Method and system for determining heavy metal pollution characteristics of water sediment

Abstract

The invention discloses a method and a system for determining heavy metal pollution characteristics of water sediment, and relates to the technical field of environment monitoring and water environment governance, the system is characterized in that surface sediment samples are regularly collected at different positions of water in a mine area and an industrial gathering area, and a metal element data set and a reference data set are established; calculating a single-factor pollution index, and judging whether single metal exceeds the standard or not; integrating the single-factor pollution indexes to obtain a comprehensive pollution index, and determining the overall pollution level; whether manual input pollution exists or not is judged by calculating the geocumulative index; according to the method, correlation analysis, principal component analysis, factor analysis and GIS space statistics are combined, multi-dimensional indexes are extracted, pollution source analysis coefficients are calculated, agricultural non-point source or industrial emission dominant pollution types are determined, and corresponding prevention and control strategies are generated. According to the method, multilevel feature recognition and source analysis of sediment heavy metal pollution can be realized, and a scientific basis is provided for water area pollution treatment and risk management and control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of environmental monitoring and water environment treatment, in particular to a method and system for determining the pollution characteristics of heavy metals in water sediments. BACKGROUND

[0002] Water sediments are important collection and storage media for heavy metals, and their pollution characteristics directly affect the safety of aquatic ecosystems and human health. The discharge of wastewater in mining areas and industrial clusters, smelting activities, and the loss of pesticides and fertilizers in agricultural production can all lead to the enrichment of Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni heavy metals in sediments, and their entry into the food chain through resuspension and biological enrichment. Therefore, how to scientifically evaluate the pollution characteristics and sources of heavy metals in sediments is a key problem in environmental monitoring and treatment.

[0003] In traditional research on sediment heavy metal pollution, due to the lack of systematic sampling layout and multi-dimensional data fusion, existing technologies cannot accurately determine the enrichment characteristics, pollution degree, and potential risks of heavy metals in sediments. At the same time, the determination of pollution characteristics by traditional methods is mostly based on single indicators or empirical judgments, lacking correlation analysis and multi-source comparison, and it is difficult to reflect the true characteristics of pollution in complex water environments, resulting in biased evaluation results and limited application value.

[0004] More importantly, existing technologies focus on the static representation of pollution degree, but lack dynamic analysis of pollution sources and linkage with governance decisions. The calculation results of different indices are often fragmented, making it difficult to form a systematic pollution classification conclusion. At the same time, lacking multi-dimensional analysis methods based on element correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial distribution characteristics, it is difficult to effectively identify whether the pollution source comes from industrial emissions or agricultural non-point sources. Especially in complex river basin environments, if there is a lack of connection mechanism between source determination and governance strategies, the evaluation results are difficult to be transformed into operational environmental management measures. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a method and system for determining the pollution characteristics of heavy metals in water sediments to solve the problems mentioned in the background art.

[0006] To achieve the above purpose, the present application is implemented by the following technical scheme: a system for determining the pollution characteristics of heavy metals in water sediments, comprising: The sampling and detection module is used to periodically collect surface sediment samples by deploying sediment samplers and underwater sampling devices in the upstream, downstream, nearshore, and central areas of water bodies in mining and industrial cluster areas, and to detect the concentrations of heavy metals such as Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni; to perform quantitative analysis on the samples and establish a metal element data set; and to collect corresponding environmental quality standard values ​​and obtain corresponding regional background values ​​to establish a reference data set. The single-factor pollution monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. The integrated pollution monitoring module is used to calculate and obtain the single-factor pollution index DPI, integrate it, calculate the comprehensive pollution index ZDp, and compare it with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it exceeds the standard, the module will provide corresponding strategies and activate the ground-accumulated monitoring mechanism. The geoaccumulation monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. The pollution source analysis module is used to extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components PCA, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot through correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistical methods, respectively. It calculates the pollution source analysis coefficient SRC and compares it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provides corresponding strategies.

[0007] Preferably, the sampling and detection module includes a sample acquisition unit, a sample detection unit, and a reference data acquisition unit; The sample collection unit is used to monitor the heavy metal pollution of water sediments in mining areas and industrial clusters in real time; sediment samplers and underwater sampling devices are installed in the upstream, downstream, nearshore and central areas of the target water area to collect surface sediment samples of 0-10 cm periodically; the collected data include the concentration values ​​of heavy metal elements Pb, Cd, Cr, Hg, As, Cu, Zn and Ni in the sediments; The sample detection unit is used to test and quantitatively analyze the collected sediment samples using inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), and inductively coupled plasma optical emission spectrometry (ICP-OES) to obtain the actual concentration parameters of each heavy metal element and establish a metal element data set. The reference data acquisition unit is used to acquire reference values ​​required for the assessment of heavy metal pollution in sediments. In the target water area, it retrieves national or regional standards such as the "Soil Environmental Quality Standard," "Surface Water Sediment Quality Standard," or "Marine Sediment Quality Standard," and, in conjunction with commonly used international sediment quality guidelines (SQGs), collects the environmental quality standard limits for heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni, obtaining the corresponding environmental quality standard values ​​Scn. It then compares these values ​​with the regional soil element background value survey results, the watershed sediment geochemical background database, and crustal element abundance values ​​published by international authoritative institutions, collecting uncontaminated sediment samples from upstream and deep layers for detection and regression fitting to obtain the corresponding regional background value Bj; and finally, it establishes a reference data set.

[0008] Preferably, the single-factor pollution monitoring module includes a first calculation unit and a first analysis unit; The first calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Environmental quality standard values ​​corresponding to the reference data set By comparison, after dimensionless processing, the single-factor pollution index DPI was calculated and obtained; The first analysis unit is used to obtain a first evaluation result by comparing the single-factor pollution index DPI with the single-factor pollution threshold Dth through a preset single-factor pollution threshold Dth. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current level of heavy metal pollution has not exceeded the standard and should be continuously monitored. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current heavy metal pollution level exceeds the standard, triggering the first early warning instruction and generating the first strategy: recording the current information on the exceeding of metal elements and activating the comprehensive pollution monitoring mechanism.

[0009] Preferably, the integrated pollution monitoring module includes a second calculation unit and a second analysis unit; The second calculation unit is used to calculate and obtain the single-factor pollution index DPI, integrate it, and after dimensionless processing, calculate and obtain the comprehensive pollution index ZDp.

[0010] Preferably, the second analysis unit is used to preset the comprehensive pollution threshold Zth, and compare the comprehensive pollution index ZDp with the comprehensive pollution threshold Zth to obtain the second evaluation result, including: When the comprehensive pollution index ZDp ≤ comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediments has not exceeded the standard, and the regular monitoring frequency should be maintained. When the comprehensive pollution index ZDp > the comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediment exceeds the standard, triggering the second early warning instruction and generating the second strategy: record the overall exceedance information of the sediment, increase the monitoring frequency, increase the sampling density of key water areas, and activate the ground accumulation monitoring mechanism.

[0011] Preferably, the geoaccumulation monitoring module includes a third calculation unit and a third analysis unit; The third calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. The regional background value Bj corresponding to the reference data set is dimensionless, and the geocumulative index Igeo is calculated.

[0012] Preferably, the third analysis unit is used to preset the geoaccumulation threshold Ith, and compare the geoaccumulation index Igeo with the geoaccumulation threshold Ith to obtain a third evaluation result, including: When the local cumulative index Igeo is less than or equal to the local cumulative threshold Ith, it indicates that the current metal is not outside the natural fluctuation range and should be continuously monitored. When the local cumulative index Igeo is greater than the local cumulative threshold Ith, it indicates that the current metal exceeds the natural fluctuation range, is judged to be human-input pollution, triggers an early warning command, and generates a third strategy: activate the pollution source tracing mechanism.

[0013] Preferably, the pollution source tracing and analysis module includes an indicator extraction unit, a fourth calculation unit, and a fourth analysis unit; The index extraction unit is used to obtain a correlation coefficient matrix from the sampled metal element concentration data using a pairwise correlation algorithm, and extract the mean to obtain the mean of the correlation coefficient matrix Rcorr; based on the heavy metal concentration matrix of the sampling points, principal component analysis (PCA) is used to obtain the proportion of the first two principal components explained by the total variance, and the cumulative variance explained rate of principal components (PCAvar) is obtained; factor analysis (FA) is performed on the heavy metal concentration matrix to extract the normalized average value of the high-load metal elements in the first principal factor, and the factor load normalization index FAload is obtained; based on the sampling point location and concentration data, spatial statistical methods are used to identify high-value areas of heavy metals on the GIS platform, extract the hotspot clustering index, and obtain the pollution hotspot clustering index GIShot.

[0014] Preferably, the fourth calculation unit is used to calculate the pollution source analysis coefficient SRC by extracting the mean of the correlation coefficient matrix Rcorr, the cumulative variance explained by the principal components PCAvar, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot, after dimensionless processing. The fourth analysis unit is used to preset the pollution source analysis threshold Sth, and compare the pollution source analysis coefficient SRC with the pollution source analysis threshold Sth to obtain the fourth evaluation result, including: When the pollution source analysis coefficient SRC < pollution source analysis threshold Sth, it indicates that the human-input pollution is within a reasonable range, and no treatment is required for the time being, but continuous monitoring is necessary. When the pollution source analysis threshold Sth ≤ pollution source analysis coefficient SRC < pollution source analysis threshold Sth*200%, it indicates that human-input pollution is dominated by agricultural non-point source pollution, triggering the fourth early warning instruction and generating the fourth strategy: implement agricultural non-point source control, such as optimizing fertilization structure, intercepting farmland tailwater wetlands, constructing ecological buffer zones, and carrying out key monitoring during busy farming seasons; When the pollution source analysis coefficient SRC ≥ pollution source analysis threshold Sth * 200%, it indicates that human-input pollution is dominated by industrial emissions, triggering the fifth early warning instruction and generating the fifth strategy: tracing the source of industrial wastewater discharge outlets, strengthening total discharge and online monitoring, carrying out sediment dredging, stabilization and solidification remediation in key areas, and establishing long-term law enforcement patrol points.

[0015] Preferably, a method for determining the characteristics of heavy metal pollution in aquatic sediments includes the following steps: Step 1: Deploy sediment samplers and underwater sampling devices in the upstream, downstream, nearshore, and central areas of water bodies in mining and industrial cluster areas to periodically collect surface sediment samples and detect the concentrations of heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni; perform quantitative analysis on the samples to establish a metal element dataset; collect corresponding environmental quality standard values ​​and obtain corresponding regional background values ​​to establish a reference dataset. Step 2: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. Step 3: The single-factor pollution index DPI is obtained by calculation and integrated to calculate the comprehensive pollution index ZDp. It is then compared with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it does, corresponding strategies are given and the ground accumulation monitoring mechanism is activated. Step 4: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. Step 5: Using correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistics, extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components (PCAvar), the normalized factor loading index (FAload), and the pollution hotspot clustering index (GIShot), respectively. Calculate the pollution source analysis coefficient SRC and compare it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provide corresponding strategies.

[0016] This invention provides a method and system for determining the characteristics of heavy metal pollution in aquatic sediments. It has the following beneficial effects: (1) The method and system for determining the characteristics of heavy metal pollution in aquatic sediments, by setting up sampling points in the upstream, downstream, nearshore and central areas, and combining high-precision detection methods such as ICP-MS, AAS, and ICP-OES, establishes a metal element data set and a reference data set, which overcomes the problems of uneven distribution of sampling points and insufficient representativeness of detection data in traditional methods, and realizes the systematic and refined monitoring of heavy metal pollution in sediments.

[0017] (2) The method and system for determining the characteristics of heavy metal pollution in water sediments introduce a graded evaluation mechanism of single-factor pollution index and comprehensive pollution index, which can first identify the risk of exceeding the standard of individual metals, and then comprehensively determine the overall pollution level. By triggering different early warning and monitoring strategies through graded classification, it avoids the inadequacy of traditional evaluation in that a single indicator cannot fully reflect the degree of pollution.

[0018] (3) The method and system for determining the characteristics of heavy metal pollution in water sediments introduces a geoaccumulation index determination mechanism on the basis of comprehensive pollution assessment. It can distinguish between natural background fluctuations and human input, solves the limitation of traditional methods in identifying pollution causes, and makes the identification of pollution characteristics more scientific and reasonable, providing a basis for subsequent source tracing.

[0019] (4) This method and system for determining the characteristics of heavy metal pollution in aquatic sediments integrates multi-dimensional indicators such as correlation analysis, PCA, FA and GIS spatial hotspot identification to construct pollution source analysis coefficient SRC, which can accurately distinguish between agricultural non-point source pollution and industrial emission pollution, and propose differentiated governance strategies. It realizes closed-loop management of the entire chain from pollution detection to exceeding the standard to cause identification to source control, and improves the pertinence and effectiveness of pollution prevention and control. Attached Figure Description

[0020] Figure 1This is a flowchart illustrating a system for determining the characteristics of heavy metal pollution in aquatic sediments according to the present invention. Figure 2 This is a schematic diagram illustrating the steps of a method for determining the characteristics of heavy metal pollution in aquatic sediments according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1 Please see Figure 1 This invention provides a system for determining the characteristics of heavy metal pollution in aquatic sediments, comprising: The sampling and detection module is used to periodically collect surface sediment samples by deploying sediment samplers and underwater sampling devices in the upstream, downstream, nearshore, and central areas of water bodies in mining and industrial cluster areas, and to detect the concentrations of heavy metals such as Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni; to perform quantitative analysis on the samples and establish a metal element data set; and to collect corresponding environmental quality standard values ​​and obtain corresponding regional background values ​​to establish a reference data set. The single-factor pollution monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. The integrated pollution monitoring module is used to calculate and obtain the single-factor pollution index DPI, integrate it, calculate the comprehensive pollution index ZDp, and compare it with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it exceeds the standard, the module will provide corresponding strategies and activate the ground-accumulated monitoring mechanism. The geoaccumulation monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. The pollution source analysis module is used to extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components PCA, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot through correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistical methods, respectively. It calculates the pollution source analysis coefficient SRC and compares it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provides corresponding strategies.

[0023] In this embodiment, by sequentially setting up sampling and detection, single-factor pollution monitoring, comprehensive pollution monitoring, geoaccumulation monitoring, and pollution source analysis modules, a progressive evaluation chain is formed, consisting of "pollution degree determination - overall pollution assessment - human input identification - pollution source analysis". This can quickly trigger comprehensive pollution and geoaccumulation analysis after the discovery of excessive levels of a single heavy metal in sediments, and finally determine the pollution source type by combining multi-dimensional statistical and spatial methods. Compared with traditional single-indicator evaluation methods, this significantly improves the systematic nature of pollution identification and the accuracy of pollution cause analysis, which is conducive to providing targeted governance and management strategies for water areas in mining areas and industrial clusters.

[0024] Example 2 This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the sampling and detection module includes a sample acquisition unit, a sample detection unit, and a reference data acquisition unit; The sample collection unit is used to monitor the heavy metal pollution of water sediments in mining areas and industrial clusters in real time; sediment samplers and underwater sampling devices are installed in the upstream, downstream, nearshore and central areas of the target water area to collect surface sediment samples of 0-10 cm periodically; the collected data include the concentration values ​​of heavy metal elements Pb, Cd, Cr, Hg, As, Cu, Zn and Ni in the sediments; The sample detection unit is used to test and quantitatively analyze the collected sediment samples using inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), and inductively coupled plasma optical emission spectrometry (ICP-OES) to obtain the actual concentration parameters of each heavy metal element and establish a metal element data set. The reference data acquisition unit is used to acquire reference values ​​required for the assessment of heavy metal pollution in sediments. In the target water area, it retrieves national or regional standards such as the "Soil Environmental Quality Standard," "Surface Water Sediment Quality Standard," or "Marine Sediment Quality Standard," and, in conjunction with commonly used international sediment quality guidelines (SQGs), collects the environmental quality standard limits for heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni, obtaining the corresponding environmental quality standard values ​​Scn. It then compares these values ​​with the regional soil element background value survey results, the watershed sediment geochemical background database, and crustal element abundance values ​​published by international authoritative institutions, collecting uncontaminated sediment samples from upstream and deep layers for detection and regression fitting to obtain the corresponding regional background value Bj; and finally, it establishes a reference data set.

[0025] In this embodiment, by setting up a sample collection unit, a sample detection unit, and a reference data acquisition unit in the sampling and detection module, a systematic acquisition of sediment sample collection, heavy metal concentration accurate detection, and environmental quality standard values ​​and regional background values ​​is realized. This ensures the comprehensiveness and scientific nature of the data sources and improves the accuracy of the comparison between the detection results and the standards. As a result, it can provide a reliable basis for subsequent pollution index calculation and judgment, and significantly enhance the accuracy and credibility of the sediment heavy metal pollution characteristic evaluation.

[0026] Example 3 This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the single-factor pollution monitoring module includes a first calculation unit and a first analysis unit; The first calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Environmental quality standard values ​​corresponding to the reference data set For comparison, after dimensionless processing, the single-factor pollution index DPI is calculated and obtained, as shown in the following formula:

[0027] The formula principle of the single-factor pollution index (DPI): The single-factor pollution index is used to measure the pollution level of a single heavy metal in sediments, reflecting the degree of deviation between its measured concentration and the environmental quality standard value. Molecular part : Represents the measured concentration of the i-th heavy metal in the sediment, which directly reflects the enrichment level of the element in the actual environment; denominator This indicates the environmental quality standard value of the heavy metal, used as a benchmark for comparison, reflecting the upper limit of the allowable limit of the element under environmental management requirements; A high DPI (Difference Pollution Index) value indicates that the concentration of the heavy metal has exceeded environmental standards, posing a significant risk to the environmental quality of sediments; a low DPI value indicates that the concentration of the metal is within an acceptable range and has a relatively small impact on environmental quality.

[0028] The first analysis unit is used to obtain a first evaluation result by comparing the single-factor pollution index DPI with the single-factor pollution threshold Dth through a preset single-factor pollution threshold Dth. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current level of heavy metal pollution has not exceeded the standard and should be continuously monitored. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current heavy metal pollution level exceeds the standard, triggering the first early warning instruction and generating the first strategy: recording the current information on the exceeding of metal elements and activating the comprehensive pollution monitoring mechanism.

[0029] The single-factor pollution threshold Dth was obtained by referring to national or regional sediment quality standards, WHO and related water environment management regulations, and by comparing and analyzing the measured background values ​​of sediment in typical water bodies with health risk limits. It was then demonstrated and formulated by an environmental science expert group.

[0030] In this embodiment, the measured concentration is compared with the standard value by introducing a single-factor pollution monitoring module, and a single-factor pollution threshold is set by combining environmental quality standards and regional background values. This enables rapid identification and quantitative judgment of single heavy metal pollution exceeding the standard. It can not only detect problems and issue early warnings in the early stage of pollution, but also provide effective triggering conditions for subsequent comprehensive pollution monitoring, thereby improving the sensitivity and response efficiency of the monitoring system to single-point pollution risks.

[0031] Example 4 This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the integrated pollution monitoring module includes a second calculation unit and a second analysis unit; The second calculation unit is used to calculate and obtain the single-factor pollution index DPI, integrate it, and after dimensionless processing, calculate and obtain the comprehensive pollution index ZDp, as shown in the following formula:

[0032] In the formula, n represents the number of heavy metal species detected. This represents the single-factor pollution index value of the i-th heavy metal.

[0033] The formula principle of the comprehensive pollution index ZDp: The comprehensive pollution index is used to comprehensively characterize the overall pollution level of multiple heavy metals on the sedimentary environment. By integrating the pollution indices of each single factor, it reflects the superposition effect of pollution. : Represents the sum of squares of all n heavy metal single-factor pollution indices, used to highlight the weighting effect of high-pollution factors and avoid a single low value masking high-risk elements; : Indicates the number of heavy metal species detected, used to standardize calculation results and match the overall pollution level with the sample detection range; A high ZDp value indicates a significant multi-metal superimposed pollution effect and an increased overall environmental risk to the sediments; a low ZDp value indicates a relatively low overall pollution level in the sediments and no serious complex pollution has been formed.

[0034] In this embodiment, the single-factor pollution indices of multiple heavy metals are integrated and calculated through the comprehensive pollution monitoring module to obtain the comprehensive pollution index ZDp, which can comprehensively reflect the overall pollution status of sediments. This realizes the transformation from single-point indicators to overall pollution level judgment, effectively avoiding one-sided conclusions caused by the anomaly of a single element, thereby improving the systematicness and scientificity of sediment heavy metal pollution assessment.

[0035] Example 5 This embodiment is an explanation based on Embodiment 4. Please refer to it. Figure 1 Specifically, the second analysis unit is used to preset the comprehensive pollution threshold Zth, and compare the comprehensive pollution index ZDp with the comprehensive pollution threshold Zth to obtain the second evaluation result, including: When the comprehensive pollution index ZDp ≤ comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediments has not exceeded the standard, and the regular monitoring frequency should be maintained. When the comprehensive pollution index ZDp > the comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediment exceeds the standard, triggering the second early warning instruction and generating the second strategy: record the overall exceedance information of the sediment, increase the monitoring frequency, increase the sampling density of key water areas, and activate the ground accumulation monitoring mechanism.

[0036] The comprehensive pollution threshold Zth is obtained by statistically analyzing measured data of the comprehensive heavy metal pollution index ZDp in a large number of sediment samples. The index distribution range between the overall sediment pollution level being within an environmentally acceptable range and the risk of significant exceedance is extracted. Combined with the experience of water environment quality assessment experts and water ecological safety requirements, a reasonable comprehensive pollution judgment threshold is determined. Referring to the "Surface Water Environmental Quality Standard" and the "Technical Specification for Sediment Environmental Quality Assessment," these standards typically specify the environmental risk classification and comprehensive judgment methods for heavy metal content in sediments. This threshold is used to accurately identify the overall risk of sediment pollution exceeding standards, ensuring the safety of the water environment and the scientific nature of pollution control.

[0037] In this embodiment, the second analysis unit of the integrated pollution monitoring module compares the integrated pollution index ZDp with the preset threshold Zth, thereby realizing the dynamic determination of the overall pollution level of sediments. When the level exceeds the standard, it can not only trigger an early warning and automatically generate an adjustment strategy, but also increase the monitoring frequency and sampling density, and link up to activate the ground cumulative monitoring mechanism, forming a closed-loop management mode from overall judgment to in-depth tracking, thereby significantly improving the accuracy and real-time performance of sediment pollution management.

[0038] Example 6 This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the ground accumulation monitoring module includes a third calculation unit and a third analysis unit; The third calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. The regional background value Bj corresponding to the reference data set is dimensionless, and the geocumulative index Igeo is calculated using the following formula:

[0039] In the formula, 1.5 is a constant used to correct for differences in sediment composition and natural fluctuations.

[0040] The principle behind the geoaccumulation index Igeo: The geoaccumulation index is used to determine whether heavy metals in sediments exceed the natural fluctuation range, thereby identifying the contribution of human input to metal enrichment; : Represents the measured concentration of the i-th heavy metal in the sediment, which is the actual measurement basis for pollution assessment; :in This represents the regional background value of the i-th heavy metal, with 1.5 as a correction factor to eliminate biases caused by differences in sediment composition and natural fluctuations, ensuring the stability and comparability of the results. A high Igeo value indicates that the metal exceeds the natural fluctuation range and there is significant anthropogenic pollution. A low Igeo value indicates that the metal concentration is mainly controlled by the natural geological background and there is no significant external interference.

[0041] In this embodiment, the geoaccumulation index Igeo is calculated by introducing the regional background value Bj and combining it with the correction factor through the third calculation unit of the geoaccumulation monitoring module. This not only effectively distinguishes between natural sedimentary background and external pollution contributions, but also eliminates the bias caused by differences in sediment composition, thereby achieving a more scientific and accurate identification of the sources of heavy metal pollution in sediments.

[0042] Example 7 This embodiment is an explanation based on Embodiment 6. Please refer to it. Figure 1Specifically, the third analysis unit is used to preset the geoaccumulation threshold Ith, and compare the geoaccumulation index Igeo with the geoaccumulation threshold Ith to obtain a third evaluation result, including: When the local cumulative index Igeo is less than or equal to the local cumulative threshold Ith, it indicates that the current metal is not outside the natural fluctuation range and should be continuously monitored. When the local cumulative index Igeo is greater than the local cumulative threshold Ith, it indicates that the current metal exceeds the natural fluctuation range, is judged to be human-input pollution, triggers an early warning command, and generates a third strategy: activate the pollution source tracing mechanism.

[0043] The geoaccumulation threshold Ith is obtained by statistically analyzing historical monitoring data of the heavy metal geoaccumulation index Igeo in sediments from numerous mining and industrial clusters. The natural fluctuation range and the index distribution interval under significant anthropogenic input are extracted. Combined with the experience of environmental geochemical experts and ecological risk assessment requirements, a reasonable geoaccumulation determination threshold is established. Referring to the "Sediment Quality Standards" and regional background value research results, these standards typically clarify the natural background range and accumulation effect classification of different metals in sediments. This threshold is used to distinguish between natural sedimentary processes and anthropogenic pollution, improving the accuracy of pollution cause determination.

[0044] In this embodiment, the geoaccumulation index Igeo is compared with the preset threshold Ith by the third analysis unit. This not only clearly distinguishes between natural fluctuations and human-input pollution, but also automatically triggers the pollution source tracing mechanism when pollution exceeds the standard, realizing closed-loop management from monitoring to early warning to source tracing, thereby improving the response speed and targeted treatment of heavy metal pollution in sediments.

[0045] Example 8 This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the pollution source tracing and analysis module includes an indicator extraction unit, a fourth calculation unit, and a fourth analysis unit; The index extraction unit is used to obtain a correlation coefficient matrix from the sampled metal element concentration data using a pairwise correlation algorithm, and extract the mean to obtain the mean of the correlation coefficient matrix Rcorr; based on the heavy metal concentration matrix of the sampling points, principal component analysis (PCA) is used to obtain the proportion of the first two principal components explained by the total variance, and the cumulative variance explained rate of principal components (PCAvar) is obtained; factor analysis (FA) is performed on the heavy metal concentration matrix to extract the normalized average value of the high-load metal elements in the first principal factor, and the factor load normalization index FAload is obtained; based on the sampling point location and concentration data, spatial statistical methods are used to identify high-value areas of heavy metals on the GIS platform, extract the hotspot clustering index, and obtain the pollution hotspot clustering index GIShot.

[0046] In this embodiment, by introducing correlation analysis, principal component analysis, factor analysis, and spatial statistical methods through the pollution source tracing and analysis module, the source characteristics of heavy metal pollution can be quantified in multiple dimensions. This not only improves the scientificity and accuracy of pollution cause identification, but also effectively locates pollution hotspots, achieving a precise transition from concentration anomalies to source tracing and analysis, and significantly enhancing the decision support capability for environmental management.

[0047] Example 9 This embodiment is an explanation based on Embodiment 8. Please refer to it. Figure 1 Specifically, the fourth calculation unit is used to calculate the pollution source analysis coefficient SRC after dimensionless processing of the extracted correlation coefficient matrix mean Rcorr, principal component cumulative variance explained rate PCAvar, factor loading normalization index FAload, and pollution hotspot clustering index GIShot, as follows:

[0048] In the formula, w1, w2, w3, and w4 represent weighting coefficients; The fourth analysis unit is used to preset the pollution source analysis threshold Sth, and compare the pollution source analysis coefficient SRC with the pollution source analysis threshold Sth to obtain the fourth evaluation result, including: When the pollution source analysis coefficient SRC < pollution source analysis threshold Sth, it indicates that the human-input pollution is within a reasonable range, and no treatment is required for the time being, but continuous monitoring is necessary. When the pollution source analysis threshold Sth ≤ pollution source analysis coefficient SRC < pollution source analysis threshold Sth*200%, it indicates that human-input pollution is dominated by agricultural non-point source pollution, triggering the fourth early warning instruction and generating the fourth strategy: implement agricultural non-point source control, such as optimizing fertilization structure, intercepting farmland tailwater wetlands, constructing ecological buffer zones, and carrying out key monitoring during busy farming seasons; When the pollution source analysis coefficient SRC ≥ pollution source analysis threshold Sth * 200%, it indicates that human-input pollution is dominated by industrial emissions, triggering the fifth early warning instruction and generating the fifth strategy: tracing the source of industrial wastewater discharge outlets, strengthening total discharge and online monitoring, carrying out sediment dredging, stabilization and solidification remediation in key areas, and establishing long-term law enforcement patrol points.

[0049] The pollution source apportionment threshold Sth is obtained by: Based on monitoring and statistical analysis of numerous typical water body heavy metal pollution source tracing cases, extracting the distribution patterns of the pollution source apportionment coefficient SRC under agricultural non-point source pollution and industrial emission dominance conditions. Combining this with the experience of pollution prevention experts and pollution control priority requirements, a reasonable pollution source apportionment threshold is determined. Referring to standards such as the "Technical Guidelines for Agricultural Non-point Source Pollution Control" and the "Water Pollution Prevention and Control Action Plan," these standards typically set clear requirements for pollution type identification and control strategies. This threshold is used to accurately distinguish between agricultural non-point source pollution and industrial emission pollution dominance, guiding the implementation of differentiated pollution control and source tracing management.

[0050] The design principle of the pollution source analysis coefficient (SRC) is based on the fusion of multi-dimensional information. A single statistical feature (such as correlation or PCA) cannot fully reflect the pollution source. By weighting and fusing four complementary indicators, namely the inter-element correlation Rcorr, the principal component explanation rate PCAvar, the factor load FAload, and the spatial hotspot index GIShot, the covariance pattern, factor concentration, and spatial distribution characteristics of pollution are comprehensively reflected. Resetting: w1, w2, w3, and w4 are set based on historical cases and expert experience to ensure that the contribution of each indicator matches the actual discriminative power; for example, in cases of industrial pollution in mining areas, the proportion of correlation and factor loading can be appropriately increased; in cases of agricultural non-point source pollution, the weight of GIS hotspots and spatial matching degree can be appropriately increased. The mean correlation coefficient between elements has a high weight in characterizing the impact of pollution source analysis. It is a key indicator that directly reflects the contribution of multi-metal synergistic variation characteristics to pollution source homology. This represents the impact of the cumulative variance explained by the principal components on the analysis of pollution sources. It has a moderate weight and reflects the explanatory power of the dominant factors on the overall pollution variance, thus reflecting the concentration of pollution sources. The normalized index of characterizing factor loadings has the second highest weight in the analysis of pollution sources, reflecting the attribution ability of the concentration of high-loading metal elements to the main pollutants. The pollution hotspot clustering index represents the impact of pollution source analysis and has a minor weight, reflecting the auxiliary role of the clustering characteristics of pollution spatial distribution in source indication. By constructing a pollution source analysis coefficient SRC, which is a weighted fusion of the correlation coefficient matrix mean Rcorr, the principal component cumulative variance explained rate PCAvar, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot, the comprehensive contribution of multidimensional statistical characteristics and spatial distribution patterns to the causes of pollution can be quantified, providing a scientific basis for the accurate differentiation of agricultural non-point source pollution and industrial point source pollution and the triggering of governance strategies. Normalization: Since the dimensions of each indicator are different, they must first be mapped to the [0, 1] interval to avoid bias caused by differences in numerical dimensions and to make the weighted results comparable. When the pollution source apportionment coefficient SRC < pollution source apportionment threshold Sth, although human input has been confirmed when determining the geoaccumulation index Igeo, if the overall SRC is low, it indicates that the various characteristic values ​​(correlation, PCA, factor loading, GIS hotspots) are not significant, which is a local, small-scale or recent low-intensity input. At this time, human input cannot be ignored, so only continuous monitoring and early warning are maintained. When the pollution source analysis threshold Sth ≤ pollution source analysis coefficient SRC < pollution source analysis threshold Sth * 200%, the element correlation is low or moderate (complex sources, strong doping, and not a single emission outlet); the PCA principal component explanation rate is moderate (multiple factors act simultaneously, and a single principal component cannot explain most of the variance); the FA first factor loading is relatively dispersed, concentrated in agricultural indicator elements such as Cd, Zn, and As; GIS hotspots are highly consistent with farmland, irrigation areas, and nearshore zones; therefore, it indicates that human input is significant, but insufficient to show the "strong correlation + strong concentration" of industrial pollution, and the combination of characteristic distribution is more consistent with the characteristics of agricultural non-point source pollution. When the pollution source apportionment coefficient SRC ≥ pollution source apportionment threshold Sth * 200%, the element correlation is significantly enhanced (multi-element co-release, with obvious synergistic changes); the first two principal components of PCA have extremely high explanatory power (single or a few emission factors explain most of the variance); the first factor loading of FA is highly concentrated (strong loading of typical industrial elements such as Pb, Cr, Cu, and Ni); the GIS hotspot index is significantly higher, and its spatial distribution highly overlaps with that of industrial discharge outlets or downstream mining areas; thus, it is indicated that pollution has shown a pattern of strong concentration, strong correlation, and strong spatial aggregation, with significant characteristics of industrial point source input.

[0051] In this embodiment, by designing the pollution source analysis coefficient SRC, a multi-dimensional index such as the correlation mean, principal component explanation rate, factor loading, and spatial hotspot index is weighted and integrated. This can distinguish between three scenarios: local low-intensity input, agricultural non-point source pollution, and industrial emission pollution. It achieves a precise upgrade in judgment from "whether there is human input" to "pollution attribution type", effectively improving the pertinence and scientific nature of pollution prevention and control strategies.

[0052] Example 10 Please refer to Figure 2 A method for determining the characteristics of heavy metal pollution in aquatic sediments, specifically including the following steps: Step 1: Deploy sediment samplers and underwater sampling devices in the upstream, downstream, nearshore, and central areas of water bodies in mining and industrial cluster areas to periodically collect surface sediment samples and detect the concentrations of heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni; perform quantitative analysis on the samples to establish a metal element dataset; collect corresponding environmental quality standard values ​​and obtain corresponding regional background values ​​to establish a reference dataset. Step 2: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. Step 3: The single-factor pollution index DPI is obtained by calculation and integrated to calculate the comprehensive pollution index ZDp. It is then compared with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it does, corresponding strategies are given and the ground accumulation monitoring mechanism is activated. Step 4: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. Step 5: Using correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistics, extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components (PCAvar), the normalized factor loading index (FAload), and the pollution hotspot clustering index (GIShot), respectively. Calculate the pollution source analysis coefficient SRC and compare it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provide corresponding strategies.

[0053] In this embodiment, a multi-level monitoring and analysis process, from single-factor pollution monitoring, comprehensive pollution assessment, geoaccumulation determination to pollution source analysis, is used to achieve accurate identification of heavy metal pollution in water sediments throughout the entire process. This not only enables timely detection of pollution exceeding standards but also determines the type of pollution source, providing a scientific basis for implementing differentiated governance strategies, thereby significantly improving the accuracy and efficiency of pollution prevention and control.

[0054] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0055] The above formulas are all derived from software simulation using a large amount of data, and are selected to be close to the actual values. The coefficients in the formulas are set by those skilled in the art based on the actual situation. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or changes made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A system for determining the characteristics of heavy metal pollution in aquatic sediments, characterized in that, include: The sampling and detection module is used to periodically collect surface sediment samples and detect the concentrations of heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn and Ni by deploying sediment samplers and underwater sampling devices in the upstream, downstream, nearshore and central areas of water bodies in mining areas and industrial clusters. Quantitative analysis of the samples was performed to establish a metal element dataset; corresponding environmental quality standard values ​​and regional background values ​​were collected to establish a reference dataset. The single-factor pollution monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. The integrated pollution monitoring module is used to calculate and obtain the single-factor pollution index DPI, integrate it, calculate the comprehensive pollution index ZDp, and compare it with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it exceeds the standard, the module will provide corresponding strategies and activate the ground-accumulated monitoring mechanism. The geoaccumulation monitoring module is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. The pollution source analysis module is used to extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components PCA, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot through correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistical methods, respectively. It calculates the pollution source analysis coefficient SRC and compares it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provides corresponding strategies.

2. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 1, characterized in that, The sampling and detection module includes a sample acquisition unit, a sample detection unit, and a reference data acquisition unit; The sample collection unit is used to monitor the heavy metal pollution of water sediments in mining areas and industrial clusters in real time; sediment samplers and underwater sampling devices are installed in the upstream, downstream, nearshore and central areas of the target water area to collect surface sediment samples of 0-10 cm periodically; the collected data include the concentration values ​​of heavy metal elements Pb, Cd, Cr, Hg, As, Cu, Zn and Ni in the sediments; The sample detection unit is used to test and quantitatively analyze the collected sediment samples using inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), and inductively coupled plasma optical emission spectrometry (ICP-OES) to obtain the actual concentration parameters of each heavy metal element and establish a metal element data set. The reference data acquisition unit is used to acquire reference values ​​required for the assessment of heavy metal pollution in sediments. In the target water area, it retrieves national or regional standards such as the "Soil Environmental Quality Standard," "Surface Water Sediment Quality Standard," or "Marine Sediment Quality Standard," and, in conjunction with commonly used international sediment quality guidelines (SQGs), collects the environmental quality standard limits for heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni, obtaining the corresponding environmental quality standard values ​​Scn. It then compares these values ​​with the regional soil element background value survey results, the watershed sediment geochemical background database, and crustal element abundance values ​​published by international authoritative institutions, collecting uncontaminated sediment samples from upstream and deep layers for detection and regression fitting to obtain the corresponding regional background value Bj; and finally, it establishes a reference data set.

3. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 1, characterized in that, The single-factor pollution monitoring module includes a first calculation unit and a first analysis unit; The first calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. Environmental quality standard values ​​corresponding to the reference data set By comparison, after dimensionless processing, the single-factor pollution index DPI was calculated and obtained; The first analysis unit is used to obtain a first evaluation result by comparing the single-factor pollution index DPI with the single-factor pollution threshold Dth through a preset single-factor pollution threshold Dth. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current level of heavy metal pollution has not exceeded the standard and should be continuously monitored. When the single-factor pollution index DPI is less than or equal to the single-factor pollution threshold Dth, it indicates that the current heavy metal pollution level exceeds the standard, triggering the first early warning instruction and generating the first strategy: recording the current information on the exceeding of metal elements and activating the comprehensive pollution monitoring mechanism.

4. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 1, characterized in that, The integrated pollution monitoring module includes a second calculation unit and a second analysis unit; The second calculation unit is used to calculate and obtain the single-factor pollution index DPI, integrate it, and after dimensionless processing, calculate and obtain the comprehensive pollution index ZDp.

5. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 4, characterized in that, The second analysis unit is used to preset the comprehensive pollution threshold Zth, and compare the comprehensive pollution index ZDp with the comprehensive pollution threshold Zth to obtain the second evaluation result, including: When the comprehensive pollution index ZDp ≤ comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediments has not exceeded the standard, and the regular monitoring frequency should be maintained. When the comprehensive pollution index ZDp > the comprehensive pollution threshold Zth, it indicates that the overall pollution level of the sediment exceeds the standard, triggering the second early warning instruction and generating the second strategy: record the overall exceedance information of the sediment, increase the monitoring frequency, increase the sampling density of key water areas, and activate the ground accumulation monitoring mechanism.

6. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 1, characterized in that, The geoaccumulation monitoring module includes a third calculation unit and a third analysis unit; The third calculation unit is used to extract the measured concentration of the i-th heavy metal in the sediment from the metal element data set. The regional background value Bj corresponding to the reference data set is dimensionless, and the geocumulative index Igeo is calculated.

7. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 6, characterized in that, The third analysis unit is used to preset the geoaccumulation threshold Ith, and compare the geoaccumulation index Igeo with the geoaccumulation threshold Ith to obtain the third evaluation result, including: When the local cumulative index Igeo is less than or equal to the local cumulative threshold Ith, it indicates that the current metal is not outside the natural fluctuation range and should be continuously monitored. When the local cumulative index Igeo is greater than the local cumulative threshold Ith, it indicates that the current metal exceeds the natural fluctuation range, is judged to be human-input pollution, triggers an early warning command, and generates a third strategy: activate the pollution source tracing mechanism.

8. The system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 1, characterized in that, The pollution source tracing and analysis module includes an indicator extraction unit, a fourth calculation unit, and a fourth analysis unit; The index extraction unit is used to obtain a correlation coefficient matrix from the sampled metal element concentration data using a pairwise correlation algorithm, and extract the mean to obtain the mean of the correlation coefficient matrix Rcorr; based on the heavy metal concentration matrix of the sampling points, principal component analysis (PCA) is used to obtain the proportion of the first two principal components explained by the total variance, and the cumulative variance explained rate of principal components (PCAvar) is obtained; factor analysis (FA) is performed on the heavy metal concentration matrix to extract the normalized average value of the high-load metal elements in the first principal factor, and the factor load normalization index FAload is obtained; based on the sampling point location and concentration data, spatial statistical methods are used to identify high-value areas of heavy metals on the GIS platform, extract the hotspot clustering index, and obtain the pollution hotspot clustering index GIShot.

9. A system for determining the characteristics of heavy metal pollution in aquatic sediments according to claim 8, characterized in that, The fourth calculation unit is used to calculate the pollution source analysis coefficient SRC by extracting the mean of the correlation coefficient matrix Rcorr, the cumulative variance explained rate of principal components PCAvar, the factor load normalization index FAload, and the pollution hotspot clustering index GIShot, after dimensionless processing. The fourth analysis unit is used to preset the pollution source analysis threshold Sth, and compare the pollution source analysis coefficient SRC with the pollution source analysis threshold Sth to obtain the fourth evaluation result, including: When the pollution source analysis coefficient SRC < pollution source analysis threshold Sth, it indicates that the human-input pollution is within a reasonable range, and no treatment is required for the time being, but continuous monitoring is necessary. When the pollution source analysis threshold Sth ≤ pollution source analysis coefficient SRC < pollution source analysis threshold Sth*200%, it indicates that human-input pollution is dominated by agricultural non-point source pollution, triggering the fourth early warning instruction and generating the fourth strategy: implement agricultural non-point source control, such as optimizing fertilization structure, intercepting farmland tailwater wetlands, constructing ecological buffer zones, and carrying out key monitoring during busy farming seasons; When the pollution source analysis coefficient SRC ≥ pollution source analysis threshold Sth * 200%, it indicates that human-input pollution is dominated by industrial emissions, triggering the fifth early warning instruction and generating the fifth strategy: tracing the source of industrial wastewater discharge outlets, strengthening total discharge and online monitoring, carrying out sediment dredging, stabilization and solidification remediation in key areas, and establishing long-term law enforcement patrol points.

10. A method for determining the characteristics of heavy metal pollution in aquatic sediments, applied to the system for determining the characteristics of heavy metal pollution in aquatic sediments as described in any one of claims 1 to 9, characterized in that, Includes the following steps: Step 1: Deploy sediment samplers and underwater sampling devices in the upstream, downstream, nearshore, and central areas of water bodies in mining and industrial cluster areas to regularly collect surface sediment samples and detect the concentrations of heavy metals Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni. Quantitative analysis of the samples was performed to establish a metal element dataset; corresponding environmental quality standard values ​​and regional background values ​​were collected to establish a reference dataset. Step 2: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. Combined with the corresponding environmental quality standard values ​​in the reference data set The single-factor pollution index DPI is calculated and compared with the single-factor pollution threshold Dth to determine whether the current heavy metal pollution level exceeds the standard. If it does, the comprehensive pollution monitoring mechanism is activated. Step 3: The single-factor pollution index DPI is obtained by calculation and integrated to calculate the comprehensive pollution index ZDp. It is then compared with the comprehensive pollution threshold Zth to determine whether the overall pollution level of the sediment exceeds the standard. If it does, corresponding strategies are given and the ground accumulation monitoring mechanism is activated. Step 4: Extract the measured concentration of the i-th heavy metal in the sediment by analyzing the metal element data. By combining the regional background value Bj corresponding to the reference data set, the geoaccumulation index Igeo is calculated and compared with the geoaccumulation threshold Ith to determine whether the current metal pollution is caused by human intervention. If so, the pollution source tracing mechanism is activated. Step 5: Using correlation analysis, principal component analysis (PCA), factor analysis (FA), and GIS spatial statistics, extract the mean correlation coefficient Rcorr, the cumulative variance explained by principal components (PCAvar), the normalized factor loading index (FAload), and the pollution hotspot clustering index (GIShot), respectively. Calculate the pollution source analysis coefficient SRC and compare it with the pollution source analysis threshold Sth to determine whether the pollution is dominated by agricultural non-point source pollution or industrial non-point source pollution, and provide corresponding strategies.

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