Deposit heavy metal pollution analysis system and method

Abstract

The invention provides a sediment heavy metal pollution analysis system and a sediment heavy metal pollution analysis method, and relates to the field of environmental monitoring. A sediment collection module uses a depth-adjustable columnar sampler, multiple layers of cabins in the sediment collection module are independently closed, and samples are collected according to a preset depth; the depth control module monitors the position and water pressure change of the sampler through a depth sensor, ensures accurate sampling, and adjusts to a target depth in real time; the sample processing module is used for automatically processing sediment samples, sequentially drying, crushing and homogenizing the sediment samples to generate sample quality coefficients, so that the detection accuracy is improved; the detection and analysis module measures the heavy metal concentration by utilizing a spectral analysis technology and calculates the element content through light absorption intensity; the risk assessment module generates an ecological risk index according to the concentration data, the risk weight and the quality coefficient, and sets a risk level to assess the pollution degree; through accurate sampling, automatic processing and risk assessment, accurate detection of sediment heavy metal pollution and accurate assessment of the pollution degree are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a sediment heavy metal pollution analysis system and method. Background Art

[0002] Analysis of heavy metal pollution in sediments can help determine the sources of pollutants, such as industrial emissions, agricultural runoff, urban wastewater, etc., and sediments are also the main source of heavy metal pollution in water bodies. Due to their close connection with aquatic ecosystems, the accumulation and distribution of heavy metals in sediments can reflect the pollution status of water bodies and identify the main types of pollutants, which is of great significance for the formulation of pollution prevention and control measures, policy formulation, and evaluation of governance effects; heavy metals in sediments will enter aquatic organisms through the food chain, thereby affecting the entire ecosystem and human health. Heavy metals are bioaccumulative and toxic. Long-term exposure may lead to a decrease in aquatic populations and biodiversity, and even affect human health problems caused by eating contaminated aquatic products.

[0003] In the prior art, the publication number CN114674811A discloses a method for analyzing the heavy metal concentration in sediments from agricultural ditches to rivers. By setting a starting point and multiple sampling points, the heavy metal concentration in the sediments at the sampling points is measured, and the distance from the sampling point to the starting point is recorded to obtain the overall sample data; the overall sample data is analyzed for differences; the relationship between the heavy metal concentration and the distance is analyzed using a regression analysis method to obtain a linear regression equation; the trend of the heavy metal concentration changing with the distance is calculated according to the linear regression equation. By measuring and analyzing the heavy metal concentration in sediments at different sampling points, the correlation between the concentration and the distance and the significance of the differences between different regions are found, thereby predicting the trend of the heavy metal concentration in sediments from agricultural ditches to rivers.

[0004] Insufficient existing technology:

[0005] In the prior art, a starting point and multiple sampling points are set, and the distance from the sampling point to the starting point is recorded to obtain overall sample data. The main focus is on sampling along the distance, and the sampling depth and accuracy are not considered in detail. Sampling is limited to a single depth, ignoring the potential impact of changes in heavy metal concentrations in sediments with depth.

[0006] The existing technology mainly analyzes the relationship between heavy metal concentration and distance through linear regression. It does not mention what detection technology is used to measure the heavy metal concentration, nor does it clarify whether it can effectively distinguish or simultaneously detect multiple heavy metal elements. It analyzes the trend of concentration change with distance through linear regression equations, and does not deeply explore the comprehensive risk assessment of heavy metal pollution to ecosystems and human health. Its method is relatively one-sided in the analysis of the significance of regional differences and fails to fully consider the comprehensive analysis of multiple factors.

[0007] Therefore, it is necessary to provide a sediment heavy metal pollution analysis system and method to solve the above problems.

[0008] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0009] The object of the present invention is to provide a sediment heavy metal pollution analysis system and method to solve the problems raised in the above background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] A sediment heavy metal pollution analysis system, the specific steps include:

[0012] The sediment collection module is used to collect sediment samples at different depths in the water area through a columnar sampler with adjustable depth. The sampler is equipped with multiple layers of independently sealed sampling chambers, each of which can be opened and closed at a predetermined depth to obtain sediment samples;

[0013] The depth control module is used to monitor the depth and position of the sampler in the water in real time, ensuring that the sampler accurately samples at the designated location and depth. It measures water pressure changes based on depth sensor technology and converts them into depth data. It sets the target depth, compares it with the current depth to determine whether the target position has been reached, and makes adjustments.

[0014] The sample processing module is used to perform automated preprocessing operations on the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generates a sample quality coefficient to improve the accuracy of subsequent detection and analysis;

[0015] The detection and analysis module is used to detect the treated sediments. The sample is detected based on the spectral analysis technology. The light absorption intensity of the light of the specific wavelength emitted by the light source is measured after passing through the decomposed elements in the sample. The concentration data of the heavy metal elements in the elements contained in the sediments is calculated.

[0016] The risk assessment module is used to evaluate the potential risks of sediments to ecosystems and human health. The ecological risk index is generated based on the heavy metal concentration data, combined with its environmental risk weight and the obtained sample quality coefficient. The risk level is set and compared with the ecological risk index to determine the degree of heavy metal pollution in the sediments and the waters in which they are located.

[0017] Furthermore, sediment samples were collected at different depths in the water body, based on the following method:

[0018] The stratified sampling method is used to collect sediment samples at different depths by setting up multiple independent closed sampling chambers. The sampler sinks to a predetermined depth, and each chamber automatically opens and collects samples when it reaches the predetermined depth, ensuring a comprehensive analysis of the pollution situation at different levels of the water body. The formula is:

[0019]

[0020] The predetermined sampling depth of the i-th sampling chamber is set to H i , L represents the total sinking depth of the sampler, N represents the number of chambers, and i represents the index of the sampling chamber sequence.

[0021] Furthermore, the water pressure change is measured based on the depth sensor technology and converted into depth data, based on the following method:

[0022] The depth sensor installed on the sampler measures the water pressure at the water depth where the sampler is located in real time. The measured water pressure is converted into the current depth data of the sampler using the relationship formula between water pressure and depth. The formula is:

[0023]

[0024] Among them, d(t) represents the depth of the sampler at time t, P(t) represents the water pressure measured at time t, ρ represents the density of water, g represents the acceleration of gravity, and P0 represents the atmospheric pressure.

[0025] Furthermore, the target depth is set, compared with the current depth to determine whether the target position has been reached, and adjustments are made based on the following method:

[0026] The target depth is preset in the system. The current water pressure is measured in real time. The current depth is calculated using the relationship between water pressure and water depth. The difference between the target depth and the current depth is obtained. Based on this difference, it is determined whether the depth of the sampler needs to be adjusted and the direction of the sampler adjustment. The proportional-integral-differential control algorithm is used to gradually approach the target depth. The logic is as follows:

[0027] Δd(i, t) = d(t) - H i

[0028]

[0029] Wherein, Δd(i, t) represents the depth error of the i-th sampling chamber at time t, Q(i, t) represents the adjustment judgment value of the sampler at time t when the i-th sampling chamber needs to be used for sampling, u(i, t) represents the control signal issued at time t when the i-th sampling chamber needs to be used for sampling, and the control signal is used to adjust the movement of the sampler, K p , K i , K d Respectively represent the proportional, integral and differential control coefficients, H i Indicates the predetermined sampling depth.

[0030] Furthermore, the sediment samples were dried, crushed, and homogenized in order to improve the accuracy of subsequent testing and analysis, based on the following methods:

[0031] The sample is placed in a dryer, and the water in the sample is evaporated by controlling the temperature and time until the sample mass no longer changes. The dried sediment sample is crushed to a certain particle size using a mechanical crushing device to increase the surface area of ​​the sample, ensure the uniformity of the sample and the sufficiency of the subsequent chemical reaction. The sample is fully mixed by stirring to ensure that the composition of the sample is evenly distributed in space to eliminate the discreteness between samples. The sample mass coefficient is calculated based on the formula:

[0032]

[0033] Among them, δ represents the sample quality coefficient, m h Indicates the mass of the sample after drying, m q Indicates the mass of the sample before drying.

[0034] Furthermore, the light absorption intensity is measured and the concentration data of heavy metal elements in the elements contained in the sediment are calculated according to the following method:

[0035] After the treated sample is atomized, the heavy metals in the sample are decomposed into free atoms. The free atoms absorb light of a specific wavelength in the ground state. The heavy metal atoms in the sample absorb part of the light, resulting in a decrease in the light intensity of the sample. By measuring the intensity of the absorbed light, the concentration data of the heavy metal elements in the sample is calculated based on the formula:

[0036]

[0037] Among them, C m (i, j) represents the concentration of the jth heavy metal in the sample of the i-th sampling chamber, A(i, j) represents the absorbance of the jth heavy metal element in the sample of the i-th sampling chamber, ε(j) represents the molar absorption coefficient of the jth heavy metal, and l represents the optical path length of the sample.

[0038] Furthermore, the potential risks of sediments to ecosystems and human health were assessed. The ecological risk index was generated based on the heavy metal concentration data, combined with the environmental risk weights and the obtained sample quality coefficients. The method was as follows:

[0039] The heavy metal concentration components were determined, and the heavy metal background values ​​and heavy metal toxicity coefficients of the waters where the sediments were located were collected as reference benchmarks for the assessment. The pollution index of a single heavy metal and the average pollution index of all heavy metals were calculated. The ecological risk index was generated by combining the environmental risk weight and the sample quality coefficient. The formula is:

[0040]

[0041] Among them, PI j represents the pollution index of the jth heavy metal, B m (i, j) represents the background value of the jth heavy metal in the sample of the i-th sampling chamber, represents the toxicity coefficient of the jth heavy metal, represents the environmental risk weight of the j-th heavy metal, CPI represents the comprehensively generated ecological risk index, j represents the index of heavy metals, m represents the number of heavy metal types, and N represents the number of compartments.

[0042] Furthermore, the risk level is set to be compared with the ecological risk index to determine the degree of heavy metal pollution in the sediment and the waters in which it is located. The method is based on:

[0043] According to the size of the comprehensive ecological risk index, the risk level is divided into the following categories: when CPI≤150, it is a low risk level, indicating that the degree of heavy metal pollution is low, the ecological environment of sediments and waters is relatively safe, and the impact on aquatic organisms and ecosystems can be ignored; when 150≤CPI≤300, it is a medium risk level, indicating that the degree of heavy metal pollution is moderate, which may have a certain negative impact on the ecosystems of sediments and waters, and there are certain ecological risks; when CPI≥300, it is a high risk level, indicating that heavy metal pollution is serious, posing a significant threat to the ecosystems of sediments and waters, and causing harm to aquatic organisms and human health.

[0044] The present invention further provides a sediment heavy metal pollution analysis method, which is used to execute any one of the above sediment heavy metal pollution analysis systems, comprising:

[0045] Step 1: Collect sediment samples at different depths in the water area through a depth-adjustable columnar sampler, which has multiple layers of independently sealed sampling chambers inside. Each chamber can be opened and closed at a predetermined depth to obtain sediment samples;

[0046] Step 2: Monitor the depth and position of the sampler in the water in real time to ensure that the sampler accurately samples at the designated location and depth. Use depth sensor technology to measure water pressure changes and convert them into depth data. Set the target depth, compare it with the current depth to determine whether the target position has been reached, and make adjustments.

[0047] Step 3: Automated preprocessing of the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generating sample quality coefficients to improve the accuracy of subsequent detection and analysis.

[0048] Step 4: Detect the treated sediments based on spectral analysis technology. The sample is detected by using the characteristics of the atoms of heavy metal elements in the sample absorbing light under the radiation of light of a specific wavelength. After the light of a specific wavelength emitted by the light source passes through the decomposed elements in the sample, its light absorption intensity is measured to calculate the concentration data of the heavy metal elements in the elements contained in the sediments.

[0049] Step 5: Assess the potential risks of sediments to ecosystems and human health. Generate an ecological risk index based on heavy metal concentration data, combined with environmental risk weights and the obtained sample quality coefficient. Set the risk level and compare it with the ecological risk index to determine the degree of heavy metal pollution in sediments and the waters in which they are located.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention takes into account the potential impact of the change in heavy metal concentration in sediments with depth. In order to make the collected sediments generally representative, sediment samples can be obtained at different depths by using a columnar sampler with adjustable depth and a multi-layered independently closed sampling chamber, thereby providing more accurate and comprehensive heavy metal distribution data. This multi-level sampling helps to fully understand the pollution of sediments at different depths, rather than being limited to samples at the surface or a single depth;

[0052] The present invention adopts a detection method based on spectral analysis technology, which can more accurately determine the concentration of multiple heavy metal elements, and improve the sensitivity and accuracy of detection through light absorption characteristics. This technology is more suitable for complex multi-element analysis and provides a more reliable data basis for risk assessment. Finally, by combining heavy metal concentrations, environmental risk weights and sample quality coefficients, an ecological risk index is generated, and a comprehensive risk level assessment is performed based on this. This method more comprehensively reflects the potential ecological and health risks of heavy metals in sediments;

[0053] The present invention not only improves the accuracy of sediment heavy metal pollution analysis, but also ensures the comprehensiveness and reliability of the results. It can automatically process large amounts of data, reduce human errors, and provide multi-dimensional pollution assessments, helping researchers and decision makers to more accurately understand environmental risks and develop more scientific governance plans, thereby promoting the efficiency and effectiveness of pollution control work. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the system module flow of the present invention.

[0055] Figure 2 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0056] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0057] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0058] Example:

[0059] See also Figure 1 The present invention provides a sediment heavy metal pollution analysis system, the specific steps include:

[0060] The sediment collection module is used to collect sediment samples at different depths in the water area through a columnar sampler with adjustable depth. The sampler is equipped with multiple layers of independently sealed sampling chambers, each of which can be opened and closed at a predetermined depth to obtain sediment samples;

[0061] The depth control module is used to monitor the depth and position of the sampler in the water in real time, ensuring that the sampler accurately samples at the designated location and depth. It measures water pressure changes based on depth sensor technology and converts them into depth data. It sets the target depth, compares it with the current depth to determine whether the target position has been reached, and makes adjustments.

[0062] The sample processing module is used to perform automated preprocessing operations on the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generates a sample quality coefficient to improve the accuracy of subsequent detection and analysis;

[0063] The detection and analysis module is used to detect the treated sediments. The sample is detected based on the spectral analysis technology. The light absorption intensity of the light of the specific wavelength emitted by the light source is measured after passing through the decomposed elements in the sample. The concentration data of the heavy metal elements in the elements contained in the sediments is calculated.

[0064] The risk assessment module is used to evaluate the potential risks of sediments to ecosystems and human health. The ecological risk index is generated based on the heavy metal concentration data, combined with its environmental risk weight and the obtained sample quality coefficient. The risk level is set and compared with the ecological risk index to determine the degree of heavy metal pollution in the sediments and the waters in which they are located.

[0065] It should be noted that since sediments may have different pollution characteristics at different depths, collecting sediments at a certain depth may make the data uniform, which is not conducive to comprehensive analysis. A device is needed to capture the vertical distribution of heavy metal pollution, help to more comprehensively analyze the pollution status of sediments, reveal the temporal and spatial variation characteristics of pollution sources, and accurately collect sediment samples from different depths in the water. This multi-layer independently closed sampling chamber design ensures that samples collected at a predetermined depth are not contaminated by other levels.

[0066] Therefore, it is necessary to collect sediment samples at different depths in the water body, based on the following methods:

[0067] The stratified sampling method is used to collect sediment samples at different depths by setting up multiple independent closed sampling chambers. The sampler sinks to a predetermined depth, and each chamber automatically opens and collects samples when it reaches the predetermined depth, ensuring a comprehensive analysis of the pollution situation at different levels of the water body. The formula is:

[0068]

[0069] The predetermined sampling depth of the i-th sampling chamber is set to Hi , L represents the total sinking depth of the sampler, N represents the number of chambers, and i represents the index of the sampling chamber sequence; the above formula can help determine the specific depth position of the sampler in the water body at a specific point in time. By subtracting the distance from the chamber to the top of the sampler from the total depth, the exact water depth of the chamber during sampling can be determined, ensuring that each chamber collects samples in different water layers.

[0070] It should be noted that in water bodies, environmental conditions at different depths may vary significantly, such as temperature, pressure, chemical composition, etc. The depth control module ensures that the sampler can reach and maintain the specified depth to obtain accurate samples. Without precise depth control, the sampler may not be able to accurately reach the target depth, resulting in sediments or water from other water layers being mixed into the sample, affecting the experimental results and data accuracy. The depth control module can effectively avoid this situation and ensure that the collected samples are pure and representative.

[0071] Therefore, it is necessary to measure the water pressure changes based on depth sensor technology and convert them into depth data. The method is based on:

[0072] The depth sensor installed on the sampler measures the water pressure at the water depth where the sampler is located in real time. The measured water pressure is converted into the current depth data of the sampler using the relationship formula between water pressure and depth. The formula is:

[0073]

[0074] Among them, d(t) represents the depth of the sampler at time t, P(t) represents the water pressure measured at time t, ρ represents the density of water, g represents the acceleration of gravity, and P0 represents the atmospheric pressure. In the above formula, it is reflected that the water pressure changes positively with the depth. By measuring the water pressure, the current depth can be inferred and calculated by inverse operation. The water pressure value monitored in real time by the depth sensor is converted into depth data for controlling and analyzing the position of the sampler.

[0075] It should be noted that accurately reaching the target depth is the key to underwater sampling, because the position of the sampler directly affects the representativeness of the sampling and the reliability of the experimental results. By measuring and calculating the current depth in real time, the system can correct the deviation in time to ensure that the sampler stably approaches and stays at the target depth.

[0076] Therefore, it is necessary to set the target depth, compare it with the current depth to determine whether the target position has been reached, and make adjustments based on the following method:

[0077] The target depth is preset in the system. The current water pressure is measured in real time. The current depth is calculated using the relationship between water pressure and water depth. The difference between the target depth and the current depth is obtained. Based on this difference, it is determined whether the depth of the sampler needs to be adjusted and the direction of the sampler adjustment. The proportional-integral-differential control algorithm is used to gradually approach the target depth. The logic is as follows:

[0078] Δd(i, t) = d(t) - H i

[0079]

[0080] Wherein, Δd(i, t) represents the depth error of the i-th sampling chamber at time t, Q(i, t) represents the adjustment judgment value of the sampler at time t when the i-th sampling chamber is needed for sampling, u(i, t) represents the control signal issued at time t when the i-th sampling chamber is needed for sampling, and the control signal is used to adjust the movement of the sampler, k p , K i , K d Respectively represent the proportional, integral and differential control coefficients, H i Indicates the predetermined sampling depth; From the above formula, it can be seen that Δd is the core variable of the control system, which reflects the deviation between the current depth of the sampler and the target depth. Q is a specific logical judgment used to determine whether the sampler needs to be adjusted and the direction of adjustment. It is the initial decision of the control algorithm. u(t) is the PID control algorithm, which accurately controls the movement of the sampler. K p , K i , k d The size relationship is: k p >K i >K d The specific reason is that K p ×Δd(i, t) is proportional control, which adjusts the output by the current error and has high response sensitivity. p If it is less than K i and K d , which will cause the system to respond slowly and the system to receive signals late; K i ×∫Δd(i, t)dt is integral control, which is adjusted according to the accumulated value of the error to eliminate the continuous deviation, and K i Should be an intermediate value, if K i Value greater than K p , the system will be too sensitive to the cumulative error, resulting in system instability and integral saturation. If it is less than K d , which will cause the system to accumulate errors slowly, and it will be difficult for the system to adjust the control algorithm immediately after Δd is generated. It is a differential control, which is adjusted based on the rate of change of the error, K d is the minimum, because the differential control is used to suppress the rate of change of the error and prevent the system from overshooting and oscillation. d Greater than K p and K i , which will make the system too sensitive to noise, so K d Setting it to the minimum value can effectively reduce system overshoot and oscillation and improve system stability.

[0081] It should be noted that sediment samples usually contain moisture. The main purpose of drying is to remove the moisture to ensure that no errors are introduced during subsequent processing and analysis due to different moisture content. The crushing process can break the sediment samples into smaller particles, increase the surface area of ​​the sample, and thus improve the rate and uniformity of subsequent chemical reactions. In order to ensure the consistency of the sample, the sample should be homogenized so that the components of the sample are evenly distributed throughout the sample, thereby ensuring that each time the sample is sampled and analyzed, the composition of the sample represents the whole, rather than the deviation of a certain part.

[0082] Therefore, it is necessary to dry, crush and homogenize the sediment samples in order to improve the accuracy of subsequent detection and analysis. The method is based on:

[0083] The sample is placed in a dryer, and the water in the sample is evaporated by controlling the temperature and time until the sample mass no longer changes. The dried sediment sample is crushed to a certain particle size using a mechanical crushing device to increase the surface area of ​​the sample, ensure the uniformity of the sample and the sufficiency of the subsequent chemical reaction. The sample is fully mixed by stirring to ensure that the composition of the sample is evenly distributed in space to eliminate the discreteness between samples. The sample mass coefficient is calculated based on the formula:

[0084]

[0085] Among them, δ represents the sample quality coefficient, m h Indicates the mass of the sample after drying, m q Indicates the mass of the sample before drying.

[0086] It should be noted that the detection module based on spectral analysis technology can accurately determine the concentration of heavy metal elements in the sample. Spectral analysis technology has high sensitivity and can detect trace or even trace amounts of heavy metal elements in the sample. It can also provide high specificity and can distinguish the absorption peaks of different elements, which makes it possible to perform multi-element analysis on complex samples. High sensitivity and specificity ensure the reliability and accuracy of the test results, which is particularly critical when it is necessary to identify and measure low-concentration pollutants.

[0087] Therefore, it is necessary to measure the light absorption intensity and calculate the concentration data of heavy metal elements in the elements contained in the sediment. The method is based on:

[0088] After the treated sample is atomized, the heavy metals in the sample are decomposed into free atoms. The free atoms absorb light of a specific wavelength in the ground state. The heavy metal atoms in the sample absorb part of the light, resulting in a decrease in the light intensity of the sample. By measuring the intensity of the absorbed light, the concentration data of the heavy metal elements in the sample is calculated based on the formula:

[0089]

[0090] Among them, C m A(i, j) represents the concentration of the jth heavy metal in the sample of the i-th sampling chamber, A(i, j) represents the absorbance of the jth heavy metal element in the sample of the i-th sampling chamber, ε(j) represents the molar absorptivity of the jth heavy metal, and l represents the optical path length of the sample. In the above formula, A(i, j) is the absorbance, which is a dimensionless quantity used to indicate how much light the sample absorbs. The higher the absorbance, the more light the sample absorbs. ε(j) represents the ability of each mole of substance to absorb light at a specific wavelength. This value is inherent in the substance and determines its absorption efficiency for light of a specific wavelength in the ground state. The basic principle formula of light absorption describes the degree to which light is weakened due to absorption when passing through a sample. By measuring the intensity difference between the incident light and the transmitted light, the absorbance A(i, j) of the sample can be calculated. The absorbance is directly related to the concentration of heavy metals in the sample. The molar absorptivity is a known constant. Therefore, by measuring the absorbance and optical path length, the concentration of heavy metals in the sample can be inferred.

[0091] It should be noted that a quantitative ecological risk index is generated by combining heavy metal concentrations, environmental risk weights and sample quality coefficients. This quantitative assessment method can convert complex pollution conditions into an easy-to-understand value or level, which not only reflects the actual situation of heavy metal pollution, but also provides a unified scale so that the pollution conditions in different regions or time periods can be objectively compared.

[0092] Therefore, it is necessary to assess the potential risks of sediments to ecosystems and human health. Based on the heavy metal concentration data, combined with its environmental risk weight and the obtained sample quality coefficient, an ecological risk index is generated. The method is as follows:

[0093] The heavy metal concentration components were determined, and the heavy metal background values ​​and heavy metal toxicity coefficients of the waters where the sediments were located were collected as reference benchmarks for the assessment. The pollution index of a single heavy metal and the average pollution index of all heavy metals were calculated. The ecological risk index was generated by combining the environmental risk weight and the sample quality coefficient. The formula is:

[0094]

[0095] Among them, PI j represents the pollution index of the jth heavy metal, B m (i, j) represents the background value of the jth heavy metal in the sample of the i-th sampling chamber, represents the toxicity coefficient of the jth heavy metal, represents the environmental risk weight of the jth heavy metal, CPI represents the comprehensively generated ecological risk index, j represents the index of heavy metals, m represents the number of heavy metal types, and N represents the number of compartments; in the above formula, the heavy metal background value can be obtained by utilizing the existing historical monitoring data to obtain the heavy metal background value of the target waters or similar waters; the toxicity coefficient is a parameter to measure the toxicity of a certain heavy metal to the environment and organisms, which is usually obtained from ecotoxicology research and reflects the potential harm of heavy metals to the ecosystem. The toxicity coefficient is usually based on laboratory toxicology research to determine the median lethal concentration or median lethal dose of a certain heavy metal to a specific organism. The following is the range of values ​​for the common heavy metal toxicity coefficients. The toxicity coefficient of mercury ranges from (40-100). Mercury is highly toxic and can The toxicity coefficient of cadmium ranges from (30-70), which is harmful to the kidneys and bones, and long-term exposure can lead to serious health problems; the toxicity coefficient of lead ranges from (20-50), which can cause damage to the nervous system, especially to children; the toxicity coefficient of arsenic ranges from (10-30), which is carcinogenic, and long-term intake can cause skin lesions and cancer; the toxicity coefficient of chromium ranges from (5-20), and hexavalent chromium is highly toxic, and long-term exposure can cause skin and respiratory diseases; it should be noted that the range of toxicity coefficients depends on the chemical properties of each heavy metal and its mechanism of influence on the organism. For example, mercury and cadmium are particularly toxic to the nervous system and kidneys, and the higher the toxicity of the heavy metal, the smaller the range of toxicity coefficients.

[0096] It should be noted that through this comprehensive assessment, potential environmental problems can be identified earlier and early warnings can be issued in a timely manner. This forward-looking risk management helps to take measures before pollution problems worsen and reduce the long-term harm of environmental pollution to ecosystems and human health. The visualization of risk levels and comparative analysis with the ecological risk index can more intuitively convey the status and risks of pollution to the public. The public can use this information to more clearly understand the extent of environmental risks, thereby enhancing their environmental awareness.

[0097] Therefore, it is necessary to set the risk level and compare it with the ecological risk index to determine the degree of heavy metal pollution in sediments and waters. The method is based on:

[0098] According to the size of the comprehensive ecological risk index, the risk level is divided into the following categories: when CPI≤150, it is a low risk level, indicating that the degree of heavy metal pollution is low, the ecological environment of sediments and waters is relatively safe, and the impact on aquatic organisms and ecosystems can be ignored; when 150≤CPI≤300, it is a medium risk level, indicating that the degree of heavy metal pollution is moderate, which may have a certain negative impact on the ecosystems of sediments and waters, and there are certain ecological risks; when CPI≥300, it is a high risk level, indicating that heavy metal pollution is serious, posing a significant threat to the ecosystems of sediments and waters, and causing harm to aquatic organisms and human health.

[0099] See also Figure 2 The present invention also provides a method for analyzing heavy metal pollution in sediments, comprising:

[0100] Step 1: Collect sediment samples at different depths in the water area through a depth-adjustable columnar sampler, which has multiple layers of independently sealed sampling chambers inside. Each chamber can be opened and closed at a predetermined depth to obtain sediment samples;

[0101] Step 2: Monitor the depth and position of the sampler in the water in real time to ensure that the sampler accurately samples at the designated location and depth. Use depth sensor technology to measure water pressure changes and convert them into depth data. Set the target depth, compare it with the current depth to determine whether the target position has been reached, and make adjustments.

[0102] Step 3: Automated preprocessing of the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generating sample quality coefficients to improve the accuracy of subsequent detection and analysis.

[0103] Step 4: Detect the treated sediments based on spectral analysis technology. The sample is detected by using the characteristics of the atoms of heavy metal elements in the sample absorbing light under the radiation of light of a specific wavelength. After the light of a specific wavelength emitted by the light source passes through the decomposed elements in the sample, its light absorption intensity is measured to calculate the concentration data of the heavy metal elements in the elements contained in the sediments.

[0104] Step 5: Assess the potential risks of sediments to ecosystems and human health. Generate an ecological risk index based on heavy metal concentration data, combined with environmental risk weights and the obtained sample quality coefficient. Set the risk level and compare it with the ecological risk index to determine the degree of heavy metal pollution in sediments and the waters in which they are located.

[0105] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0106] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A sediment heavy metal pollution analysis system, characterized in that: The analysis system comprises: The sediment collection module is used to collect sediment samples at different depths in the water area through a columnar sampler with adjustable depth. The sampler is equipped with multiple layers of independently sealed sampling chambers, each of which can be opened and closed at a predetermined depth to obtain sediment samples; The depth control module is used to monitor the depth and position of the sampler in the water in real time, ensuring that the sampler accurately samples at the designated location and depth. It measures water pressure changes based on depth sensor technology and converts them into depth data. It sets the target depth, compares it with the current depth to determine whether the target position has been reached, and makes adjustments. The sample processing module is used to perform automated preprocessing operations on the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generates a sample quality coefficient to improve the accuracy of subsequent detection and analysis; The detection and analysis module is used to detect the treated sediments. The sample is detected based on the spectral analysis technology. The light absorption intensity of the light of the specific wavelength emitted by the light source is measured after passing through the decomposed elements in the sample. The concentration data of the heavy metal elements in the elements contained in the sediments is calculated. The risk assessment module is used to evaluate the potential risks of sediments to ecosystems and human health. The ecological risk index is generated based on the heavy metal concentration data, combined with its environmental risk weight and the obtained sample quality coefficient. The risk level is set and compared with the ecological risk index to determine the degree of heavy metal pollution in the sediments and the waters in which they are located.

2. A sediment heavy metal pollution analysis system according to claim 1, characterized in that: Sediment samples were collected at different depths in the water body, based on the following methods: The stratified sampling method is used to collect sediment samples at different depths by setting up multiple independent closed sampling chambers. The sampler sinks to a predetermined depth, and each chamber automatically opens and collects samples when it reaches the predetermined depth, ensuring a comprehensive analysis of the pollution situation at different levels of the water body. The formula is: The predetermined sampling depth of the i-th sampling chamber is set to H i , L represents the total sinking depth of the sampler, N represents the number of chambers, and i represents the index of the sampling chamber sequence.

3. A sediment heavy metal pollution analysis system according to claim 1, characterized in that: The depth sensor technology is used to measure water pressure changes and convert them into depth data based on the following method: The depth sensor installed on the sampler measures the water pressure at the water depth where the sampler is located in real time. The measured water pressure is converted into the current depth data of the sampler using the relationship formula between water pressure and depth. The formula is: Among them, d(t) represents the depth of the sampler at time t, P(t) represents the water pressure measured at time t, ρ represents the density of water, g represents the acceleration of gravity, and P0 represents the atmospheric pressure.

4. A sediment heavy metal pollution analysis system according to claim 3, characterized in that: Set the target depth, compare it with the current depth to determine whether the target position has been reached, and make adjustments based on the following method: The target depth is preset in the system. The current water pressure is measured in real time. The current depth is calculated using the relationship between water pressure and water depth. The difference between the target depth and the current depth is obtained. Based on this difference, it is determined whether the depth of the sampler needs to be adjusted and the direction of the sampler adjustment. The proportional-integral-differential control algorithm is used to gradually approach the target depth. The logic is as follows: Δd(i,t)=d(t)-H i Wherein, Δd(i, t) represents the depth error of the i-th sampling chamber at time t, Q(i, t) represents the adjustment judgment value of the sampler at time t when the i-th sampling chamber needs to be used for sampling, u(i, t) represents the control signal issued at time t when the i-th sampling chamber needs to be used for sampling, and the control signal is used to adjust the movement of the sampler, K p , K i , K d Respectively represent the proportional, integral and differential control coefficients, H i Indicates the predetermined sampling depth.

5. A sediment heavy metal pollution analysis system according to claim 1, characterized in that: Sediment samples were dried, crushed, and homogenized in order to improve the accuracy of subsequent testing and analysis, based on the following methods: The sample is placed in a dryer, and the water in the sample is evaporated by controlling the temperature and time until the sample mass no longer changes. The dried sediment sample is crushed to a certain particle size using a mechanical crushing device to increase the surface area of ​​the sample, ensure the uniformity of the sample and the sufficiency of the subsequent chemical reaction. The sample is fully mixed by stirring to ensure that the composition of the sample is evenly distributed in space to eliminate the discreteness between samples. The sample mass coefficient is calculated based on the formula: Among them, δ represents the sample quality coefficient, m h Indicates the mass of the sample after drying, m q Indicates the mass of the sample before drying.

6. A sediment heavy metal pollution analysis system according to claim 1, characterized in that: The light absorption intensity is measured and the concentration data of heavy metal elements in the elements contained in the sediment is calculated based on the following method: After the treated sample is atomized, the heavy metals in the sample are decomposed into free atoms. The free atoms absorb light of a specific wavelength in the ground state. The heavy metal atoms in the sample absorb part of the light, resulting in a decrease in the light intensity of the sample. By measuring the intensity of the absorbed light, the concentration data of the heavy metal elements in the sample is calculated based on the formula: Among them, C m (i, j) represents the concentration of the jth heavy metal in the sample of the i-th sampling chamber, A(i, j) represents the absorbance of the jth heavy metal element in the sample of the i-th sampling chamber, ε(j) represents the molar absorption coefficient of the jth heavy metal, and l represents the optical path length of the sample.

7. A sediment heavy metal pollution analysis system according to claim 6, characterized in that: To assess the potential risks of sediments to ecosystems and human health, an ecological risk index is generated based on heavy metal concentration data, combined with environmental risk weights and the obtained sample quality coefficients. The method is as follows: The heavy metal concentration components were determined, and the heavy metal background values ​​and heavy metal toxicity coefficients of the waters where the sediments were located were collected as reference benchmarks for the assessment. The pollution index of a single heavy metal and the average pollution index of all heavy metals were calculated. The ecological risk index was generated by combining the environmental risk weight and the sample quality coefficient. The formula is: Among them, PI j represents the pollution index of the jth heavy metal, B m (i, j) represents the background value of the jth heavy metal in the sample of the i-th sampling chamber, represents the toxicity coefficient of the jth heavy metal, represents the environmental risk weight of the j-th heavy metal, CPI represents the comprehensively generated ecological risk index, j represents the index of heavy metals, m represents the number of heavy metal types, and N represents the number of compartments.

8. A sediment heavy metal pollution analysis system according to claim 7, characterized in that: The risk level is set to be compared with the ecological risk index to determine the degree of heavy metal pollution in sediments and waters. The method is based on: According to the size of the comprehensive ecological risk index, the risk level is divided into the following categories: when CPI≤150, it is a low risk level, indicating that the degree of heavy metal pollution is low, the ecological environment of sediments and waters is relatively safe, and the impact on aquatic organisms and ecosystems can be ignored; when 150≤CPI≤300, it is a medium risk level, indicating that the degree of heavy metal pollution is moderate, which may have a certain negative impact on the ecosystems of sediments and waters, and there are certain ecological risks; when CPI≥300, it is a high risk level, indicating that heavy metal pollution is serious, posing a significant threat to the ecosystems of sediments and waters, and causing harm to aquatic organisms and human health.

9. A sediment heavy metal pollution analysis method, the sediment heavy metal pollution analysis method is used to execute the sediment heavy metal pollution analysis system according to any one of claims 1 to 8, comprising: Step 1: Collect sediment samples at different depths in the water area through a depth-adjustable columnar sampler, which has multiple layers of independently sealed sampling chambers inside. Each chamber can be opened and closed at a predetermined depth to obtain sediment samples; Step 2: Monitor the depth and position of the sampler in the water in real time to ensure that the sampler accurately samples at the designated location and depth. Use depth sensor technology to measure water pressure changes and convert them into depth data. Set the target depth, compare it with the current depth to determine whether the target position has been reached, and make adjustments. Step 3: Automated preprocessing of the collected sediment samples. Each subunit in the module performs specific sample preprocessing, drying, crushing, and homogenizing the sediment samples in sequence, and generating sample quality coefficients to improve the accuracy of subsequent detection and analysis. Step 4: Detect the treated sediments based on spectral analysis technology. The sample is detected by using the characteristics of the atoms of heavy metal elements in the sample absorbing light under the radiation of light of a specific wavelength. After the light of a specific wavelength emitted by the light source passes through the decomposed elements in the sample, its light absorption intensity is measured to calculate the concentration data of the heavy metal elements in the elements contained in the sediments. Step 5: Assess the potential risks of sediments to ecosystems and human health. Generate an ecological risk index based on heavy metal concentration data, combined with environmental risk weights and the obtained sample quality coefficient. Set the risk level and compare it with the ecological risk index to determine the degree of heavy metal pollution in sediments and the waters in which they are located.

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