Ecological Risk Prediction Method for Offshore Floating Structures

Abstract

The present invention relates to the technical field of offshore floating structures, and specifically relates to a method for predicting the ecological risks of offshore floating structures, comprising the following steps: S1, data collection: collecting environmental data around the offshore floating structure; S2, data preprocessing: preprocessing the collected environmental data; S3, sediment ecological toxicity analysis: evaluating the impact of pollutants in sediments on marine organisms and the ecological environment; S4, establishing an ecological risk model: predicting the ecological risks of the offshore floating structure; S5, model training and verification: adjusting the parameters of the ecological risk model; S6, risk assessment: predicting the risks of the offshore floating structure to the surrounding ecological environment; S7, report generation: generating an ecological risk assessment report based on the risk prediction results output by the ecological risk model. The present invention can comprehensively and accurately predict the potential risks of offshore floating structures to the surrounding ecological environment.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore floating structures, and particularly to a method for predicting the ecological risk of offshore floating structures. Background Art

[0002] With the continuous deepening of ocean development and utilization, offshore floating structures (such as offshore wind power platforms, marine aquaculture facilities, and ocean observation stations, etc.) are widely used globally. However, while these structures bring economic and social benefits, they also pose potential risks and impacts on the marine ecological environment. For example, floating structures may cause changes in seawater flow and sediment distribution, leading to the accumulation of pollutants in local sea areas, and further affecting the survival and reproduction of surrounding marine organisms. Therefore, it becomes particularly important to evaluate and predict the risks of offshore floating structures to the ecological environment.

[0003] Existing ecological risk assessment methods usually focus on the analysis of single factors, lack of comprehensive integration of multi-dimensional environmental data, and cannot accurately predict the pollutant diffusion and biological exposure processes in complex marine ecosystems. In addition, traditional models often ignore the transfer and biological magnification effects of pollutants in the food chain, resulting in greater uncertainty in the risk assessment results.

[0004] The present invention provides a method for predicting the ecological risk of offshore floating structures, aiming to comprehensively evaluate and predict the impacts of offshore floating structures on the surrounding ecological environment by integrating various environmental data and advanced ecological risk models. Summary of the Invention

[0005] Based on the above purposes, the present invention provides a method for predicting the ecological risk of offshore floating structures.

[0006] The method for predicting the ecological risk of offshore floating structures includes the following steps:

[0007] S1, Data collection: Collect environmental data around the offshore floating structure through various sensors and remote sensing technologies. The environmental data includes water quality parameters, biodiversity data, meteorological data, and ocean dynamics data;

[0008] S2, Data preprocessing: Preprocess the collected environmental data, including cleaning, noise reduction, and completion;

[0009] S3, Sediment ecological toxicity analysis: Collect seabed sediment samples around the offshore floating structure, conduct chemical and ecological toxicity analyses, evaluate the impacts of pollutants in the sediment on marine organisms and the ecological environment, and predict the diffusion path and ecological impacts of sediment pollution by establishing a sediment - organism model;

[0010] S4. Establish an ecological risk model: Combine the analysis results of sediment ecological toxicity analysis to construct an ecological risk model to predict the ecological risk of the offshore floating structure.

[0011] S5. Model training and verification: Use historical data and experimental data to train and verify the constructed ecological risk model, and adjust the parameters of the ecological risk model.

[0012] S6. Risk assessment: Input the preprocessed environmental data into the trained ecological risk model to predict the risk of the offshore floating structure to the surrounding ecological environment.

[0013] S7. Report generation: Based on the risk prediction results output by the ecological risk model, generate an ecological risk assessment report, including risk levels, impact ranges, and recommended measures.

[0014] Furthermore, the data collection in S1 includes:

[0015] Water quality parameter monitoring: Use water quality sensors (such as multi-parameter water quality detectors) to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate, and phosphate concentrations in seawater, and obtain real-time data on changes in water quality parameters.

[0016] Biodiversity data investigation: Record and analyze the types, quantities, and distributions of organisms around the offshore floating structure through underwater cameras, acoustic monitoring equipment, and environmental DNA (eDNA) sampling techniques.

[0017] Meteorological data collection: Use meteorological stations and satellite remote sensing technology to collect the wind speed, wind direction, air temperature, rainfall, and solar radiation intensity in the area where the offshore floating structure is located.

[0018] Obtain ocean dynamics data: Measure the height, period, tidal changes, sea current speed, and direction of ocean waves through wave buoys, tide gauges, and current meters.

[0019] Furthermore, the sediment ecological toxicity analysis in S3 includes:

[0020] S31. Sediment collection: Use sediment traps to collect seabed sediment samples in the area around the offshore floating structure.

[0021] S32. Chemical analysis: Conduct chemical analysis on the collected sediment samples to detect the content of pollutants in the sediment. The content of pollutants includes heavy metals, organic pollutants, and microplastics, and quantitatively analyze the composition and concentration of pollutants.

[0022] S33, Ecotoxicity Test: Conduct an ecotoxicity test on sediment samples to evaluate the toxic effects of pollutants in the sediment samples on marine organisms. Use bioindicator species (such as marine copepods, benthos, etc.) to conduct a biotoxicity experiment and measure ecotoxicity indicators. The ecotoxicity indicators include lethal concentration and growth inhibition rate;

[0023] S34, Sediment-Bio Model Establishment: Based on the results of chemical analysis and ecotoxicity tests, establish a sediment-bio model to simulate the diffusion path and ecological impact of pollutants in the sediment. Consider sediment particle migration, pollutant release, and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment.

[0024] Further, the sediment collection in S31 includes:

[0025] S311, Sampling Point Location: In the area around the offshore floating structure, determine the sediment sampling points according to ocean dynamics data and environmental conditions;

[0026] S312, Sediment Trap Selection: Select a sediment trap, including a box corer, a grab sampler, or a piston corer, and select the corresponding sediment trap according to the sediment type and sampling depth;

[0027] S313, Sediment Collection: Place the sediment trap at the determined sediment sampling point, operate the sediment trap to sink to the seabed, and close the trap through mechanical or hydraulic equipment;

[0028] S314, Sample Processing: Lift the collected sediment sample to the sea surface to avoid sediment sample loss or contamination, then transfer the sediment sample to a preset sampling container, and number and record it;

[0029] S315, Sample Preservation and Transportation: Conduct preservation treatment on the collected sediment samples, including refrigeration and sealing.

[0030] Further, the chemical analysis in S32 includes:

[0031] S321, Sample Processing: Homogenize the collected sediment samples, and then conduct drying, grinding, and sieving to prepare for chemical analysis;

[0032] S322, Heavy Metal Detection: Use strong acids (such as a mixture of nitric acid, hydrochloric acid, and hydrofluoric acid) to digest the sediment samples under high temperature and high pressure, and use an inductively coupled plasma optical emission spectrometer (ICP-OES) to detect the digested solution to quantitatively analyze the heavy metal content in the sample. The calculation formula is:

[0033] ;

[0034] Among them, is the heavy metal concentration, is the signal intensity of the sample, is the signal intensity of the blank sample, is the slope of the standard curve;

[0035] S323, Organic pollutant detection: Soxhlet extract the organic pollutants in the sediment sample using a solvent (such as dichloromethane or n-hexane), dissolve the organic pollutants in the organic solvent, purify the extract by gel permeation chromatography to remove interfering substances, obtain the organic pollutant extract, and use a gas chromatography-mass spectrometry (GC-MS) to detect the purified organic pollutant extract, quantitatively analyze the organic pollutants in the sample, and quantify the organic pollutant concentration by the internal standard method. The calculation formula is:

[0036] ;

[0037] Among them, is the organic pollutant concentration, is the peak area of the organic pollutants in the sample, is the peak area of the internal standard, is the internal standard correction factor;

[0038] S324, Microplastic detection: Separate microplastic particles from the sediment by flotation method, use a high-density solution (such as zinc chloride solution) to make the microplastics float, separate the microplastic particles, observe the morphology of the microplastic particles using a microscope, and use a Fourier transform infrared spectrometer (FTIR) for chemical composition identification, count the number and mass of the microplastic particles, and calculate the content of the microplastic particles in the sediment. The calculation formula is:

[0039] ;

[0040] Among them, is the microplastic concentration, is the number of separated microplastic particles, is the mass of the sediment sample.

[0041] Furthermore, the ecological toxicity test in S33 includes:

[0042] S331, Selection of bioindicator species: Select bioindicator species for ecological toxicity testing. The bioindicator species include marine copepods (such as marine copepods) and benthic organisms (such as water fleas, worms, etc.);

[0043] S332, Sediment sample preparation: Mix the collected sediment sample with seawater in a predetermined ratio to prepare sediment suspensions with different concentrations for ecological toxicity testing;

[0044] S333, Experimental design: Design the experimental group and the control group. In the experimental group, sediment suspensions with different concentration gradients are set, and in the control group, unpolluted sediment is used;

[0045] S334, Toxicity experiment: Place the bioindicator species in the experimental group and the control group, observe and record the biological responses within a predetermined time (such as 24 hours, 48 hours, 96 hours), and measure the ecotoxicity indicators, including the lethal concentration LC50 test and the growth inhibition rate test, where;

[0046] For the lethal concentration LC50 test, calculate the lethal concentration LC50 by recording the sediment concentration when 50% of the biological individuals in the experimental group die. The calculation formula is:

[0047] ;

[0048] where, is the sediment concentration of each concentration group, is the number of dead biological individuals in this concentration group, and N is the total number of biological individuals in all experimental groups;

[0049] For the growth inhibition rate test, calculate the growth inhibition rate by measuring the growth changes of the bioindicator species in sediment suspensions with different concentrations. The calculation formula is:

[0050] ;

[0051] where, is the growth amount of the organisms in the experimental group, is the growth amount of the organisms in the control group;

[0052] S335, Data analysis: Conduct statistical analysis on the experimental data, compare the survival rate and growth rate of the bioindicator species at different concentrations, draw the dose-response curve, and evaluate the toxicity intensity of the pollutants in the sediment.

[0053] Furthermore, the establishment of the sediment-bio model in S34 includes:

[0054] S341, Data integration: Integrate the results of sediment chemical analysis and ecotoxicity tests, including the types, concentrations of pollutants in the sediment and the ecotoxicity indicators, as the basic data for the sediment-bio model;

[0055] S342, Model construction: Based on the sediment particle migration, pollutant release and biological exposure mechanisms, construct a sediment-bio model for simulating the diffusion path and ecological impact of pollutants in the sediment, where;

[0056] The migration of sediment particles is simulated using the sediment dynamics equation, considering factors such as water flow, waves, and sedimentation. The calculation formula is as follows:

[0057] ;

[0058] where, is the sediment particle concentration, is the water flow velocity vector, is the sediment diffusion coefficient, is the sediment settlement rate;

[0059] The release of pollutants is simulated by considering the release process of pollutants from sediment particles, taking into account factors such as desorption, diffusion, and bioturbation. The calculation formula for the release rate is as follows:

[0060] ;

[0061] where, is the pollutant release rate, is the release rate constant, is the pollutant concentration in the sediment, is the sediment porosity;

[0062] The biological exposure mechanism is simulated through a biological exposure model, which simulates the process of marine organisms being exposed to pollutants through ingestion, respiration, and skin contact. The calculation formula is as follows:

[0063] ;

[0064] where, is the biological exposure dose, , , are the pollutant concentrations in water, sediment, and organisms respectively, , , are the ingestion rates in water, sediment ingestion rates, and skin absorption rates respectively;

[0065] S343, Model calibration: Use real-time sediment samples to calibrate the sediment-biological model and adjust the model parameters of the sediment-biological model;

[0066] S344, Simulation prediction: Through the calibrated sediment-biological model, simulate the diffusion path and influence range of pollutants in the sediment in the ecological environment, and predict the ecological impact of pollutants;

[0067] S345, Result analysis and application: Based on the simulation results of the sediment-biological model, evaluate the spread and impact of pollutants in the marine ecological environment.

[0068] Furthermore, the ecological risk model in S4 adopts a food web model, and the food web model includes:

[0069] S41, Initial setting of pollutant concentration: Set the initial pollutant concentrations in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is:

[0070] ;

[0071] ;

[0072] Among them, and are respectively the initial pollutant concentrations in seawater and sediment, and are the actually monitored initial concentrations;

[0073] S42, Dynamic changes of pollutants in seawater and sediment: Simulate the diffusion, adsorption, and desorption processes of pollutants in seawater and sediment, considering water flow and sediment dynamics. The calculation formula is:

[0074] ;

[0075] ;

[0076] Among them, is the adsorption rate constant, is the desorption rate constant, is the diffusion coefficient in water, is the sedimentation rate;

[0077] S43, Bioaccumulation and biomagnification: Simulate the accumulation and biomagnification effects of pollutants in organisms through ingestion and respiration. The calculation formula is:

[0078] ;

[0079] Among them, is the pollutant concentration in the i-th organism, is the absorption rate constant in water, is the absorption rate constant in sediment, is the feeding rate of the i-th organism, is the sedimentation rate constant, is the excretion rate constant;

[0080] S44, Pollutant transfer in the food chain: Simulate the transfer of pollutants in the food chain, considering the biomagnification effects between different trophic levels. The calculation formula is:

[0081] ;

[0082] Among them, is the pollutant concentration in the i-th organism, is the pollutant concentration in the j-th organism, is the biomagnification factor transferred from the j-th organism to the i-th organism;

[0083] S45, Ecological risk assessment: Evaluate the impact of pollutant concentration in organisms on the ecological environment, predict the ecological risk of offshore floating structures. The calculation formula is:

[0084] ;

[0085] Among them, is the ecological risk value of the i-th organism, is the pollutant concentration in the i-th organism, is the toxicity threshold of the i-th organism.

[0086] Furthermore, the model training and verification in S5 include:

[0087] S51, Data preparation: Collect and organize historical data and experimental data, including pollutant concentrations in historical monitored sediments and water bodies, pollutant accumulation data in organisms, and ecological toxicity experiment results;

[0088] S52, Initial model parameter setting: According to existing experiments and preliminary analysis results, set the initial parameters of the ecological risk model, including pollutant diffusion coefficient, adsorption and desorption rates, and biological absorption and excretion rates;

[0089] S53, Model training: Input historical data and experimental data into the ecological risk model, simulate the distribution and transfer process of pollutants in sediments, water bodies and organisms, compare the predicted results of the ecological risk model with the actual data, and calculate the prediction error through root mean square error (RMSE) and mean absolute percentage error (MAPE). The calculation formulas are:

[0090] ;

[0091] ;

[0092] Among them, is the value of the i-th data point predicted by the ecological risk model, is the value of the i-th data point of actual monitoring, and n is the total number of data points;

[0093] S54, Parameter adjustment: According to the error analysis results, adjust the parameters of the ecological risk model to reduce the prediction error. The calculation formula is:

[0094] ;

[0095] Among them, is the adjusted parameter value, is the parameter value before adjustment, is the actual monitored data, is the prediction result of the ecological risk model;

[0096] S55, Model verification: Use independent data sets at different times or locations as verification data, input the verification data into the trained ecological risk model, run the simulation and predict the diffusion path and biological exposure of pollutants, compare the actual detection data of the verification data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, calculate the verification error, and the verification formula is:

[0097] ;

[0098] S56, Model optimization: Optimize the parameters of the ecological risk model according to the verification error and performance evaluation results.

[0099] Furthermore, the risk assessment in S6 includes:

[0100] S61, Data input: Input the preprocessed environmental data into the trained and verified ecological risk model;

[0101] S62, Model operation: Run the ecological risk model to simulate the diffusion path, transfer process and accumulation of pollutants in sediments, water bodies and organisms;

[0102] S63, Pollutant diffusion and absorption simulation: Use the ecological risk model to simulate the diffusion of pollutants in water bodies and sediments, as well as the absorption and biomagnification effects in organisms, and generate pollutant concentration distribution data at different time points;

[0103] S64, Food chain transfer simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the pollutant concentration in each organism;

[0104] S65, Ecological risk assessment: Calculate the ecological risk value of each organism according to the pollutant concentration data output by the ecological risk model , evaluate the toxic effects of pollutants on organisms, and according to the calculated ecological risk value , classify the ecological risks into different levels, identify risk areas and biological groups at different levels;

[0105] S66, Impact range analysis: Analyze the impact range and intensity of pollutants on different ecological environment components (such as fish, benthic organisms, plankton, etc.).

[0106] Advantages of the present invention:

[0107] In the present invention, through a variety of sensors and remote sensing technologies, multi-dimensional environmental data including water quality parameters, biodiversity data, meteorological data, and ocean dynamics data are collected to ensure the comprehensiveness and accuracy of the data. Through systematic preprocessing and sediment ecological toxicity analysis, the impact of pollutants in sediments on marine organisms and the ecological environment is evaluated, and through a sediment-biological model, the diffusion path and ecological impact of pollutants are simulated, enabling a comprehensive and accurate prediction of the potential risks of offshore floating structures to the surrounding ecological environment.

[0108] In the present invention, by combining the results of sediment ecological toxicity analysis through a food web model, the dynamic changes of pollutants in water, sediment, and organisms can be more accurately simulated, considering the adsorption, desorption, diffusion of pollutants, as well as the accumulation and biomagnification effects in organisms. Through model training and verification, historical data and experimental data are used to calibrate and optimize model parameters to ensure the high precision and reliability of the model. This model can predict the transfer process of pollutants in the food chain, evaluate the toxic effects of pollutants on organisms at different trophic levels, and provide a scientific ecological risk assessment.

[0109] In the present invention, by inputting the preprocessed environmental data into the trained and verified ecological risk model, the model is run to simulate the diffusion path and influence range of pollutants in the ecological environment, generating a detailed ecological risk assessment report. This method can identify high-risk areas and biological groups, provide data on the diffusion path and concentration distribution of pollutants, analyze the impact of pollutants on different ecosystem components, provide important scientific basis for environmental protection and management decision-making, and improve the accuracy and reliability of prediction. Brief Description of the Drawings

[0110] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0111] Figure 1 Schematic diagram of the prediction method process for the embodiment of the present invention;

[0112] Figure 2 Schematic diagram of the sediment ecological toxicity analysis for the embodiment of the present invention. Detailed Embodiments

[0113] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the following further details the present invention in combination with specific embodiments.

[0114] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0115] As Figure 1 - Figure 2 shown, the ecological risk prediction method for offshore floating structures includes the following steps:

[0116] S1, Data collection: Collect the environmental data around the offshore floating structure through a variety of sensors and remote sensing technologies. The environmental data includes water quality parameters, biodiversity data, meteorological data, and ocean dynamics data;

[0117] S2, Data preprocessing: Preprocess the collected environmental data, including cleaning, noise reduction, and completion, to ensure the integrity and accuracy of the data;

[0118] S3, Sediment ecological toxicity analysis: Collect the seabed sediment samples around the offshore floating structure, conduct chemical and ecological toxicity analyses, evaluate the impact of pollutants in the sediment on marine organisms and the ecological environment, and predict the diffusion path and ecological impact of sediment pollution by establishing a sediment - organism model;

[0119] S4, Establish an ecological risk model: Combine the analysis results of sediment ecological toxicity analysis to construct an ecological risk model to predict the ecological risk of offshore floating structures;

[0120] S5, Model training and verification: Use historical data and experimental data to train and verify the constructed ecological risk model, and adjust the parameters of the ecological risk model to improve the prediction accuracy;

[0121] S6, Risk assessment: Input the preprocessed environmental data into the trained ecological risk model to predict the risk of offshore floating structures to the surrounding ecological environment;

[0122] S7, Report generation: Generate an ecological risk assessment report based on the risk prediction results output by the ecological risk model, including risk levels, impact ranges, and recommended measures;

[0123] Through the above steps, integrating various environmental data and analysis techniques to provide comprehensive and accurate ecological risk prediction for offshore floating structures, which helps to improve the accuracy and reliability of the prediction and provides important scientific basis for environmental protection and management decision-making.

[0124] The data collection in S1 includes:

[0125] Water quality parameter monitoring: Using water quality sensors (such as multi-parameter water quality detectors) to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate and phosphate concentrations in seawater, and obtaining real-time data on the changes of water quality parameters;

[0126] Biodiversity data investigation: Through underwater cameras, acoustic monitoring equipment and environmental DNA (eDNA) sampling techniques, recording and analyzing the types, quantities and distributions of organisms around offshore floating structures, with special attention to communities such as plankton, benthic organisms and fish;

[0127] Meteorological data collection: Using meteorological stations and satellite remote sensing technologies to collect wind speed, wind direction, air temperature, rainfall and solar radiation intensity in the area where the offshore floating structure is located, ensuring comprehensive coverage of the changes in meteorological conditions;

[0128] Obtaining ocean dynamics data: Through wave buoys, tide gauges and current meters, measuring the height, period of ocean waves, tidal changes, current speed and direction, providing detailed data support for the flow characteristics of the ocean environment;

[0129] Through the comprehensive application of the above-mentioned various sensors and remote sensing technologies, it is possible to comprehensively and accurately collect the environmental data around offshore floating structures, providing a reliable data basis for subsequent ecological risk prediction.

[0130] The sediment ecological toxicity analysis in S3 includes:

[0131] S31, Sediment collection: Using sediment traps to collect seabed sediment samples in the area around the offshore floating structure, ensuring that the samples are representative and of sufficient quantity to reflect the characteristics of the regional sediment;

[0132] S32, Chemical analysis: Conducting chemical analysis on the collected sediment samples to detect the content of pollutants in the sediment, and the content of pollutants includes heavy metals, organic pollutants, microplastics, and quantitatively analyzing the composition and concentration of pollutants;

[0133] S33, Ecotoxicity test: Conducting an ecotoxicity test on the sediment samples to evaluate the toxic effects of pollutants in the sediment samples on marine organisms. Using bioindicator species (such as marine copepods, benthic organisms, etc.) to conduct bio-toxicity experiments and measuring ecotoxicity indicators, and the ecotoxicity indicators include lethal concentration, growth inhibition rate;

[0134] S34, Sediment - organism model establishment: Based on the results of chemical analysis and ecotoxicity tests, establish a sediment - organism model to simulate the diffusion path and ecological impact of pollutants in sediments, considering sediment particle migration, pollutant release, and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment;

[0135] Through the above steps, comprehensively evaluate the impact of pollutants in sediments on marine organisms and the ecological environment, and predict their diffusion path and long - term ecological impact through the model, providing a scientific basis for the ecological risk prediction of offshore floating structures.

[0136] The sediment collection in S31 includes:

[0137] S311, Locating sampling points: In the surrounding area of the offshore floating structure, determine the sediment sampling points according to ocean dynamics data and environmental conditions to ensure that the sediment samples reflect the characteristics of the regional sediments;

[0138] The specific steps for locating sampling points include:

[0139] Analysis of sea current and wave data: Use equipment such as current meters and wave buoys to collect ocean dynamics data such as sea current velocity, direction, and wave height, analyze the characteristics of water body flow and energy distribution, and select areas where sediments are likely to deposit and accumulate;

[0140] Submarine topography survey: Through multi - beam sonar or side - scan sonar equipment, draw a submarine topographic map, identify the undulations and changes in the submarine topography, and select areas with relatively flat terrain and thick sediments as sampling points;

[0141] Monitoring of water quality parameters: Combine the data of water quality sensors to monitor the suspended sediment concentration and sediment particle characteristics in the water body, and select areas with relatively high suspended sediment concentration and easy sediment formation;

[0142] Assessment of environmental conditions: Consider environmental conditions such as seasonal changes, weather conditions, and human activities, and select areas with less external interference and long - term stability for sampling;

[0143] Reference to historical data: Use existing sediment sampling and analysis data, refer to the location and sediment characteristics of historical sampling points, and optimize the current sampling point layout;

[0144] S312, Selection of sediment traps: Select sediment traps, including box corers, grab samplers, or piston corers, and select the corresponding sediment traps according to the sediment type and sampling depth;

[0145] The specific selection of sediment traps includes:

[0146] Determine sediment type: Collect preliminary data on the sediment type in the collection area, and determine the main sediment types (such as muddy, sandy, mixed sediments, etc.) through historical records or preliminary surveys;

[0147] Determine sampling depth: According to the research objectives and analysis requirements, determine the sediment depth to be collected (surface layer, shallow layer, deep layer);

[0148] Select a suitable sampler: For surface muddy sediments, select a box corer to maintain stratification. For surface mixed or coarse-grained sediments, select a grab sampler to obtain a large-area sample. For deep sediments, select a piston corer to obtain a complete vertical profile;

[0149] Consider equipment and operating conditions: Ensure that the selected equipment is suitable for the vessel and operating conditions to avoid affecting the sampling effect due to equipment limitations;

[0150] S313, Sediment collection: Deploy a sediment sampler at the determined sediment sampling point, operate the sediment sampler to sink to the seabed, ensure that the sampler is in full contact with and penetrates the sediment layer, and close the sampler through mechanical or hydraulic equipment to ensure the integrity and representativeness of the sediment sample;

[0151] S314, Sample processing: Lift the collected sediment sample to the sea surface to avoid loss or contamination of the sediment sample, then transfer the sediment sample to a preset sampling container, and number and record it to ensure that the source and characteristics of each sample are clear;

[0152] S315, Sample preservation and transportation: Conduct preservation treatment on the collected sediment sample, including refrigeration and sealing, ensure that the sample is not contaminated or degraded during transportation, and send it to the laboratory for subsequent analysis in a timely manner;

[0153] Through the above steps, use a sediment sampler to collect seabed sediment samples in the area around the offshore floating structure, ensure the representativeness and integrity of the samples, and provide a reliable basis for subsequent chemical and ecotoxicity analyses.

[0154] The chemical analysis in S32 includes:

[0155] S321, Sample processing: Homogenize the collected sediment sample to ensure its uniformity, and perform drying, grinding, and sieving to prepare for chemical analysis;

[0156] S322, Heavy metal detection: Use strong acids (such as a mixture of nitric acid, hydrochloric acid, and hydrofluoric acid) to digest the sediment sample under high temperature and high pressure to ensure that the heavy metals are completely dissolved in the solution. Use an inductively coupled plasma optical emission spectrometer (ICP-OES) to detect the digested solution and quantitatively analyze the content of heavy metals in the sample. The calculation formula is:

[0157] ;

[0158] wherein, is the heavy metal concentration, is the signal intensity of the sample, is the signal intensity of the blank sample, is the slope of the standard curve;

[0159] The slope of the standard curve is obtained as follows:

[0160] (1) Prepare standard solutions with known concentrations: Prepare a series of standard solutions with known concentrations, and the concentration of each solution should cover the expected range of the concentration of the sample to be measured;

[0161] (2) Measure the signal intensity of each standard solution: Use appropriate instruments (such as spectrometers, colorimeters, conductivity meters, etc.) to measure the signal intensity of each standard solution, and these signal intensities will correspond to the concentrations of the solutions;

[0162] (3) Plot the relationship graph of concentration - signal intensity: Plot the concentrations (x - axis) of the standard solutions against the corresponding signal intensities (y - axis) on the graph paper, and in the graph, a trend close to a straight line will appear;

[0163] (4) Calculate the slope through linear regression: Use the linear regression analysis method to fit these data points into a straight line, and the straight - line equation is expressed as:

[0164] y = mx + b;

[0165] wherein, y is the signal intensity, x is the concentration, and m is the slope, representing the change in signal intensity caused by a unit change in concentration;

[0166] (5) Obtain the slope of the standard curve: The slope m calculated through regression analysis is the slope of the standard curve ;

[0167] S323, Detection of organic pollutants: Use a solvent (such as dichloromethane or n - hexane) to perform Soxhlet extraction on the organic pollutants in the sediment sample, dissolve the organic pollutants in the organic solvent, purify the extract through gel permeation chromatography to remove interfering substances, obtain the organic pollutant extract, and use a gas chromatography - mass spectrometry (GC - MS) instrument to detect the purified organic pollutant extract, quantitatively analyze the organic pollutants in the sample, and quantify the organic pollutant concentration by the internal standard method. The calculation formula is:

[0168] ;

[0169] wherein, is the organic pollutant concentration, is the peak area of organic pollutants in the sample, is the peak area of the internal standard, is the internal standard correction factor;

[0170] S324, Microplastic detection: Microplastic particles are separated from sediments by flotation method. High-density solutions (such as zinc chloride solution) are used to make microplastics float, and then the microplastic particles are separated. The morphology of microplastic particles is observed by microscope, and Fourier Transform Infrared Spectrometer (FTIR) is used for chemical composition identification. The number and mass of microplastic particles are counted, and the content of microplastic particles in sediments is calculated. The calculation formula is:

[0171] ;

[0172] where, is the microplastic concentration, is the number of separated microplastic particles, is the mass of the sediment sample;

[0173] Through the above steps, chemical analysis is carried out on the collected sediment samples to detect the contents of heavy metals, organic pollutants and microplastics in the sediments, and by quantitatively analyzing the composition and concentration of pollutants, reliable scientific data are provided for the ecological risk prediction of offshore floating structures.

[0174] The eco-toxicity tests in S33 include:

[0175] S331, Selection of bioindicator species: Bioindicator species are selected for eco-toxicity tests. Bioindicator species include marine copepods (such as marine copepods) and benthic organisms (such as water fleas, worms, etc.), and these species are sensitive to environmental pollutants and are easy to culture;

[0176] S332, Preparation of sediment samples: The collected sediment samples are mixed with seawater in a predetermined ratio to prepare sediment suspensions with different concentrations for eco-toxicity tests;

[0177] S333, Experimental design: Experimental groups and control groups are designed. Different concentration gradients of sediment suspensions are set in the experimental groups, and pollution-free sediments are used in the control group to ensure the reliability and comparability of experimental results;

[0178] S334, Toxicity experiment: The bioindicator species are placed in the experimental groups and the control group, and the biological responses within a predetermined time (such as 24 hours, 48 hours, 96 hours) are observed and recorded, and eco-toxicity indexes are measured, including lethal concentration LC50 test and inhibition growth rate test, where;

[0179] The lethal concentration LC50 test calculates the lethal concentration LC50 by recording the sediment concentration when 50% of the biological individuals in the experimental group die. The calculation formula is:

[0180] ;

[0181] where, is the sediment concentration of each concentration group, is the number of dead biological individuals in this concentration group, and N is the total number of biological individuals in all experimental groups;

[0182] The growth inhibition rate test calculates the growth inhibition rate by measuring the growth changes of biological indicator species in sediment suspensions at different concentrations. The calculation formula is:

[0183] ;

[0184] where, is the growth amount of organisms in the experimental group, is the growth amount of organisms in the control group;

[0185] S335, Data analysis: Statistically analyze the experimental data, compare the survival rate and growth rate of biological indicator species at different concentrations, draw a dose-response curve, and evaluate the toxicity intensity of pollutants in the sediment;

[0186] Through the above steps, use biological indicator species to conduct an ecotoxicity test on sediment samples, determine ecotoxicity indicators such as lethal concentration and growth inhibition rate, evaluate the toxic effects of pollutants in the sediment on marine organisms, and provide reliable biotoxicity data for the ecological risk prediction of offshore floating structures.

[0187] The establishment of the sediment - organism model in S34 includes:

[0188] S341, Data integration: Integrate the results of sediment chemical analysis and ecotoxicity tests, including the types, concentrations of pollutants in the sediment and ecotoxicity indicators, as the basic data for the sediment - organism model;

[0189] S342, Model construction: Based on sediment particle migration, pollutant release and biological exposure mechanisms, construct a sediment - organism model to simulate the diffusion path and ecological impact of pollutants in the sediment, where;

[0190] The sediment particle migration simulates the migration of sediment particles in the water body using the sediment dynamics equation, considering factors such as water flow, waves and sedimentation. The calculation formula is:

[0191] ;

[0192] where, is the sediment particle concentration, is the water flow velocity vector, is the sediment diffusion coefficient, is the sediment settling rate;

[0193] Pollutant release is through simulating the release process of pollutants from sediment particles, considering the factors of desorption, diffusion, and bioturbation. The calculation formula for the release rate is:

[0194] ;

[0195] where, is the pollutant release rate, is the release rate constant, is the pollutant concentration in the sediment, is the sediment porosity;

[0196] The biological exposure mechanism is through a biological exposure model to simulate the process of marine organisms being exposed to pollutants through the pathways of ingestion, respiration, and skin contact. The calculation formula is:

[0197] ;

[0198] where, is the biological exposure dose, , , are the pollutant concentrations in water, sediment, and organisms respectively, , , are the ingestion rates in water, sediment ingestion rate, and skin absorption rate respectively;

[0199] S343, Model calibration: Use real-time sediment samples to calibrate the sediment-biological model, adjust the model parameters of the sediment-biological model to ensure the accuracy and reliability of the model;

[0200] Model calibration and verification specifically include:

[0201] S3431, Real-time sediment sample collection and processing: Regularly collect sediment samples in the area around the offshore floating structure, process and analyze the samples to obtain pollutant concentration data and sediment characteristic data;

[0202] S3432, Initial model parameter setting: Based on the results of chemical analysis and ecotoxicity tests, set the initial parameters of the sediment-biological model, including sediment diffusion coefficient, pollutant release rate, biological exposure rate;

[0203] S3433, Model Calibration: Input the pollutant concentration and sediment property data in real-time sediment samples into the model, run the initially set sediment-biological model to simulate the diffusion path of pollutants and the biological exposure situation, compare the simulation results output by the model with the real-time sediment sample data, calculate the prediction error, and gradually adjust the model parameters such as the sediment diffusion coefficient, pollutant release rate, and biological exposure rate according to the error analysis results to make the model prediction results more consistent with the actual monitoring data. The adjustment formula is:

[0204] ;

[0205] Among them, is the adjusted parameter value, is the parameter value before adjustment, is the real-time sediment sample, is the model prediction result;

[0206] S344, Simulation Prediction: Through the calibrated sediment-biological model, simulate the diffusion path and influence range of pollutants in the sediment in the ecological environment, and predict the ecological impact of pollutants;

[0207] S345, Result Analysis and Application: Based on the simulation results of the sediment-biological model, evaluate the spread and impact of pollutants in the marine ecological environment, and provide a scientific basis for ecological risk assessment and management;

[0208] Through the above steps, simulate the diffusion path and ecological impact of pollutants in the sediment, ensure the accuracy and reliability of the model. This method can provide detailed predictions of pollutant diffusion and biological exposure, provide a scientific basis for ecological risk assessment and environmental management decisions, and improve the real-time and regional applicability of predictions.

[0209] The ecological risk model in S4 adopts a food web model, and the food web model includes:

[0210] S41, Initial Setting of Pollutant Concentration: Set the initial pollutant concentration in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is:

[0211] ;

[0212] ;

[0213] Among them, and are the initial pollutant concentrations in seawater and sediment respectively, and are the actually monitored initial concentrations;

[0214] S42, Dynamic Changes of Pollutants in Seawater and Sediment: Simulate the diffusion, adsorption, and desorption processes of pollutants in seawater and sediment, considering water flow and sediment dynamics. The calculation formula is:

[0215] ;

[0216] ;

[0217] Wherein, is the adsorption rate constant, is the desorption rate constant, is the diffusion coefficient in water, is the sedimentation rate;

[0218] S43, Bioaccumulation and Biomagnification: Simulate the accumulation and biomagnification effects of pollutants in organisms through ingestion and respiration. The calculation formula is:

[0219] ;

[0220] Wherein, is the pollutant concentration in the i-th organism, is the absorption rate constant in water, is the absorption rate constant in sediment, is the feeding rate of the i-th organism, is the sedimentation rate constant, is the excretion rate constant;

[0221] S44, Pollutant Transfer in the Food Chain: Simulate the transfer of pollutants in the food chain, considering the biomagnification effect between different trophic levels. The calculation formula is:

[0222] ;

[0223] Wherein, is the pollutant concentration in the i-th organism, is the pollutant concentration in the j-th organism, is the biomagnification factor transferred from the j-th organism to the i-th organism;

[0224] S45, Ecological Risk Assessment: Evaluate the impact of pollutant concentration in organisms on the ecological environment and predict the ecological risks of offshore floating structures. The calculation formula is:

[0225] ;

[0226] Wherein, is the ecological risk value of the i-th organism, is the pollutant concentration in the i-th organism, is the toxicity threshold of the i-th organism;

[0227] Through the above food web model, combined with the results of sediment ecological toxicity analysis, the diffusion path of pollutants in the ecological environment around the offshore floating structure and the accumulation process in organisms can be more accurately simulated. In particular, the dynamic changes of pollutants in water and sediment, the absorption and amplification effects in organisms, and the transfer process in the food chain are considered, making the model more suitable for predicting the ecological risks of offshore floating structures. In this way, a more scientific ecological risk assessment can be provided, providing a reliable basis for environmental protection and management decisions.

[0228] The model training and verification in S5 include:

[0229] S51, Data preparation: Collect and organize historical data and experimental data, including the pollutant concentrations in historical monitored sediment and water, the pollutant accumulation data in organisms, and the results of ecological toxicity experiments;

[0230] S52, Initial model parameter setting: According to the existing experiments and preliminary analysis results, set the initial parameters of the ecological risk model, including pollutant diffusion coefficients, adsorption and desorption rates, and biological absorption and excretion rates;

[0231] S53, Model training: Input the historical data and experimental data into the ecological risk model, simulate the distribution and transfer process of pollutants in sediment, water, and organisms, compare the prediction results of the ecological risk model with the actual data, and calculate the prediction error through the root mean square error (RMSE) and mean absolute percentage error (MAPE). The calculation formulas are:

[0232] ;

[0233] ;

[0234] Among them, is the value of the i-th data point predicted by the ecological risk model, is the value of the i-th data point actually monitored, and n is the total number of data points;

[0235] S54, Parameter adjustment: According to the error analysis results, adjust the parameters of the ecological risk model to reduce the prediction error. The calculation formula is:

[0236] ;

[0237] Among them, is the adjusted parameter value, is the parameter value before adjustment, is the actually monitored data, is the prediction result of the ecological risk model;

[0238] S55, Model Validation: Use independent datasets from different times or locations as validation data. Input the validation data into the trained ecological risk model, run the simulation, and predict the diffusion path of pollutants and the biological exposure. Compare the actual detection data of the validation data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, calculate the validation error, and the validation formula is:

[0239] ;

[0240] S56, Model Optimization: According to the validation error and performance evaluation results, optimize the parameters of the ecological risk model to ensure the applicability and stability of the model under different environmental conditions;

[0241] Through the above steps, use historical data and experimental data to train and validate the constructed ecological risk model, adjust the model parameters, improve the accuracy and reliability of the model, and provide a scientific basis for the ecological risk prediction of offshore floating structures.

[0242] The risk assessment in S6 includes:

[0243] S61, Data Input: Input the preprocessed environmental data into the trained and validated ecological risk model;

[0244] S62, Model Run: Run the ecological risk model to simulate the diffusion path, transfer process, and accumulation of pollutants in sediments, water bodies, and organisms;

[0245] S63, Pollutant Diffusion and Absorption Simulation: Use the ecological risk model to simulate the diffusion of pollutants in water bodies and sediments, as well as the absorption and biomagnification effects in organisms, and generate pollutant concentration distribution data at different time points;

[0246] S64, Food Chain Transfer Simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the pollutant concentration in each organism;

[0247] S65, Ecological Risk Assessment: According to the pollutant concentration data output by the ecological risk model, calculate the ecological risk value of each organism , evaluate the toxic effects of pollutants on organisms, and according to the calculated ecological risk value , classify the ecological risk into different levels, identify risk areas and biological groups at different levels;

[0248] S66, Impact Range Analysis: Analyze the impact range and intensity of pollutants on different ecological environment components (such as fish, benthic organisms, plankton, etc.);

[0249] Through the above steps, using the ecological risk model, the preprocessed environmental data is input into the model to simulate the diffusion path and influence range of pollutants in the ecological environment, predict the ecological impact of pollutants, and provide a scientific basis for environmental management and decision-making.

[0250] Those of ordinary skill in the art should understand that the discussion of any embodiment above is only exemplary and is not intended to imply that the scope of the present invention is limited to these examples; under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the present invention as described above, which are not provided in detail for the sake of brevity.

[0251] The present invention is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for predicting ecological risks of offshore floating structures, characterized in that: The following steps are involved: S1, Data Collection: Collect environmental data around offshore floating structures through a variety of sensors and remote sensing technologies. Environmental data include water quality parameters, biodiversity data, meteorological data, and ocean dynamics data; S2, data preprocessing: preprocessing the collected environmental data, including cleaning, noise reduction and completion; S3, Sediment Ecotoxicity Analysis: Collect seabed sediment samples around offshore floating structures for chemical and ecotoxicity analysis to assess the impact of pollutants in sediments on marine organisms and the ecological environment, and predict the diffusion path and ecological impact of sediment pollution by establishing a sediment-organism model; S4, Establishing an ecological risk model: Based on the results of sediment ecotoxicity analysis, an ecological risk model is constructed to predict the ecological risks of offshore floating structures; S5, model training and verification: use historical data and experimental data to train and verify the constructed ecological risk model, and adjust the parameters of the ecological risk model; S6, risk assessment: input the pre-processed environmental data into the trained ecological risk model to predict the risk of offshore floating structures to the surrounding ecological environment; S7, report generation: based on the risk prediction results output by the ecological risk model, generate an ecological risk assessment report, including risk level, impact scope and recommended measures; The ecological risk model in S4 adopts a food web model, which includes: S41, initial setting of pollutant concentration: Set the initial pollutant concentration in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is: C w,0 =C w,init ; C s,0 =C s,init ; Among them, C w,0 and C s,0 are the initial pollutant concentrations in seawater and sediment, respectively, C w,init and C s,init is the initial concentration actually monitored; S42, Dynamic changes of pollutants in seawater and sediments: Simulate the diffusion, adsorption and desorption of pollutants in seawater and sediments, taking into account the water flow and sediment dynamics. The calculation formula is: Among them, k ad is the adsorption rate constant, k des is the desorption rate constant, D w is the diffusion coefficient in water, R s is the deposition rate; S43, Bioabsorption and Biomagnification: Simulate the accumulation and biomagnification effect of pollutants in organisms through ingestion and respiration. The calculation formula is: Among them, C b,i is the pollutant concentration in the i-th organism, k bw is the absorption rate constant in water, k bs is the absorption rate constant in the sediment, IR i is the feeding rate of the i-th organism, k dep,i is the deposition rate constant, k excr,i is the excretion rate constant; S44, Pollutant transfer in the food chain: simulate the transfer of pollutants in the food chain, taking into account the biomagnification effect between different trophic levels. The calculation formula is: Among them, C b,i is the pollutant concentration in the i-th organism, C b,j is the pollutant concentration in the jth organism, BAF ij is the biomagnification factor from the jth organism to the ith organism; S45, Ecological Risk Assessment: Assess the impact of pollutant concentrations in organisms on the ecological environment and predict the ecological risk of offshore floating structures. The calculation formula is: Among them, R i is the ecological risk value of the i-th organism, C b,i is the pollutant concentration in the i-th organism, T b,i is the toxicity threshold of the i-th organism.

2. The method for predicting ecological risks of offshore floating structures according to claim 1, characterized in that: The data collection in S1 includes: Water quality parameter monitoring: Use water quality sensors to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate and phosphate concentration in seawater, and obtain real-time data on water quality parameter changes; Biodiversity data survey: Record and analyze the species, quantity and distribution of organisms around floating structures at sea through underwater cameras, acoustic monitoring equipment and environmental DNA sampling technology; Meteorological data collection: using meteorological stations and satellite remote sensing technology to collect wind speed, wind direction, temperature, rainfall and solar radiation intensity in the area where the offshore floating structure is located; Ocean dynamics data acquisition: Using wave buoys, tide gauges, and current meters to measure the height, period, tidal changes, current speed, and direction of ocean waves.

3. The method for predicting ecological risks of offshore floating structures according to claim 1, characterized in that: The sediment ecotoxicity analysis in S3 includes: S31, Sediment Collection: Collect seafloor sediment samples in the area around the offshore floating structure using a sediment trap; S32, chemical analysis: chemical analysis of the collected sediment samples to detect the content of pollutants in the sediments, including heavy metals, organic pollutants, and microplastics, and quantitatively analyze the composition and concentration of pollutants; S33, Ecotoxicity Test: Conduct ecotoxicity tests on sediment samples to evaluate the toxic effects of pollutants in sediment samples on marine organisms, use biological indicator species to conduct biological toxicity experiments, and determine ecotoxicity indicators, including lethal concentration and growth inhibition rate; S34, Sediment-Organism Model Establishment: Based on the results of chemical analysis and ecotoxicity testing, a sediment-organism model is established to simulate the diffusion path and ecological impact of pollutants in sediments, consider sediment particle migration, pollutant release and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment.

4. The method for predicting ecological risks of offshore floating structures according to claim 3, characterized in that: The sediment collection in S31 includes: S311, Locate sampling points: Determine sediment sampling points in the area around the floating structure at sea based on ocean dynamics data and environmental conditions; S312, sediment trap selection: select a sediment trap, including a box-type mud sampler, a grab bucket mud sampler or a columnar mud sampler, and select the corresponding sediment trap according to the sediment type and sampling depth; S313, sediment collection: placing sediment traps at the determined sediment sampling points, operating the sediment traps to sink to the seafloor, and closing the traps by mechanical or hydraulic equipment; S314, sample processing: lifting the captured sediment samples to the sea surface to avoid loss or contamination of the sediment samples, and then transferring the sediment samples to the preset sampling containers, and numbering and recording them; S315, Sample preservation and transportation: Preservation of collected sediment samples, including refrigeration and sealing.

5. The method for predicting ecological risks of offshore floating structures according to claim 4, characterized in that: The chemical analysis in S32 includes: S321, Sample processing: homogenize, dry, grind and sieve the collected sediment samples in preparation for chemical analysis; S322, heavy metal detection: Use strong acid to digest the sediment sample at high temperature and high pressure, use inductively coupled plasma emission spectrometer to detect the digested solution, and quantitatively analyze the content of heavy metals in the sample. The calculation formula is: Among them, C 重金属 is the heavy metal concentration, I 样品 is the signal intensity of the sample, I 空白 is the signal intensity of the blank sample, S 标准曲线 is the slope of the standard curve; S323, organic pollutant detection: Use solvent to perform Soxhlet extraction on organic pollutants in sediment samples, dissolve organic pollutants in organic solvents, purify the extract by gel permeation chromatography, remove interfering substances, obtain organic pollutant extracts, detect the purified organic pollutant extracts by gas chromatography-mass spectrometry, quantitatively analyze organic pollutants in samples, and quantify organic pollutant concentrations by internal standard method. The calculation formula is: Among them, C 有机污染物 is the concentration of organic pollutants, A 样品 is the peak area of ​​organic pollutants in the sample, A 内标 is the peak area of ​​the internal standard, F 内标 is the internal standard correction factor; S324, Microplastic Detection: Microplastic particles are separated from sediments by flotation, and microplastic particles are floated by high-density solution to separate them. The morphology of microplastic particles is observed by microscope, and the chemical composition is identified by Fourier transform infrared spectrometer. The number and mass of microplastic particles are counted, and the content of microplastic particles in sediments is calculated. The calculation formula is: Among them, C 微塑料 is the concentration of microplastics, N 微塑料 is the number of separated microplastic particles, M 沉积物 is the mass of the sediment sample.

6. The method for predicting ecological risks of offshore floating structures according to claim 5, characterized in that: The ecotoxicity tests in S33 include: S331, Selection of bio-indicator species: Select bio-indicator species for ecotoxicity testing. Bio-indicator species include marine copepods and benthic organisms; S332, sediment sample preparation: the collected sediment samples are mixed with seawater in a predetermined ratio to prepare sediment suspensions of different concentrations for ecotoxicity testing; S333, Experimental design: Design an experimental group and a control group. The experimental group is set with sediment suspensions of different concentration gradients, and the control group uses uncontaminated sediments; S334, toxicity test: placing biological indicator species in experimental and control groups, observing and recording biological responses within a predetermined period of time, and determining ecotoxicity indicators, including lethal concentration LC50 test and growth inhibition rate test, among which; The lethal concentration LC50 test records the sediment concentration when 50% of the biological individuals in the experimental group die, and calculates the lethal concentration LC50. The calculation formula is: Among them, C i is the sediment concentration of each concentration group, M i is the number of dead organisms in this concentration group, and N is the total number of organisms in all experimental groups; The growth inhibition test measures the growth changes of biological indicator species in sediment suspensions of different concentrations and calculates the growth inhibition rate. The calculation formula is: Among them, G 实验组 is the growth of organisms in the experimental group, G 对照组 is the growth of organisms in the control group; S335, Data Analysis: Perform statistical analysis on experimental data, compare the survival and growth rates of bio-indicator species at different concentrations, draw dose-response curves, and evaluate the toxicity intensity of pollutants in sediments.

7. The method for predicting ecological risks of offshore floating structures according to claim 6, characterized in that: The sediment-organism model establishment in S34 includes: S341, Data Integration: Integrate the results of sediment chemical analysis and ecotoxicity testing, including the types, concentrations, and ecotoxicity indicators of pollutants in sediments, as basic data for the sediment-organism model; S342, Model Construction: Based on the mechanisms of sediment particle migration, pollutant release and biological exposure, a sediment-organism model is constructed to simulate the diffusion path and ecological impact of pollutants in sediments, including; The sediment particle migration uses the sediment dynamics equation to simulate the migration of sediment particles in the water body, taking into account the factors of water flow, waves and sedimentation. The calculation formula is: Among them, G s is the sediment particle concentration, is the water velocity vector, D s is the sediment diffusion coefficient, R s is the sediment settling rate; The pollutant release is calculated by simulating the release process of pollutants from sediment particles, taking into account factors such as desorption, diffusion and bioturbation. The release rate is calculated as follows: R p =k d ·C p ·(1-θ); Among them, R p is the pollutant release rate, k d is the release rate constant, C p is the pollutant concentration in the sediment, θ is the sediment porosity; The biological exposure mechanism simulates the process of marine organisms being exposed to pollutants through ingestion, respiration and skin contact through a biological exposure model. The calculation formula is: Among them, D e is the biological exposure dose, C w , C s , C b are the pollutant concentrations in water, sediment and organisms, IR w IR s IR b They are the water ingestion rate, sediment ingestion rate, and skin absorption rate; S343, model calibration: using real-time sediment samples to calibrate the sediment-organism model and adjust the model parameters of the sediment-organism model; S344, simulation prediction: Use a calibrated sediment-organism model to simulate the diffusion path and impact range of pollutants in sediments in the ecological environment and predict the ecological impact of pollutants; S345, Result Analysis and Application: Evaluate the spread and impact of pollutants in the marine ecological environment based on the results of sediment-organism model simulation.

8. The method for predicting ecological risks of offshore floating structures according to claim 7, characterized in that: The model training and verification in S5 includes: S51, Data Preparation: Collect and organize historical data and experimental data, including historical monitoring of pollutant concentrations in sediments and water bodies, pollutant accumulation data in organisms, and ecotoxicity experimental results; S52, initial model parameter setting: according to the existing experimental and preliminary analysis results, the initial parameters of the ecological risk model are set, including pollutant diffusion coefficient, adsorption and desorption rate, biological absorption and excretion rate; S53, model training: input historical data and experimental data into the ecological risk model, simulate the distribution and transfer process of pollutants in sediments, water bodies and organisms, compare the prediction results of the ecological risk model with the actual data, and calculate the prediction error through the root mean square error and mean absolute percentage error. The calculation formula is: Among them, O model,i is the value of the ith data point predicted by the ecological risk model, O real,i is the value of the ith data point actually monitored, and n is the total number of data points; S54, parameter adjustment: According to the error analysis results, adjust the ecological risk model parameters to reduce the prediction error. The calculation formula is: Among them, P new is the adjusted parameter value, P old is the parameter value before adjustment, O real is the actual monitoring data, O model Predict results for ecological risk models; S55, Model Validation: Use independent data sets from different times or locations as validation data, input the validation data into the trained ecological risk model, run simulations and predict the diffusion path and biological exposure of pollutants, compare the actual test data of the validation data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, and calculate the validation error. The validation formula is: S56, Model optimization: Optimize ecological risk model parameters based on validation errors and performance evaluation results.

9. The method for predicting ecological risks of offshore floating structures according to claim 8, characterized in that: The risk assessment in S6 includes: S61, Data input: Input the preprocessed environmental data into the trained and validated ecological risk model; S62, model operation: Run the ecological risk model to simulate the diffusion path, transfer process and accumulation of pollutants in sediments, water bodies and organisms; S63, Pollutant diffusion and absorption simulation: Use ecological risk models to simulate the diffusion of pollutants in water and sediments, as well as the absorption and biomagnification effects in organisms, to generate pollutant concentration distribution data at different time points; S64, Food Chain Transfer Simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the concentration of pollutants in each organism; S65, Ecological Risk Assessment: Calculate the ecological risk value R for each organism based on the pollutant concentration data output by the ecological risk model. i , assess the toxic effects of pollutants on organisms, based on the calculated ecological risk value R i , classify ecological risks into different levels, and identify risk areas and biological groups at different levels; S66, Impact Scope Analysis: Analyze the scope and intensity of the impact of pollutants on different ecological and environmental components.

Images