soil is the accumulation rate of heavy metals per unit mass of soil, in mg / y·kg;

[0023] Δ soil is the annual cumulative flux of heavy metals per unit area in soil, in g / y·ha;

[0024] h is the soil depth of the monitoring area, 1m;

[0025] ρ soil The average soil density in the monitoring area;

[0026] The p soil 1540kg / m 3 ;

[0027] S5: Using the positive definite matrix factorization model PMF, the content of heavy metals in the soil surface layer in step S1 is taken as the research object, data analysis is performed, several factors are extracted, and the factors are identified as different source categories using identification components. The specific contribution of different factors to the content of heavy metals in the soil is then calculated through multiple linear regression. The specific formula is shown in formula (8):

[0028] In formula (8), x ij is the concentration of the jth heavy metal in the i-th sample, in mg / kg;

[0029] p is the number of factors affecting the heavy metal concentration of the sample;

[0030] g ik represents the mass concentration of the kth factor to the i-th sample;

[0031] f kj is the mass concentration of the jth element in the i-th sample;

[0032] e ij represents the residual between the i-th sample and the j-th element;

[0033] The objective function Q is minimized using the weighted least squares method, as shown in formula (9), and the model results are obtained;

[0034] In formula (9), u ij is the uncertainty value of the jth heavy metal in the i-th sample; it is related to laboratory conditions and test methods and is quantified using formula (10):

[0035] In formula (10), δ is the standard deviation of the relationship between heavy metal concentrations, and MDL is the method detection limit;

[0036] Furthermore, the step S1 specifically includes:

[0037] (1) Soil

[0038] Sampling rules: A five-point sampling method is used, in which samples are collected at the four vertices and the center of a square and then mixed; the sampling depth is 0-20 cm (topsoil); in the entire monitoring area, the sampling point distribution complies with the following principles: starting from the non-ferrous metal smelting slag field, a sampling point is established every 200 meters on the migration path, and the sampling point locations are shown in Figure 1.

[0039] The soil sample processing method includes: air drying the soil samples, then sieving all soil samples with a 2 mm nylon mesh, and storing the mesh in a polyethylene bottle; a portion of each sample is further ground into a 0.15 mm nylon mesh, and after digestion, the total amount of heavy metals is analyzed;

[0040] The specific steps of digestion are as follows: take 0.1g sample into a digestion tank, add 6mL nitric acid, pre-treat in an acid remover at 120℃ for 30min, remove and cool, add 1mL nitric acid, 2mL hydrofluoric acid, and 3mL hydrochloric acid in a microwave instrument, set the temperature time gradient to 150℃ for 10min, 180℃ for 5min, and 200℃ for 25min; after the microwave ends, remove the sample into an acid remover at 170℃ for 30min, during which time 1mL perchloric acid is added; remove the acid to about 2mL, cool and adjust the volume to 25mL, and then use an inductively coupled plasma mass spectrometer (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium).

[0041] (2) Surface water

[0042] Sampling rules: Surface water is divided into river water, irrigation water, and surface runoff water;

[0043] The river water sampling method is as follows: sampling points are set up at the upper, middle and lower reaches of the river, and river water samples are collected using polyethylene bottles, with a sampling volume of 500 mL each time;

[0044] The irrigation water sampling method is as follows: when farmers irrigate, they collect irrigation water samples using polyethylene bottles, with a sampling volume of 500 mL each time;

[0045] The surface runoff water sampling method is as follows: the runoff from the farmland outlet to the river is collected at the farmland outlet using a polyethylene bottle, and the flow rate is detected and recorded at the same time;

[0046] The surface water sample processing method includes: for each water sample, sealing it, shaking it evenly, and transporting it back to the laboratory for digestion;

[0047] The specific steps of digestion are as follows: take a water sample into a crucible, add 6 mL of nitric acid and 2 mL of hydrogen peroxide, cover it, place it on a hot plate and heat it at 120°C for two hours, remove the cover, continue heating until about 5 mL of the solution remains, remove it and adjust the volume, and then use an inductively coupled plasma mass spectrometer (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium).

[0048] (3) Atmospheric dust

[0049] The atmospheric dust sampling method includes: starting from the non-ferrous metal smelting slag field, setting up atmospheric dust collection points along the migration path, placing dust collection cylinders 5 meters above the ground to prevent suspended matter in the soil from affecting the collection of atmospheric dust, adding 5 mL of ethylene glycol to each dust collection cylinder to prevent bacterial growth and the influence of exogenous substances on sample composition; and adding 2% HNO3 to prevent changes in element types. When collecting samples, dry and wet sediments are not separated, and the samples are sealed in polyethylene bottles and sent to the laboratory for processing as soon as possible.

[0050] The atmospheric dust sample processing method includes: placing the atmospheric dust sample for 2-3 days, centrifuging it in a centrifuge at 3500 rpm for 10 minutes, transferring the supernatant to a glass bottle, and measuring its volume; transferring the remaining sediment to a beaker, drying it at 60°C to a constant weight, and recording its mass; the supernatant is the wet sediment sample; the sediment is the dry sediment sample; the treated wet and dry sediments are digested separately and the total amount of heavy metals is detected;

[0051] The digestion method of wet deposition is consistent with that of surface water. The specific digestion steps of dry deposition are as follows: take 0.1g sample into a digestion tank, add 5mL hydrochloric acid, 5mL hydrofluoric acid, and 1mL hydrogen peroxide into a microwave instrument, set the temperature time gradient to 150℃ for 10min, 180℃ for 5min, and 200℃ for 25min; after the microwave is finished, use an acid remover to remove the acid at 170℃ for 30min, during which time 1mL perchloric acid is added; remove the acid to about 2mL, cool and adjust the volume to 25mL, and then use an inductively coupled plasma mass spectrometer (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium).

[0052] (4) Crops

[0053] The crop sampling method includes: sampling the entire corn plant during the harvest season, with sampling points evenly distributed within the monitoring area, removing as much soil as possible from the roots, and then splitting the corn plant into three parts: roots, stems and leaves, and fruits. The samples are then collected separately in sample bags and returned to the laboratory for processing as soon as possible.

[0054] The crop sample processing method includes: first rinsing the collected corn samples (including roots, stems, leaves, and fruits) with tap water to remove dirt and impurities, then repeatedly rinsing with deionized water, drying in an oven at 105°C for 2 hours, and then completely drying at 60°C for 48 hours, and recording the mass of the dried crops; grinding the dried samples, and then testing the total amount of heavy metals after digestion;

[0055] The specific digestion steps are as follows: about 0.1 g of a sample is taken into a digestion tank, 8 mL of nitric acid is added and soaked overnight, 1 mL of hydrogen peroxide is then added, and after a reaction period, the sample is placed on a microwave machine, and a temperature-time gradient is set to 150° C. for 10 minutes and 190° C. for 25 minutes; the power is determined by the number of tanks; after the microwave ends, the sample is acid-dried at 170° C. in an acid-dried instrument for 30 minutes until about 2 mL of the sample remains, the sample is removed and cooled to a constant volume, and then the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium) is tested using an inductively coupled plasma mass spectrometer (ICP-MS).

[0056] (5) Fertilizers and pesticides

[0057] According to the farming habits of local farmers, six fertilizer and pesticide samples were obtained locally at different growth stages of corn. The fertilizer was stored in sealed bags and the pesticide in clean polyethylene bottles and sent back to the laboratory for processing as soon as possible;

[0058] The pesticide samples included four types: Spodoptera litura nuclear polyhedrosis virus, clothianidin, nicosulfuron, and nicosulfuron; the fertilizer samples included urea and compound fertilizer.

[0059] The sample processing method for fertilizers and pesticides includes: testing the total amount of heavy metals after sample digestion. The specific steps of digestion are: taking 5 mL of sample into a 100 mL beaker, adding 50% nitric acid to digest until nearly dry, dissolving it with 5% nitric acid solution and making the volume 50 mL, and then using an inductively coupled plasma mass spectrometer (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium).

[0060] Furthermore, the step S2 specifically includes: the specific calculation method is as shown in formulas (3) to (7):

[0061] ① Atmospheric dust input flux I At =(C w V w +C d W d )×100 / S formula (3);

[0062] In formula (3):

[0063] I Atis the flux of heavy metals entering the farmland soil of the monitoring area through atmospheric dust, in g / ha·y;

[0064] C w 、C d are the concentrations of heavy metals in wet deposition and dry deposition, in units of ug / L and ug / g, respectively;

[0065] V w 、W d are wet deposition and dry deposition, in L and g respectively;

[0066] S is the area of ​​the sampling bottle mouth, unit is cm 2 ; 100 is the unit conversion factor.

[0067] ② Pesticide and fertilizer input flux

[0068] In formula (4): I Fer is the input flux of heavy metal fertilizers and pesticides, in g / ha·y;

[0069] F i,j is the actual application rate of pesticides and fertilizers, in g / y·ha;

[0070] C i,j The content of elements in fertilizers and pesticides, in mg / kg or ug / mL;

[0071] n is the number of fertilizer types applied at the sampling point.

[0072] ③ Irrigation water input flux I Ir =VC i 10 -6 Formula (5);

[0073] In formula (5):

[0074] I Ir is the input of heavy metals (i) in irrigation water, in g / y·ha;

[0075] V is the amount of irrigation water applied, in L / y·ha;

[0076] C i is the concentration of element (i) in irrigation water, in μg / L.

[0077] ④Surface runoff output flux

[0078] In formula (6):

[0079] O Runis the output of heavy metals (i) in runoff, in g / y·ha;

[0080] C i is the concentration of heavy metal (i) in runoff, in μg / L;

[0081] V is the surface runoff volume, in L;

[0082] R is the ratio of mean annual precipitation to rainfall during the study period, unitless;

[0083] S is the sampling bottleneck area, unit is cm 2 .

[0084] ⑤Crop output flux

[0085] In formula (7):

[0086] O Crop is the output of heavy metal (i) in crop (j), in g / y·ha;

[0087] N e,j is the number of root parts of the annual crop (j);

[0088] C i,e,j is the concentration of heavy metal (i) in the root of crop (j), in μg / g;

[0089] N n,j is the content of the stem and leaf part of the annual crop (j), in g / y·ha;

[0090] C i,n,j is the concentration of element (i) in the stem and leaf part (j) of the crop, in μg / g;

[0091] N p，j is the number of fruit parts (p) per year, in g / y·ha;

[0092] C i,p,j is the concentration of heavy metal i in the fruit part of the crop (p), in μg / g;

[0093] n is the number of harvested parts.

[0094] Beneficial effects of this application:

[0095] Establish an emission inventory to reveal the dynamic equilibrium relationship of heavy metal accumulation in soil: By constructing an inventory of input and output fluxes of heavy metal pollutants, this application can quantitatively calculate the input and output fluxes of heavy metals in farmland soil, which helps to reveal the dynamic equilibrium relationship of heavy metal accumulation in soil and predict the accumulation changes of heavy metals in farmland soil. The list of input sources and output pathways mainly includes atmospheric dust, irrigation water, and fertilizers and pesticides as input flux sources of heavy metals in farmland soil, and surface runoff and crops as output fluxes. By calculating the balance relationship of heavy metal input and output fluxes, the source and destination of heavy metals can be quantitatively calculated.

[0096] This application attempts to introduce the PMF model to further discuss the sources of heavy metal pollution in farmland soil. Emission inventory results indicate that the primary source of heavy metals in soil comes from atmospheric dust, a direct reflection of the test data. However, the PMF model discusses the inherent mathematical logic of heavy metal content in soil. In fact, this method also helps explain the sources of heavy metals in atmospheric dust within the monitoring area, providing a detailed breakdown of regional heavy metal source analysis.

[0097] Therefore, this application combines the receptor model (PMF model) with the emission inventory. Based on the investigation of heavy metal accumulation changes, it further analyzes the sources of heavy metal accumulation, quantitatively calculates the contribution of traffic sources, natural sources, industrial sources, agricultural sources, etc., and combines source analysis with heavy metal accumulation prediction. This technical solution can provide theoretical guidance for the prevention and control of soil heavy metal pollution and precise management. Based on this data, effective pollution control measures and management strategies can be formulated to reduce the accumulation of heavy metals in soil and reduce the risks to farmland ecosystems and human health.

[0098] Of course, any product implementing the present application does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0100] Figure 1 is a schematic diagram of on-site sample collection;

[0101] Figure 2 is a schematic diagram of the layout of atmospheric dust collection cylinders;

[0102] Figure 3 is a schematic diagram of the layout of pesticide and fertilizer collection points;

[0103] Figure 4 is a schematic diagram of the layout of irrigation water collection points;

[0104] Figure 5 is a schematic diagram of the layout of surface runoff collection points;

[0105] Figure 6 is a schematic diagram of the layout of crop collection points. DETAILED DESCRIPTION

[0106] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0107] Example 1

[0108] The method described in this embodiment for predicting soil heavy metal accumulation based on an emission inventory and a receptor model includes the following steps:

[0109] S1: By calculating the spatiotemporal variations of heavy metal accumulation fluxes in surface soil (0-20 cm), and taking atmospheric dust, irrigation water, and fertilizers and pesticides as the input flux sources of heavy metals in farmland soil, and surface runoff and crops as the output fluxes, an inventory of heavy metal pollutant input and output fluxes was constructed to explore the dynamic balance relationship of heavy metal accumulation in soil;

[0110] S2: The sources of heavy metals in farmland soil in the area affected by the nonferrous metallurgical site are classified as follows: atmospheric dust, irrigation water, fertilizers and pesticides;

[0111] The export pathways of heavy metals from farmland soil are surface runoff and crops. The heavy metal input and output fluxes are the mass of heavy metals input and output per unit area of ​​soil in the affected area of ​​the nonferrous metallurgy site per year, respectively, in g / y·ha.

[0112] Calculate the three heavy metal input fluxes of atmospheric dust, pesticides and fertilizers, and irrigation water, and the two heavy metal output fluxes of surface runoff and crops in the monitoring area;

[0113] S3: Based on the calculation results of S2, sort out the input flux and output flux lists, and calculate the annual heavy metal input and output balance per unit area of ​​farmland soil by establishing the list. The specific calculation formula is shown in (1): Δsoil=∑inputs-∑outputs Formula (1);

[0114] In formula (1): Δsoil is the annual change of heavy metals in soil per unit area;

[0115] ∑inputs and ∑outputs are the input flux and output flux of heavy metals per unit area of ​​soil calculated in step S2, respectively, in units of g / y·ha;

[0116] S4: According to the mass balance formula (1) in step S3, the heavy metal accumulation flux is calculated, and the annual accumulation rate of heavy metals per unit mass of farmland soil is calculated by the following formula:

[0117] Where:

[0118] In formula (2): DV soil is the accumulation rate of heavy metals per unit mass of soil, in mg / y·kg;

[0119] Δ soil is the annual cumulative flux of heavy metals per unit area in soil, in g / y·ha;

[0120] h is the soil depth of the monitoring area, 1m;

[0121] ρ soil The average soil density in the monitoring area is 1540 kg / m 3 ;

[0122] S5: Using the positive definite matrix factorization model PMF, the content of heavy metals in the soil surface layer in step S1 is taken as the research object, data analysis is performed, several factors are extracted, and the factors are identified as different source categories using identification components. The specific contribution of different factors to the content of heavy metals in the soil is then calculated through multiple linear regression. The specific formula is shown in formula (8):

[0123] In formula (8), x ij is the concentration of the jth heavy metal in the i-th sample, in mg / kg;

[0124] p is the number of factors affecting the heavy metal concentration of the sample;

[0125] g ik represents the mass concentration of the kth factor to the i-th sample;

[0126] f kj is the mass concentration of the jth element in the i-th sample;

[0127] e ij represents the residual between the i-th sample and the j-th element;

[0128] The objective function Q is minimized using the weighted least squares method, as shown in formula (9), and the model results are obtained;

[0129] In formula (9), u ij is the uncertainty value of the jth heavy metal in the i-th sample; it is related to laboratory conditions and test methods and is quantified using formula (10):

[0130] In formula (10), δ is the standard deviation of the relationship between heavy metal concentrations, and MDL is the detection limit of the method.

[0131] In this embodiment, step S1 specifically includes:

[0132] (1) Soil sampling rules: A five-point sampling method was used, in which samples were collected at the four vertices and the center of a square and then mixed; the sampling depth was 0-20 cm; throughout the monitoring area, the sampling points were distributed in accordance with the following principles: starting from the non-ferrous metal smelting slag field, a sampling point was established every 200 meters on the migration path, and the sampling points were shown in Figure 1.

[0133] Sample processing method: The samples were air-dried, and the soil samples were air-dried. All air-dried soil samples were then sieved using a 2 mm nylon mesh and stored in polyethylene bottles. A portion of each sample was further ground into a 0.15 mm nylon mesh and digested before analysis for the total amount of heavy metals.

[0134] The digestion process involved pre-treating 0.1 g of sample in a digestion vessel, adding 6 mL of nitric acid, and pre-treating the sample in a microwave oven at 120°C for 30 minutes. The sample was then cooled and added with 1 mL of nitric acid, 2 mL of hydrofluoric acid, and 3 mL of hydrochloric acid. The sample was then placed in a microwave oven with a temperature gradient of 150°C for 10 minutes, 180°C for 5 minutes, and 200°C for 25 minutes. After the microwave oven was completed, the sample was pre-treated at 170°C for 30 minutes, during which time 1 mL of perchloric acid was added. The sample was then pre-treated to approximately 2 mL, cooled, and diluted to 25 mL. The concentrations of heavy metals (lead, zinc, arsenic, copper, and cadmium) were then determined using an inductively coupled plasma mass spectrometer (ICP-MS).

[0135] (2) Surface water

[0136] Sampling rules: Surface water is divided into river water, irrigation water, and surface runoff water.

[0137] For river water, sampling points were set up at the upper, middle and lower reaches of the river, and river water samples were collected using polyethylene bottles, with a sampling volume of 500 mL each time;

[0138] For irrigation water, 500 mL of irrigation water samples were collected using polyethylene bottles when farmers were irrigating.

[0139] For surface runoff water: runoff from the farmland outlet to the river, use polyethylene bottles to collect surface runoff water samples at the farmland outlet, and at the same time detect the flow rate and keep records.

[0140] Sample processing method: For all the above water samples, seal them and shake them well, then transport them back to the laboratory for digestion. The specific steps of digestion are as follows: take the sample to a crucible, add 6mL of nitric acid and 2mL of hydrogen peroxide, cover it, place it on a hot plate and heat it at 120℃ for two hours, remove the cover, and continue heating until about 5mL of solution remains, remove it and adjust the volume, and then use inductively coupled plasma mass spectrometry (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, cadmium).

[0141] (3) Atmospheric dust

[0142] Sampling method: Starting from the non-ferrous metal smelting slag field, set up atmospheric dust collection points on the migration path, and place the dust collecting cylinder 5 meters above the ground to avoid the influence of suspended matter in the soil on the collection of atmospheric dust. Add 5mL of ethylene glycol to each dust collecting cylinder to avoid the influence of bacteria and exogenous substances on the sample composition; then add 2% HNO3 to prevent the change of element types. When collecting samples, dry and wet sediments are not separated. They are packaged in polyethylene bottles and sent to the laboratory for processing as soon as possible.

[0143] Sample processing method: The atmospheric dust sample is placed for 2-3 days, centrifuged at 3500rpm for 10 minutes, the supernatant is transferred to a glass bottle, and its volume is measured; the remaining sediment is transferred to a beaker, dried at 60°C to constant weight, and its mass is recorded; the supernatant is the wet precipitation sample; the treated dry and wet precipitation are digested separately and the total amount of heavy metals is detected.

[0144] The digestion method of wet deposition is consistent with that of surface water. The specific digestion steps of dry deposition are as follows: take 0.1g sample into a digestion tank, add 5mL hydrochloric acid, 5mL hydrofluoric acid, and 1mL hydrogen peroxide into a microwave instrument, set the temperature time gradient to 150℃ for 10min, 180℃ for 5min, and 200℃ for 25min; after the microwave is finished, use an acid remover to remove the acid at 170℃ for 30min, during which time 1mL perchloric acid is added; remove the acid to about 2mL, cool and adjust the volume to 25mL, and then use an inductively coupled plasma mass spectrometer (ICP-MS) to test the concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium).

[0145] (4) Crops

[0146] Sampling method: During the harvest season, the entire corn plant is sampled. The sampling points are evenly distributed within the monitoring area. The soil at the roots is removed as much as possible. The corn plant is then split into three parts: roots, stems and leaves, and fruits. The samples are then packed separately in sample bags and sent back to the laboratory for processing as soon as possible.

[0147] Sample processing method: The collected corn samples (including roots, stems, leaves, and fruits) were first rinsed with tap water to remove dirt and impurities, then repeatedly rinsed with deionized water, dried in an oven at 105°C for 2 hours, and then completely dried at 60°C for 48 hours. The mass of the crop after drying was recorded; the dried samples were ground into powder, and then digested and tested for the total amount of heavy metals.

[0148] The specific steps of digestion are as follows: take about 0.1 g of sample and put it into a digestion tank, add 8 mL of nitric acid and soak it overnight, then add 1 mL of hydrogen peroxide, wait for a while, put it on the microwave, set the temperature and time gradient to 150°C for 10 minutes and 190°C for 25 minutes; the power is determined by the number of tanks, after the microwave ends, the sample is acid-dried at 170°C in an acid-dried instrument for 30 minutes until the sample is about 2 mL left, then removed and cooled to a constant volume, and then the concentration of heavy metals (lead, zinc, arsenic, copper, cadmium) is tested using an inductively coupled plasma mass spectrometer (ICP-MS).

[0149] (5) Fertilizers and pesticides

[0150] According to the local farmers' farming habits, six fertilizer and pesticide samples were obtained locally at different growth stages of corn. The fertilizers were stored in sealed bags and the pesticides in clean polyethylene bottles and sent back to the laboratory for processing as soon as possible.

[0151] Sample processing method: Pesticide samples include four types: Spodoptera litura nuclear polyhedrosis virus sample, clothianidin chlorpyrifos sample, nicosulfuron sample, and nicosulfuron-pyraclostrobin sample; fertilizer samples include two types: urea sample and compound fertilizer sample.

[0152] The total amount of heavy metals was tested after sample digestion. The specific steps of digestion were as follows: 5 mL of sample was taken into a 100 mL beaker, 50% nitric acid was added to digest until almost dry, and the sample was dissolved with 5% nitric acid solution and the volume was fixed to 50 mL. The concentration of heavy metals (lead, zinc, arsenic, copper, and cadmium) was then tested using an inductively coupled plasma mass spectrometer (ICP-MS).

[0153] In this embodiment, the step S2 specifically includes: the specific calculation method is as shown in formulas (3) to (7);

[0154] ① Atmospheric dust input flux I At =(C w V w +C d W d )×100 / S (3);

[0155] In formula (3): I At is the flux of heavy metals entering the farmland soil of the monitoring area through atmospheric dust, in g / ha·y;

[0156] Cw 、C d are the concentrations of heavy metals in wet deposition and dry deposition, in ug / L and ug / g, respectively;

[0157] V w 、W d are wet deposition and dry deposition, in L and g respectively;

[0158] S is the area of ​​the sampling bottle mouth, unit is cm 2 ; 100 is the unit conversion factor.

[0159] ② Pesticide and fertilizer input flux

[0160] In formula (4): I Fer is the input flux of heavy metal fertilizers and pesticides, in g / ha·y;

[0161] F i,j is the actual application rate of pesticides and fertilizers, in g / y·ha;

[0162] C i,j The content of elements in fertilizers and pesticides, in mg / kg or ug / mL;

[0163] n is the number of fertilizers applied at the sampling point;

[0164] ③ Irrigation water input flux I Ir =VC i 10 -6 (5);

[0165] In formula (5):

[0166] I Ir is the input of heavy metals (i) in irrigation water, in g / y·ha;

[0167] V is the amount of irrigation water applied, in L / y·ha;

[0168] C i is the concentration of element (i) in irrigation water, in μg / L;

[0169] ④Surface runoff output flux

[0170] In formula (6):

[0171] O Run is the output of heavy metals (i) in runoff, in g / y·ha;

[0172] C i is the concentration of heavy metal (i) in runoff, in μg / L;

[0173] V is the surface runoff volume, in L;

[0174] R is the ratio of mean annual precipitation to rainfall during the study period, unitless;

[0175] S is the sampling bottleneck area, unit is cm 2 .

[0176] ⑤Crop output flux

[0177] In formula (7):

[0178] O Crop is the output of heavy metal (i) in crop (j), in g / y·ha;

[0179] N e，j is the number of root parts of the annual crop (j);

[0180] C i，e，j is the concentration of heavy metal (i) in the root of crop (j), in μg / g;

[0181] N n，j is the content of the stem and leaf part of the annual crop (j), in g / y·ha;

[0182] C i，n，j is the concentration of element (i) in the stem and leaf part (j) of the crop, in μg / g;

[0183] N p，j is the number of fruit parts (p) per year, in g / y·ha;

[0184] C i，p，j is the concentration of heavy metal i in the fruit part of the crop (p), in μg / g;

[0185] n is the number of harvested parts.

[0186] Example 2

[0187] Sample collection:

[0188] Taking a lead-zinc smelting industrial zone in Gejiu City, Yunnan Province, southwest China, as an example, we conducted a field survey and sampling of farmland in the area. All sampling points are shown in Figure 1.

[0189] Calculation of input and output fluxes in the impact area:

[0190] After experimental analysis of the collected samples, the corresponding calculation formula in step S2 is used.

[0191] 1. Input flux calculation

[0192] (1) Atmospheric dust input flux

[0193] Four dust collection cylinders are arranged within a 2 km range of the monitoring area, as shown in Figure 2.

[0194] Table 2-1 Atmospheric dustfall input flux

[0195] The deposition amount per hectare of farmland in the monitoring area is 38.253 kg. According to the calculation method of the input flux of heavy metals in atmospheric dustfall, the input fluxes of Pb, As, Cu, Cd and Zn in the monitoring area are calculated to be 226.43, 262.74, 77.51, 28.06 and 802.00 g / y·ha, respectively.

[0196] (2) Pesticide and fertilizer input flux

[0197] Table 2-2 Pesticide and fertilizer input flux

[0198] Four pesticides, including Spodoptera litura nuclear polyhedrosis virus (Spodoptera litura nuclear polyhedrosis virus), clothianidin, nicosulfuron, and nicosulfuron-pyraclostrobin, and two fertilizers, urea and compound fertilizer, were collected from farmland in the monitoring area. The sampling points for pesticides and fertilizers are shown in Figure 3 . Local farmers were surveyed about their annual pesticide and fertilizer usage, and the input fluxes of heavy metals from pesticides and fertilizers were calculated. The calculations, based on formula ②, showed that the input fluxes of Pb, As, Cu, Cd, and Zn into the farmland soil in the monitoring area were 0.07, 0.04, 0.71, 0.00, and 0.29 g / y·ha, respectively.

[0199] (3) Irrigation water input flux

[0200] Table 2-3 Irrigation water input flux

[0201] In 2023, the irrigation water volume per mu of farmland soil in the monitoring area was approximately 16,250 L. Based on the measurement of the average metal concentrations of the irrigation water samples obtained, the sampling points are shown in Figure 4. The annual irrigation water consumption of local farmers was surveyed. According to Formula ③, the input fluxes of Pb, As, Cu, Cd, and Zn in the farmland soil of the monitoring area were calculated to be 0.26, 2.72, 0.12, 0.01, and 0.88 g / y·ha, respectively.

[0202] 2. Output Flux Calculation

[0203] (1) Surface runoff output flux

[0204] Table 2-4 Surface runoff output flux

[0205] In 2023, based on reference data from the National Meteorological Science Data Center (National Meteorological Information Center - China Meteorological Data Network (cma.cn)), the average annual rainfall during the monitoring period (September 2022–September 2023) was 930 mm. The total rainfall during the monitoring period was 1596 mm, with an R value of 0.583, corresponding to Equation 4. The surface runoff sampling points are shown in Figure 5.

[0206] The calculated input fluxes of Pb, As, Cu, Cd and Zn in the monitoring area were 0.07, 0.13, 0.03, 0.02 and 0.39 g / y·ha, respectively.

[0207] The crop sampling points are shown in Figure 6. The output flux of heavy metals through corn crops was calculated using Formula ⑤, and the results are shown in Table 2-5.

[0208] Table 2-5 Crop output flux

[0209] Example 3

[0210] Create an input and output flux list

[0211] Table 3-1 Input and output flux list

[0212] Table 3-2 Heavy metal input and output flux balance

[0213] In summary, according to the emission inventory, the cumulative fluxes of Pb, As, Cu, Cd, and Zn in the monitoring area in 2023 were 180.03, 181.45, 57.64, 12.85, and 541.39 g / y·ha, respectively (negative values ​​indicate that the heavy metals in this element are in a purified state in that year); 3 As the average soil density, the soil from 0 to 100 cm was taken as the measurement object, and the cumulative fluxes of heavy metals Pb, As, Cu, Cd, and Zn per unit mass of the soil in the monitoring area were allocated as 116.93, 118.22, 37.44, 8.35, and 352.07 mg / kg*y, respectively.

[0214] Example 4

[0215] Receptor model

[0216] The PMF model was used to analyze surface soil heavy metal data. This study tested the PMF model with 2, 3, 4, 5, 6, and 7 contribution factors, running the model 20 times. Results showed that a factor of 4 yielded the optimal solution for heavy metal concentration resolution. Over 85% of soil samples had residual values ​​between -3 and 3.

[0217] Table 4-1 shows the residual analysis of the basic model run, the fitting coefficients of each element (R 2 ) were all above 0.9, indicating that the PMF model results were reliable. The PMF results divided the sources of soil heavy metals into four factors, namely factor 1, factor 2, factor 3, and factor 4, which accounted for 18.9%, 53%, 10.5%, and 17.6% of the total contribution, respectively.

[0218] Table 4-1 Residual analysis of PMF basic model results

[0219] The main contributing elements of factor 1 are Cd (51.4%), As (22.9%), and Zn (20.9%); the main contributing elements of factor 2 are Zn (59.7%), Pb (44.3%), and Cd (42.6%); the main contributing elements of factor 3 are Pb (38.2%); the main contributing elements of factor 4 are Pb (15.4%), Zn (19.4%), As (12.2%), and Cu (41.3%).

[0220] For PMF model analysis, the more elements and samples you have, the more accurate the results. This technical method provides a calculation guideline. Other solutions can refer to calculations for more elements.

[0221] In summary, the method provided in this application for predicting soil heavy metal accumulation based on emission inventory and receptor model takes atmospheric dust, irrigation water, fertilizers and pesticides as the input flux sources of heavy metals in farmland soil, and surface runoff and crops as the output flux. By constructing an input and output flux inventory of heavy metal pollutants to clarify the dynamic balance relationship of soil heavy metal accumulation, and continuously collecting and monitoring soil samples, it is of great help in determining the migration balance of heavy metals in the farmland impact area of ​​non-ferrous metallurgical slag yard and the source of soil heavy metal pollution, and provides theoretical guidance for subsequent soil heavy metal prevention and control and precise management.

[0222] The preferred embodiments of the present application disclosed above are intended only to help illustrate the present application. The preferred embodiments do not describe all details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made based on the content of this specification. This specification selects and describes these embodiments in detail to better explain the principles and practical applications of the present application, so that those skilled in the art can better understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model, characterized in that Including the following steps: S1: By calculating the spatio-temporal changes in the cumulative flux of heavy metals in the topsoil, and taking atmospheric dustfall, irrigation water, chemical fertilizers, and pesticides as the sources of the input flux of heavy metals in farmland soil, and surface runoff water and crops as the output flux, construct an inventory of the input and output fluxes of heavy metal pollutants to explore the dynamic balance relationship of heavy metal accumulation in the soil; S2: Classify the sources of heavy metals in the farmland soil in the affected area of the non-ferrous metal smelting and beneficiation site as: atmospheric dustfall, irrigation water, chemical fertilizers, and pesticides; The output paths of heavy metals in farmland soil are: surface runoff and crops; The heavy metal input flux and output flux are respectively the mass of heavy metals input and output per unit area per year in the farmland soil in the affected area of the non-ferrous metal smelting and beneficiation site, with the unit of g / y·ha; Calculate the heavy metal input flux and the heavy metal output flux of the monitoring area; S3: According to the calculation results of the step S2, sort out the inventory of the input flux and output flux, and calculate the annual heavy metal input-output balance per unit area of the topsoil in the affected area of the non-ferrous metal smelting and beneficiation site by establishing an inventory. The specific calculation formula is shown in Equation (1): Δsoil = ∑inputs - ∑outputs Equation (1); In Equation (1): Δsoil is the annual change amount of heavy metals in the soil per unit area; ∑inputs and ∑outputs are respectively the heavy metal input flux and output flux of the soil per unit area calculated in the step S2, with the unit of g / y·ha; S4: According to the mass balance formula (1) in step S3, calculate the heavy metal cumulative flux, and calculate the annual cumulative rate of heavy metals in the farmland soil in the affected area of the non-ferrous metal smelting and beneficiation site per unit area through formula (2); In formula (2): DV soil is the accumulation rate of heavy metals in soil per unit mass, with the unit of mg / y·kg; Δ soil is the annual cumulative flux of heavy metals in soil per unit area, with the unit of g / y·ha; h is the soil depth of the monitoring area, 1 m; ρ soil is the average density of the soil in the monitoring area; S5: Using the positive definite matrix factorization model PMF, taking the content of heavy metals in the soil surface layer in step S1 as the research object, performing data analysis, extracting several factors, using the identification components to identify the several factors as different source classes, and then calculating the specific contributions of different factors to the soil heavy metal content through multiple linear regression; the specific formula is shown in formula (8): In formula (8), x ij is the concentration of the j-th heavy metal in the i-th sample, with the unit of mg / kg; p is the number of factors affecting the heavy metal concentration of the sample; g ik represents the mass concentration of the k-th factor for the i-th sample; f kj is the mass concentration of the j-th element in the i-th sample; e ij represents the residual of the i-th sample and the j-th element; Minimize the objective function Q using the weighted least squares method, as shown in Equation (9), to obtain the model result; In Equation (9), u ij is the uncertainty value of the j-th heavy metal in the i-th sample; it is related to the laboratory conditions and testing methods and is quantified by Equation (10): In Equation (10), δ is the relational standard deviation of the heavy metal concentration, and MDL is the method detection limit.

2. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 1, wherein the ρ soil is 1540 kg / m 3 .

3. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 1, characterized in that, The step S1 includes the sampling and sample processing methods for various types of samples, and the various types of samples include soil, irrigation water, surface runoff, atmospheric dustfall, crops, chemical fertilizers, and pesticides.

4. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 3, wherein The sampling of the soil includes: adopting the five-point sampling method, which is to collect samples at the four vertices and the center of a square and then mix them; the sampling depth is 0 - 20 cm; in the entire monitoring area, the distribution of sampling points conforms to the following principle: starting from the non-ferrous metal smelting slag yard, establish a sampling point every 200 meters on the migration path; The sample processing method of the soil includes: air-drying the soil samples, and then screening all the air-dried soil samples with a 2 mm nylon sieve, and storing the sieve in a polyethylene bottle; a part of each sample is further ground to a 0.15 mm nylon sieve, and after digestion, the total amount of heavy metals is analyzed; The specific steps of digestion are as follows: Take 0.1 g of soil sample and place it in a digestion tank. Add 6 mL of nitric acid, and pre-treat it in a fume expelling instrument at 120 °C for 30 min. Take it down and cool. Add 1 mL of nitric acid, 2 mL of hydrofluoric acid, and 3 mL of hydrochloric acid into a microwave instrument. Set the temperature-time gradient as follows: keep it at 150 °C for 10 min, 180 °C for 5 min, and 200 °C for 25 min. After the microwave treatment, carry out acid expelling in a fume expelling instrument at 170 °C for 30 min, and add 1 mL of perchloric acid during this period. Expel the acid until about 2 mL remains, cool, and make up the volume to 25 mL. Then, use an inductively coupled plasma mass spectrometer to measure the concentration of heavy metals.

5. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 3, wherein: The surface water is divided into river water, irrigation water, and surface runoff water. The sampling method for the river water is as follows: Set sampling points at the upper, middle, and lower reaches of the river respectively. Collect river water samples with a polyethylene bottle, and the sampling volume is 500 mL each time. The sampling method for the irrigation water is as follows: Collect irrigation water samples with a polyethylene bottle when farmers are irrigating, and the sampling volume is 500 mL each time. The sampling method for the surface runoff water is as follows: For the runoff from the farmland outlet to the river, collect surface runoff water samples with a polyethylene bottle at the farmland outlet, and detect the flow rate and record it at the same time. The sample treatment method for the surface water includes: For each water sample, seal it and shake it well, then transport it back to the laboratory for digestion. The specific steps of digestion are as follows: Take a water sample in a crucible, add 6 mL of nitric acid and 2 mL of hydrogen peroxide, cover it, and heat it on a hot plate at 120 °C for two hours. Remove the cover and continue heating until the solution remains about 5 mL. Take it down and make up the volume. Then, use an inductively coupled plasma mass spectrometer to measure the concentration of heavy metals.

6. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 3, characterized in that The sampling method for the atmospheric dustfall includes: Starting from a non-ferrous metal smelting slag yard, set atmospheric dustfall collection points on the migration path. Place the dust collection cylinder at a position 5 meters above the ground to avoid the influence of suspended substances in the soil on the collection of atmospheric dustfall. Add 5 mL of ethylene glycol to each dust collection cylinder to avoid the influence of exogenous substances generated by bacterial growth on the sample components. Then add 2% HNO3 to prevent the change of element species. When collecting the sample, do not separate the wet and dry depositions. Package it with a polyethylene bottle and send it to the laboratory for treatment. The sample treatment method for the atmospheric dustfall includes: Let the atmospheric dustfall sample stand for 2 - 3 days, centrifuge it at a speed of 3500 rpm in a centrifuge for 10 min, transfer the upper clear liquid to a glass bottle, and measure its volume. Transfer the remaining precipitate to a beaker, dry it to a constant weight at 60 °C, and record its mass. The upper clear liquid is the wet deposition sample, and the precipitate is the dry deposition sample. After separately digesting the treated wet and dry deposition samples, detect the total amount of heavy metals. The digestion method for wet deposition samples is the same as that for surface water. The specific digestion steps for dry deposition samples are as follows: Take 0.1 g of dry deposition samples in a digestion tank, add 5 mL of hydrochloric acid, 5 mL of hydrofluoric acid, and 1 mL of hydrogen peroxide, place them in a microwave instrument, set the temperature-time gradient to hold at 150 °C for 10 min, 180 °C for 5 min, and 200 °C for 25 min; after the microwave is finished, carry out acid evaporation at 170 °C in an acid evaporator for 30 min, and add 1 mL of perchloric acid during this period; evaporate the acid until about 2 mL remains, cool and make up the volume to 25 mL, and then use an inductively coupled plasma mass spectrometer to measure the concentration of heavy metals.

7. The method for predicting the accumulation of heavy metals in soil based on an emission inventory and a receptor model according to claim 3, wherein The crops include corn.

8. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 3, wherein The sampling method for the crops includes: During the harvest season, take the entire plant of corn crops. The sampling points are evenly distributed within the monitoring area. Remove the soil from the roots, split the corn plants into three parts: roots, stems and leaves, and fruits, and pack them separately in sample bags, and send them back to the laboratory for processing; The sample processing method for the crops includes: The collected corn samples are first rinsed with tap water to remove soil and impurities, then repeatedly rinsed with deionized water, dried in an oven at 105 °C for 2 h, and then completely dried at 60 °C for 48 h, and record the mass of the dried crops; Grind the dried samples into powder, and then measure the total amount of heavy metals after digestion; The specific digestion steps are as follows: Take 0.1 g of the sample in a digestion tank, add 8 mL of nitric acid and soak overnight, then add 1 mL of hydrogen peroxide. After reacting for a while, put it on the microwave. Set the temperature-time gradient to 150 °C for 10 min and 190 °C for 25 min; after the microwave is finished, carry out acid evaporation of the sample at 170 °C in an acid evaporator for 30 min. When the sample is about 2 mL, take it down, cool and make up the volume, and then use an inductively coupled plasma mass spectrometer to measure the concentration of heavy metals.

9. The method for predicting the accumulation of heavy metals in soil based on the emission inventory and receptor model according to claim 3, wherein The sampling method for the chemical fertilizers and pesticides includes: At different growth stages of corn, obtain 6 samples of chemical fertilizers and pesticides. The chemical fertilizers are stored in sealed bags, and the pesticides are stored in clean polyethylene bottles, and send them back to the laboratory for processing; The pesticide samples include four kinds: Spodoptera litura nuclear polyhedrosis virus sample, thiamethoxam lambda-cyhalothrin sample, nicosulfuron sample, and nicosulfuron mefenpyr-diethyl sample. The chemical fertilizer samples include two kinds: urea sample and compound fertilizer sample; The sample processing method for the chemical fertilizers and pesticides includes: Measure the total amount of heavy metals after digesting the samples. The specific digestion steps are as follows: Take 5 mL of the sample in a 100 mL beaker, add 50% nitric acid and digest until nearly dry, dissolve with 5% nitric acid solution and make up the volume to 50 mL, and then use an inductively coupled plasma mass spectrometer to measure the concentration of heavy metals.

10. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to claim 1, wherein The specific step S2 specifically includes: The calculation method is as shown in formulas (3) to (7): Atmospheric dustfall input flux: I At = (C w V w + C d W d ) × 100 / S Equation (3); In formula (3): I At is the heavy metal flux entering the farmland soil in the monitoring area through atmospheric dustfall, with the unit of g / ha·y; C w and C d are the concentrations of heavy metals in wet deposition and dry deposition, with the units of μg / L and μg / g respectively; V w and W d are wet deposition and dry deposition amounts respectively, with the units of L and g respectively; S is the area of the sampling bottle mouth, in cm 2 ; 100 is the unit conversion factor; Input flux of pesticides and chemical fertilizers: In formula (4): I Fer is the annual input flux of heavy metals in chemical fertilizers and pesticides per unit area, with the unit of g / ha·y; F i，j is the actual application rate of pesticides and fertilizers, with the unit of g / y·ha; C i,j It is the content of elements in chemical fertilizers and pesticides, with the unit of mg / kg or μg / mL; n is the number of chemical fertilizer types applied at the sampling point; Input flux of irrigation water: I Ir = VC i · 10 -6 Equation (5); In formula (5): I Ir The input amount of heavy metal (i) in irrigation water, with the unit of g / y·ha; V is the amount of irrigation water applied, with the unit of L / y·ha; C i is the concentration of heavy metal (i) in the irrigation water, in μg / L; Output flux of surface runoff: In formula (6): O Run is the output of heavy metal (i) in surface runoff, with the unit of g / y·ha; C i is the concentration of heavy metal (i) in surface runoff, in μg / L; V is the surface runoff water volume, with the unit of L; R is the ratio of the annual average precipitation to rainfall during the research period, without unit; S is the sampling bottleneck area, with the unit of cm 2 ; Output flux of crops: In formula (7): O Crop is the output of heavy metal (i) in crop (i), in g / y·ha; N e，j is the number of annual crop (i) root parts; C i，e,j is the concentration of heavy metal (i) in the roots of crop (j), in μg / g; N n,j is the content of the annual crop's stem and leaf part (j), in g / y·ha; C i,n,j is the concentration of element (i) in the crop stem and leaf part (j), in μg / g; N p，j is the number of the fruit part (p) per year, in g / y·ha; C i，p，j is the concentration of heavy metal i in the crop fruit part (p), in μg / g; n is the number of harvested parts.

11. The method for predicting soil heavy metal accumulation based on an emission inventory and a receptor model according to any one of claims 4 to 6, characterized in that The heavy metals are lead, zinc, arsenic, copper or cadmium.

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