A model and method for simulating the marine environmental behavior and food web transfer of typical persistent organic pollutants

Abstract

The present application belongs to the field of environmental pollution and environmental chemistry, and particularly relates to a model and method for simulating the marine environmental behavior and food web migration of typical persistent organic pollutants. The model comprises atmosphere, seawater (including suspended particles), sediment (including pore water), and a food web unit composed of multi-trophic level organisms (including plankton, benthos and fish of different diets). The present application integrates biological energy science and input parameters of aquaculture activities (such as feed delivery, residual feed loss, and fecal excretion), and constructs a multi-medium non-steady-state fate model of the aquaculture marine ecosystem. The model can accurately quantify the cross-medium flux of organic pollutants (such as PFAS, PCBs, DDTs, pesticides, etc.) between the "aquaculture source-environment-organism", realizes the quantitative tracing of the environmental contribution rate of aquaculture activities, and can predict the temporal and spatial distribution and enrichment level of pollutants in wild fish, thereby providing a scientific basis for the ecological risk management of the marine aquaculture area and the overall marine environment.

Description

Technical Field

[0001] This invention belongs to the field of environmental pollution and environmental chemistry, and in particular relates to a model and method for simulating the marine environmental behavior and food web migration of typical persistent organic pollutants. Background Technology

[0002] Persistent organic pollutants (POPs) are a class of globally prevalent chemical substances characterized by environmental persistence, bioaccumulation, biotoxicity, and long-distance transport. Traditional methods for controlling POPs involve environmental and biological risk assessments of the target study area. The advantage of these methods is that they can immediately provide an instantaneous concentration of POPs in the environment or organisms. However, the development of POPs in the environment is a non-steady-state process; many natural factors influence their concentration. Traditional methods cannot explain the migration of POPs across multiple environmental media, cannot account for bioaccumulation and amplification, and cannot achieve continuous monitoring or future prediction.

[0003] To address this, existing research (Mackay D. Multimedia environmental models: The fugacity approach, second edition [M]. 2nd edition. Boca Raton: CRC Press, 2001) has found that the environmental behavior of organic pollutants in multimedia environments is not random; the capacity of the environmental media determines their distribution, migration, and transformation rates. This has led to the establishment of the fugacity theory and models based on this theory. The fugacity model, based on the mass balance law, establishes a numerical model based on the quantitative expression of semi-volatile organic chemicals in multimedia ecological environments. Through inputs and outputs, it simulates and predicts the behavioral fate of pollutants in the real environment. Furthermore, some scholars have already conducted research on the migration of organic pollutants between environmental media based on this theory. For example, they have used fugacity models to simulate the migration and fate of polybrominated diphenyl ethers (PBDEs) in the environment using Guangzhou as the research area; constructed a four-level fugacity model to simulate the migration of four isomers of hexachlorocyclohexane (HCHs) in the environment over time using Beijing as the research area; and established a four-level, multi-media dynamic fugacity model to simulate the fate of four isomers of HCHs in the lower reaches of the Yellow River Basin from 1952 to 2010. Although the simulation results can well reveal the long-term changing trend of HCHs in the environment caused by pesticide application, the following shortcomings still exist.

[0004] (1) Existing multi-media fugacity models mainly focus on terrestrial ecosystems or lake systems, with limited research on pollutant behavior in marine environments, especially coastal aquaculture areas. These models typically treat the study area as a single homogeneous system, failing to distinguish the distribution characteristics of pollutants at different spatial scales. For example, they cannot simultaneously simulate the potential high pollution load in local aquaculture areas and the average pollution level of the entire sea area. (2) Existing models mainly focus on the behavior of pollutants in abiotic environmental media, lacking consideration for marine food web ecosystems. (3) There is a lack of systematic mechanistic description of the physiological processes of pollutant absorption, metabolism, and excretion in aquatic organisms. (4) The impact of marine aquaculture activities as a source of pollutant emissions has not been effectively integrated. (5) Existing models lack systematic integration of key parameters such as pollutant content in aquaculture feed, feed loss rate, and the absorption and metabolism of pollutants by farmed fish, making it impossible to quantitatively assess the contribution of aquaculture activities relative to other pollution sources (such as atmospheric deposition and river input). Summary of the Invention

[0005] To address the aforementioned issues, this application discloses a model and method for simulating the marine environmental behavior of pollutants and their migration through food webs. This model is based on fugacity theory and couples a multi-media environmental fate model with a bioenergetics model. By constructing a set of unsteady mass balance equations that include inputs from aquaculture activities, it achieves dynamic simulation of the spatiotemporal migration and fate of organic pollutants in the "atmosphere-seawater-sediment-food web" system.

[0006] To achieve the above objectives, the first technical solution of this application discloses a model for simulating the marine environmental behavior of target pollutants and food web migration. This model is an improved fugacity model based on fugacity theory, comprising:

[0007] Coupled atmospheric units, seawater units, sediment units, and multitrophic biological units are interconnected through a set of unsteady mass balance differential equations.

[0008] The differential equation set of the multi-trophic-level biological unit includes a mass balance equation established for the i-th organism in each biological unit; wherein...

[0009] Pollutant capacity is measured by bioenergetics-based fugacity capacity. Characterization, its calculation formula simultaneously considers the differential distribution of lipids, proteins and water in the organism;

[0010] Pollutant intake includes gill respiration intake, dietary intake, and predatory intake, which are expressed via gill respiration intake transfer coefficients. Dietary intake and predator intake transfer coefficients Characterization;

[0011] Furthermore, in the mass balance equation of the multitrophic level biological unit, the dietary intake term defines the feeding of wild fish at high trophic levels on escaped farmed feed, which is used to characterize the indirect effects of aquaculture activities through the food web;

[0012] The mass balance equation of the seawater unit includes an ocean current input term and a feed loss term used to characterize the impact of aquaculture activities.

[0013] The mass balance equation of the sediment unit includes a term for feed loss and a term for fish manure loss, which characterize the impact of aquaculture activities.

[0014] The target pollutants include at least one of perfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs), and pesticides.

[0015] Furthermore, the fugacity capacity The calculation formula is:

[0016] ;

[0017] in, Represents the total Z-value of the i-th biophase. This represents the lipid content in the intestine of the i-th organism. This represents the protein content in the intestine of the i-th organism. The expression for the proportionality constant of non-lipid organic matter relative to the adsorption capacity of octanol, with a value of 0.035;

[0018] The Z-value represents the aqueous phase in a water unit, and the calculation formula is: In the formula, This represents the Z-value in the gas phase of the air unit;

[0019] The Z-value, representing biological organic matter, is calculated using the following formula: In the formula, Indicates the octanol-water partition coefficient. This represents the gas-water distribution coefficient.

[0020] Furthermore, the formula for calculating the transport coefficient of the pollutant intake item is as follows:

[0021] ;

[0022] in, Indicates the gill uptake rate, This represents the population size of the i-th organism. The Z-value represents the overall value of the water body unit.

[0023] ;

[0024] in, This represents the D value of the i-th organism through its feeding pathway. , This indicates the absorption efficiency of chemical substances in food; This represents the food intake rate of the i-th organism; The average weight of the i-th organism is expressed in kg. This represents the predation rate of organism i in preying on organism j in the food web; Let Z represent the total phase Z value of prey j as the i-th type of organism.

[0025] Furthermore, in the system of differential equations for the multi-trophic-level biological unit, the mass balance equation for the i-th organism is:

[0026] ;

[0027] in, Represents the rate of change of the mass of the target pollutant in the i-th organism over time;

[0028] It accounts for 97% of the feed for livestock;

[0029] Representative: The intake of the i-th organism from water and sediment via gill respiration, where XW is the proportion of respiration from water and XS is the proportion of respiration from sediment;

[0030] Let D represent the net predation intake and excretion of the i-th (i≠j) organism in the food web, where D Ei The D value represents the loss of feces and includes the contribution of feeding to escaped feed.

[0031] This represents the mass loss of the i-th organism due to metabolism, gill excretion, natural death, and predation; among which, The D value represents metabolic loss; The D value represents the amount of water released into the gills; The D value represents natural death; The D value represents the loss due to predation.

[0032] Furthermore, the model can support the construction of two spatial scales, including a local spatial scale model for simulating a single aquaculture farm and its surrounding sea area, and a regional spatial scale model for simulating multiple aquaculture farms or the entire sea area.

[0033] The second technical solution of this application discloses a method for simulating the marine environmental behavior and food web migration of target pollutants, including the following steps:

[0034] S1. Construct a model to simulate the marine environmental behavior and food web migration of the target pollutants mentioned above;

[0035] S2. Solve the unsteady mass balance differential equations of the model to obtain the dynamic concentration and migration flux of the target pollutant in each unit and obtain the simulation results;

[0036] S3. Based on the simulation results, quantify the contribution of aquaculture activity input sources to the accumulation of target pollutants in the environment and food web.

[0037] Furthermore, the step of quantifying the contribution rate is implemented through a scenario comparison method, specifically including: a scenario with aquaculture is defined as one that includes the sum of ocean current input and aquaculture feed loss in the seawater unit, and the sum of aquaculture feed loss and farmed fish feces in the sediment unit; a scenario without aquaculture is one that does not include aquaculture feed loss in the seawater unit, only retains ocean current input, does not include aquaculture feed loss and farmed fish feces in the sediment unit, and does not include feeding on escaped aquaculture feed in the biological unit. The difference between the simulation results obtained by running the models with and without aquaculture scenarios is used to calculate the contribution rate of aquaculture activities.

[0038] The third technical solution of this application discloses a system for simulating the marine environmental behavior of pollutants and food web migration, including a processor and a memory. The memory stores a computer program. When the processor executes the program, it is used to construct and solve the model of the simulated marine environmental behavior of target pollutants and food web migration, and to execute the above-mentioned method steps.

[0039] as well as,

[0040] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method.

[0041] A pollution source apportionment and risk assessment method is characterized by applying the model simulating the marine environmental behavior and food web migration of the target pollutant, and quantitatively calculating the contribution rate of aquaculture by running comparative scenarios with and without aquaculture activity input sources; and / or assessing the health risks to consumers based on the bioaccumulation level of pollutants in organisms output by the model; wherein the target pollutant includes PFAS compounds.

[0042] Beneficial Effects: This invention establishes a model and method for simulating the marine environmental behavior of pollutants and food web migration (CFAME). The model includes the atmosphere, seawater (containing suspended particles), sediments (containing pore water), and food web units composed of organisms at multiple trophic levels (including plankton, benthic organisms, and fish with different diets). Based on traditional fugacity theory, this invention innovatively integrates bioenergetics and aquaculture activity input parameters (such as feed input, uneaten feed loss, and fecal excretion) to construct a multi-media unsteady-state homing model for aquaculture ecosystems. This model can accurately quantify the cross-media flux of organic pollutants (such as PFAS, PCBs, DDTs, pesticides, etc.) between the aquaculture source, environment, and organisms, enabling quantitative source tracing of the environmental contribution rate of aquaculture activities. It can also predict the spatiotemporal distribution and enrichment levels of pollutants in wild fish, providing a scientific basis for environmental risk management in marine aquaculture areas. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This section introduces the multi-media transmission pathways and mechanisms simulated in the model. Detailed Implementation

[0045] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0046] Fugacity models based on fugacity theory are numerical models established by applying quantitative expressions of toxic organic chemicals in multi-media ecological environments according to the law of mass balance. Through input and output, they simulate and predict the behavior and fate of pollutants in real environments (e.g., existing technology Mackay D. Multimedia environmental models: The fugacity approach, second edition[M]. 2nd edition. Boca Raton: CRC Press, 2001). These models include the atmosphere, soil, and surface water. However, for marine environments, especially coastal aquaculture areas, the models lack consideration of factors such as marine ecosystems and the impact of aquaculture activities on pollutant behavior. Therefore, they cannot simulate the marine environmental behavior and food web migration processes of target pollutants.

[0047] Therefore, the first embodiment of this application discloses a model for simulating the marine environmental behavior of target pollutants and food web migration. The model is an improved fugacity model based on fugacity theory, comprising:

[0048] Coupled atmospheric units, seawater units, sediment units, and multitrophic biological units are interconnected through a set of unsteady mass balance differential equations.

[0049] The differential equation set of the multi-trophic-level biological unit includes a mass balance equation established for the i-th organism in each biological unit; wherein...

[0050] Pollutant capacity is measured by bioenergetics-based fugacity capacity Z. BBi Characterization, its calculation formula simultaneously considers the differential distribution of lipids, proteins and water in the organism;

[0051] Pollutant intake includes gill respiration intake, dietary intake, and predatory intake, which are expressed via gill respiration intake transfer coefficients. Dietary intake and predator intake transfer coefficients Characterization;

[0052] Furthermore, in the mass balance equation of the multitrophic level biological unit, the dietary intake term defines the feeding of wild fish at high trophic levels on escaped farmed feed, which is used to characterize the indirect effects of aquaculture activities through the food web;

[0053] The mass balance equation of the seawater unit includes an ocean current input term and a feed loss term used to characterize the impact of aquaculture activities.

[0054] The mass balance equation of the sediment unit includes a term for feed loss and a term for fish manure loss, which characterize the impact of aquaculture activities.

[0055] The target pollutants include at least one of perfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs), and pesticides.

[0056] In this model, the atmospheric, seawater, and sediment units are conventional units set by existing fugacity models. However, for biological units, existing technologies generally only consider lipid distribution, which has the limitation of low prediction accuracy. In contrast, the multi-trophic-level biological units constructed in this application, based on a bioenergetics model, simultaneously construct biological fugacity capacity that considers the differential distribution of lipids, proteins, and water, which can more accurately predict the pollutant accumulation levels of organisms with different tissue compositions.

[0057] ;

[0058] in, Represents the total Z-value of the i-th biophase. This represents the lipid content in the intestine of the i-th organism. This represents the protein content in the intestine of the i-th organism. The expression for the proportionality constant of non-lipid organic matter relative to the adsorption capacity of octanol, with a value of 0.035;

[0059] The Z-value represents the aqueous phase in a water unit, and the calculation formula is: In the formula, This represents the Z-value in the gas phase of the air unit;

[0060] The Z-value, representing biological organic matter, is calculated using the following formula: In the formula, Indicates the octanol-water partition coefficient. This represents the gas-water distribution coefficient.

[0061] The multitrophic level biological units include phytoplankton, plankton, and benthic organisms (such as sea cucumbers) at the first level of the ocean; and fish at the second to fourth trophic levels (such as pomfret, marbled fish, scarlet wrasse, spotted fish, and blue cod). It should be noted that the organisms used to construct this model will vary depending on the species in different marine regions.

[0062] In a further embodiment, the pollutant intake item comprehensively considers the entire feeding process of a multitrophic level biological unit, including gill respiration intake, dietary intake, and predatory intake.

[0063] Furthermore, the formula for calculating the transport coefficient of the pollutant intake item is as follows:

[0064] ;

[0065] in, Indicates the gill uptake rate, This represents the population size of the i-th organism. The Z-value represents the overall sedimentary unit.

[0066] ;

[0067] in, This represents the D value of the i-th organism through its feeding pathway. , This indicates the absorption efficiency of chemical substances in food; This represents the food intake rate of the i-th organism; This represents the average weight (kg) of the i-th organism. This represents the predation rate of organism i in preying on organism j in the food web; This represents the overall Z-value of organism j as the prey;

[0068] Furthermore, if i is a benthic organism, XS cannot be ignored.

[0069] In a further implementation, to evaluate the impact of marine aquaculture activities, these activities are integrated as a specific pollutant input source into a traditional multi-media fugacity model. These activities are categorized into direct impacts on seawater and sediment units, and indirect impacts on the feeding of high-trophic-level wild fish in multi-trophic-level biological units (i.e., high-trophic-level wild fish include not only feeding on natural prey but also on escaped farmed feed). Therefore, the mass balance differential equations of the model are improved as follows:

[0070] The mass balance equation of the seawater unit includes an ocean current input term and a feed loss term used to characterize the impact of aquaculture activities.

[0071] The mass balance equation of the sediment unit includes terms for feed loss and fish manure loss, which characterize the impact of aquaculture activities:

[0072] Seawater Unit:

[0073] ;

[0074] in, The loss of aquaculture feed is represented by 1% of the total amount of aquaculture feed and 10% of the total amount of aquaculture fish feces. Characterizes ocean current inputs.

[0075] Sedimentary unit:

[0076] ;

[0077] in, It is 2% of the total amount of aquaculture feed and 90% of the total amount of aquaculture fish excrement.

[0078] The feeding of wild fish at higher trophic levels onto escaped farmed feed is defined in the dietary intake term of the mass balance equation for multitrophic level biological units. This definition characterizes the indirect effects of aquaculture activities through the food web. Specifically:

[0079] Biological unit (the i-th organism):

[0080] ;

[0081] in, Represents the rate of change of the mass of the target pollutant in the i-th organism over time;

[0082] It accounts for 97% of the feed for livestock;

[0083] Representative: The intake of the i-th organism from water and sediment via gill respiration, where XW is the proportion of respiration from water and XS is the proportion of respiration from sediment;

[0084] Let D represent the net predation intake and excretion of the i-th (i≠j) organism in the food web, where D Ei The D value represents the loss of feces and includes the contribution of feeding to escaped feed.

[0085] This represents the mass loss of the i-th organism due to metabolism, gill excretion, natural death, and predation; among which, The D value represents metabolic loss; The D value represents the amount of water released into the gills; The D value represents natural death; The D value represents the loss due to predation.

[0086] Through the above improvements, the resulting model can not only comprehensively consider the impact of marine aquaculture activities on the marine environmental behavior and food web migration of simulated target pollutants, but also, in specific applications, calculate the quantitative contribution rate of marine activities through scenario comparison. Specifically, the model first scenario, which includes all input source terms, and the model second scenario, which does not include the aquaculture activity input source terms (i.e., does not include the aquaculture feed loss term added to the mass balance equation of the seawater unit and the aquaculture fish feces term added to the sediment unit), are run. The contribution rate of aquaculture activities is calculated by comparing the simulation results of the two scenarios.

[0087] It should be noted that the above model also includes a mass balance model for the atmospheric unit, which can be constructed using existing technologies. Atmospheric unit:

[0088] .

[0089] In a further embodiment, the model can support the construction of two spatial scales, including a local spatial scale model for simulating a single aquaculture farm and its surrounding sea area, and a regional spatial scale model for simulating multiple aquaculture farms or the entire sea area.

[0090] Compared with existing fugacity models, this application achieves a higher degree of fugacity through... The calculation incorporates differences in lipid / protein components and includes sediment respiration pathways (XS term) in the mass balance equation, which significantly improves the simulation accuracy of pollutant transport in benthic organisms and complex food webs. Validation shows that the proportion of simulated values ​​deviating from measured values ​​within 10 times is over 80%.

[0091] This invention innovatively couples aquaculture feed loss and fecal discharge as independent source terms into a multi-media model, enabling quantitative differentiation between aquaculture sources and background sources, and revealing that aquaculture activities are an important source of pollutants in sediments and high-trophic-level fish.

[0092] Based on the constructed parameterized model, this invention can generate chemical spatial distribution maps according to the KOW and KAW properties of chemicals, and quickly screen out substances that are prone to sedimentation. ) or fish ( High-risk chemicals with high accumulation (within the range of 3-9).

[0093] It should be noted that the above model construction process also includes the construction of a basic parameter set for the model (such as environmental parameters of the target area, biochemical properties of target pollutants, food web structure parameters of organisms at multiple trophic levels in the target area, etc.), and the division of the collected parameters into abiotic units, biotic units or spatial scales, which are conventional methods in this field.

[0094] For example, the base dataset can be selected from the following parameters based on the characteristics of different target regions:

[0095] 1. Environmental parameters, including atmospheric area Atmospheric altitude aerosol volume fraction ( ), dry sedimentation rate Rainfall rate Removal rate (Q), sea area Seawater depth water flow Suspended particulate volume fraction ( ), water molecule diffusivity Dissolved oxygen saturation (S, %), particle density in water sediment depth Sediment water content ( ), Sediment organic carbon mass fraction (r), Dry sediment density sediment settling rate Sediment resuspension rate diffusion path length in sediments Sediment burial rate Mass transfer coefficient on the air side above the water surface air-side and water-side mass transfer coefficients Mass transfer coefficient on the water side above the sediment Temperature Wind speed Seawater temperature .

[0096] 2. Physicochemical properties of the target pollutant, including: octanol-water partition coefficient ( ), gas-water distribution coefficient ( Octyl alcohol-gas partition coefficient ( molar mass Logarithm of the air-water partition coefficient at 25°C Logarithm of octanol-gas partition coefficient at 25°C Logarithm of octanol-water partition coefficient at 25°C Chemical half-life in air Chemical half-life in water Chemical half-life in sediments supercooled liquid vapor pressure .

[0097] 3. Collect food web structure parameters, including: predator-prey relationships (the proportion of prey j to the total food intake of predator i). ), organism weight lipid fraction in organisms ( ), protein fraction in organisms ( Metabolic rate Maximum survival time Gill absorption type Average biological density Organic matter sedimentation rate ( ), adsorption affinity of nonionic organic chemicals ( ), lipid assimilation efficiency ( Protein assimilation efficiency ( ), water assimilation efficiency ( Algal gill absorption rate gill chemical transfer efficiency ( ), gill ventilation rate oxygen concentration Chemical dietary efficiency ( ), the food intake rate of predator i The dietary absorption rate of predator i biological population size Background concentration in air Background concentration in seawater Concentration in fish feed .

[0098] The spatial scale division can be as follows: For each spatial scale, a multi-media binning model structure is constructed to divide the study area into interacting abiotic and biotic units:

[0099] Abiotic units include atmospheric units (containing gaseous and aerosol phases), seawater units (containing dissolved water and suspended particulate phases), and sediment units (containing sediment solid phase and pore water phase).

[0100] Biological unit: Construct a food web structure containing multiple trophic levels, including at least plankton, benthic invertebrates (such as sea cucumbers), and fish at different trophic levels (such as omnivorous fish and carnivorous fish), with each species as an independent homogeneous unit.

[0101] It should be noted that in the above model, the Z-values ​​and D-values ​​for the atmospheric unit, seawater unit, and sediment unit are performed according to existing techniques; for example...

[0102] For abiotic environmental media, the Z-value calculation follows the Mackay fugacity theory (Mackay, 2001):

[0103] The atmospheric Z-value is calculated based on the ideal gas law, taking into account the distribution of the gas phase and the aerosol phase;

[0104] Atmospheric environmental phase: gas phase Aerosol phase General atmospheric phase ;

[0105] The Z-value of seawater is calculated based on Henry's law, taking into account the distribution of dissolved phase and suspended particulate phase;

[0106] Aquatic environment phase: Aquatic phase Suspended particulate phase Total phase of water ;

[0107] The Z-value of sediments is calculated based on the solid-liquid partition coefficient;

[0108] Sedimentary environmental phase: Sedimentary solid phase ; General facies of sediments ;

[0109] Formula for calculating D value:

[0110] Environmental migration processes include atmospheric dry / wet deposition (DDD, DWD), rainwater dissolution (DRD), air-water diffusion (DV), water-sediment diffusion (DWSY), deposition (DWSD), resuspension (DWSR), and burial (DBUR); the specific calculation process is as follows:

[0111] ;

[0112] ;

[0113] ;

[0114] ;

[0115] ;

[0116] ;

[0117] ;

[0118] .

[0119] The second embodiment of this application discloses a modeling method for simulating the marine environmental behavior of target pollutants and food web migration, comprising the following steps:

[0120] S1. Construct a model as described in the first implementation scheme to simulate the marine environmental behavior of target pollutants and their migration through food webs;

[0121] S2. Solve the unsteady mass balance differential equations of the model to obtain the dynamic concentration and migration flux of the target pollutant in each unit and obtain the simulation results;

[0122] S3. Based on the simulation results, quantify the contribution of aquaculture activity input sources to the accumulation of target pollutants in the environment and food web.

[0123] In this embodiment, an ordinary differential equation solver (such as an ODE Solver) can be used to solve the unsteady mass balance differential equations of the model to obtain the unsteady concentration of pollutants in each unit and the migration flux between each process, thereby quantifying the contribution of aquaculture activity inputs to the accumulation of target pollutants in the environment and food web.

[0124] In a further implementation, the contribution of aquaculture input sources to the accumulation of target pollutants in the environment and food web is quantified.

[0125] Furthermore, the contribution rate is achieved through a scenario comparison method, specifically: running a first scenario of the model that includes all input source terms, and running a second scenario of the model that does not include the aquaculture activity input source terms (i.e., does not include the aquaculture feed loss term added in the mass balance equation of the seawater unit, and the aquaculture fish feces term added in the sediment unit). The contribution rate of aquaculture activities is calculated by comparing the simulation results of the two scenarios.

[0126] The technical solution and the technical effects achieved by this application will be described in detail below through specific embodiments.

[0127] Example 1: Simulation of the migration and fate of PCB-153 salmon in the Marlborough Sounds salmon farming area, New Zealand

[0128] like Figure 1 As shown, the migration behavior of the target pollutant PCB-153 in the marine environment and food web is illustrated, revealing the migration, transformation, and fate of this pollutant among the atmospheric (AIR) unit, the water (WATER) unit, the sediment (SEDIMENT) unit, and the BIOTA (biological) unit, represented by salmon.

[0129] For atmospheric units: pollutants enter the system through advective inflow and leave through advective outflow. During this process, they enter water bodies through processes such as dry and wet deposition and rainwater dissolution, and return to the air through water-air diffusion.

[0130] For seawater units: pollutants can degrade, deposit, and diffuse, and can also return to the water due to resuspension of sediments. The input comes not only from the air, but also from the direct input of aquaculture activities (manifested as aquaculture feed input) when aquaculture activities are present.

[0131] For sedimentary units, pollutants in the water body are deposited and degraded here, and can also be resuspended back into the water layer. In addition to pollutants from the water, inputs also come from direct inputs from aquaculture activities (manifested as fish manure inputs) when aquaculture is present.

[0132] For biological units, this manifests as multi-trophic-level units. For example, marine fish at trophic levels 2-4 ingest pollutants through: direct absorption from the water via gills or acquisition from the food chain through feeding. Excretion / loss occurs through gill release, metabolism, and excretion, returning substances to the environment. For high-trophic-level wild fish, in addition to autonomous feeding through the food chain, intake also includes consuming escaped farmed feed when aquaculture is present. Inter-organism transfer occurs through the inflow of pollutants between different organisms, and also through the death and metabolism of organisms, entering the water column or sediment.

[0133] Based on the above cyclic process, a model was constructed to simulate the marine environmental behavior and food web migration of PCB-153.

[0134] Step S1: Build a model parameter database by collecting and establishing the basic parameter set that drives the model's operation.

[0135] In this embodiment, Marlborough Sounds in New Zealand was selected as the study area, and PCB-153 was set as the target pollutant. Based on field monitoring data and literature, the following set of basic parameters was constructed:

[0136] S1.1 Environmental Parameters: Set the seawater area of ​​the simulation region (local mode) ( )for Seawater depth ( The length is 20m.

[0137] Set atmospheric altitude ( The area is 1000m, and the atmospheric area is the same as the sea surface area.

[0138] Set sediment depth ( The sediment depth was 0.1 m, and the organic carbon mass fraction (r) was 0.04.

[0139] Ambient temperature ( The wind speed data used were the daily average data measured in the region from 2008 to 2018.

[0140] S1.2 Physicochemical properties of pollutants (PCB-153):

[0141] Molar mass: 357.84 g / mol.

[0142] The n-octanol-water partition coefficient at 25°C ( ): 7.75.

[0143] Gas-water partition coefficient at 25°C ( ): -3.03.

[0144] Octyl alcohol-gas partition coefficient at 25°C ( ): 9.73.

[0145] Half-life: 1570 days in the atmosphere, 4320 days in water, and 38900 days in sediment.

[0146] S1.3 Parameters of organisms and food webs:

[0147] A food web was constructed containing seven typical species: plankton, sea cucumber, and five fish species (butterfish, marblefish, scarlet wrasse, spotty, and blue cod).

[0148] Physiological parameters of various species: for example, the average weight of the apex predator blue cod ( The weight is set at 1.5 kg, and the lipid content is ( The value is 0.2.

[0149] Dietary preference matrix ( The recipe for blue cod includes 30% plankton, 20% butterfish, 20% marblefish, 20% scarlet wrasse, and 5% spotty.

[0150] Aquaculture activity input parameters: Set the maximum concentration of PCB-153 in salmon feed to 0.61 ng / g (wet weight). Set organic waste generated by the aquaculture system (uneaten feed and fish feces) to be directly discharged into the water and sediment units.

[0151] Step S2, Model Building:

[0152] S2.1 This embodiment constructs a local model based on a single aquaculture farm and its surrounding sea area as the research unit.

[0153] S2.2 divides the study area into three abiotic units: atmosphere (gas phase + aerosols), seawater (water phase + suspended particles), and sediment (solid phase + pore water), as well as a biotic unit composed of the aforementioned seven types of organisms. Specifically, within the sediment unit, through... The parameters are related to the exchange of substances between benthic organisms such as sea cucumbers and pore water in sediments.

[0154] Step S3: Establish a calculation model for fugacity capacity (Z value) and transmission coefficient (D value). The following formulas are programmed using a programming platform:

[0155] Substitute the parameters from step S1 into the Z-value and D-value formulas described in this invention.

[0156] Using temperature correction Calculate the Z-value of each phase of each organism ( For example, consider the different adsorption capacities of lipids (0.2) and proteins (0.17) in blue cod for pollutants.

[0157] Establish a system of unsteady differential equations, where:

[0158] Seawater layer inputs include: direct inputs from feed loss ( ).

[0159] Sediment layer inputs include: direct inputs from the settling of farmed fish excrement ( This flux is calculated from stocking density and excretion rate.

[0160] The biolayer equation covers the processes of breathing from water, breathing from sediment (for sea cucumbers), and feeding on natural prey and aquaculture waste (for specific opportunistic predators).

[0161] Step S4: Model Simulation and Result Analysis

[0162] The simulation model was run to simulate the dynamic migration flux (g / day) of PCB-153 in various media. The simulation results show:

[0163] The contribution of aquaculture activities to sediments:

[0164] Simulation results show that the flux of PCB-153 from salmon feces (containing a small amount of waste feed) settling into the sediment is as high as g / d is the main source of this pollutant in sediments.

[0165] The contribution of aquaculture to food webs:

[0166] The flux of waste feed directly consumed by wildlife is g / d. Specifically, blue cod obtain 90% of their total PCB-153 intake through consuming waste feed.

[0167] Conclusion: The simulation clearly reveals that aquaculture waste (feces and feed) is a key factor driving the accumulation of PCB-153 in benthic organisms and high-trophic-level fish within the aquaculture area, verifying the effectiveness of this model in quantifying the contribution of aquaculture pollution.

[0168] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A model for simulating the marine environmental behavior of target pollutants and their migration through food webs, characterized by being an improved fugacity model based on fugacity theory. include: Coupled atmospheric units, seawater units, sediment units, and multitrophic biological units are interconnected through a set of unsteady mass balance differential equations. The differential equation set of the multi-trophic-level biological unit includes a mass balance equation established for the i-th organism in each biological unit; wherein... Pollutant capacity is measured by bioenergetics-based fugacity capacity. Characterization, its calculation formula simultaneously considers the differential distribution of lipids, proteins and water in the organism; Pollutant intake includes gill respiration intake, dietary intake, and predatory intake, which are expressed via gill respiration intake transfer coefficients. Dietary intake and predator intake transfer coefficients Characterization; Furthermore, in the mass balance equation of the multitrophic level biological unit, the dietary intake term defines the feeding of wild fish at high trophic levels on escaped farmed feed, which is used to characterize the indirect effects of aquaculture activities through the food web; The mass balance equation of the seawater unit includes an ocean current input term and a feed loss term used to characterize the impact of aquaculture activities. The mass balance equation of the sediment unit includes a term for feed loss and a term for fish manure loss, which characterize the impact of aquaculture activities. The target pollutants include at least one of perfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs), and pesticides.

2. The model according to claim 1, characterized in that, Fugacity capacity The calculation formula is: ； in, Represents the total Z-value of the i-th biophase. This represents the lipid content in the intestine of the i-th organism. This represents the protein content in the intestine of the i-th organism. The expression for the proportionality constant of non-lipid organic matter relative to the adsorption capacity of octanol, with a value of 0.035; The Z-value represents the aqueous phase in a water unit, and the calculation formula is: In the formula, This represents the Z-value in the gas phase of the air unit; The Z-value, representing biological organic matter, is calculated using the following formula: In the formula, Indicates the octanol-water partition coefficient. This represents the gas-water distribution coefficient.

3. The model according to claim 1, characterized in that, The formula for calculating the transport coefficient of the pollutant intake item is as follows: ； in, Indicates the gill uptake rate, This represents the population size of the i-th organism. The Z-value represents the overall value of the water body unit. ； in, This represents the D value of the i-th organism through its feeding pathway. , This indicates the absorption efficiency of chemical substances in food; This represents the food intake rate of the i-th organism; The average weight of the i-th organism is expressed in kg. This represents the predation rate of organism i in preying on organism j in the food web; Let Z represent the total phase Z value of prey j as the i-th type of organism.

4. The model according to claim 1, characterized in that, In the system of differential equations for the multitrophic level biological unit, the mass balance equation for the i-th organism is: ； in, Represents the rate of change of the mass of the target pollutant in the i-th organism over time; It accounts for 97% of the feed for livestock; Representative: The intake of the i-th organism from water and sediment via gill respiration, where XW is the proportion of respiration from water and XS is the proportion of respiration from sediment; Let D represent the net predation intake and excretion of the i-th (i≠j) organism in the food web, where D Ei The D value represents the loss of feces and includes the contribution of feeding to escaped feed. This represents the mass loss of the i-th organism due to metabolism, gill excretion, natural death, and predation; among which, The D value represents metabolic loss; The D value represents the amount of water released into the gills; The D value represents natural death; The D value represents the loss due to predation.

5. The model according to claim 1, characterized in that, The model can support the construction of two spatial scales, including a local spatial scale model for simulating a single aquaculture farm and its surrounding sea area, and a regional spatial scale model for simulating multiple aquaculture farms or the entire sea area.

6. A method for simulating the marine environmental behavior and food web migration of a target pollutant, characterized in that, Includes the following steps: S1. Construct a model as described in any one of claims 1-5 to simulate the marine environmental behavior of target pollutants and food web migration; S2. Solve the unsteady mass balance differential equations of the model to obtain the dynamic concentration and migration flux of the target pollutant in each unit and obtain the simulation results; S3. Based on the simulation results, quantify the contribution of aquaculture activity input sources to the accumulation of target pollutants in the environment and food web.

7. The method according to claim 6, characterized in that, The step of quantifying the contribution rate is implemented through a scenario comparison method, specifically including: A scenario with aquaculture is defined as one that includes the sum of ocean current input and aquaculture feed loss in the seawater unit, and the sum of aquaculture feed loss and farmed fish feces in the sediment unit; a scenario without aquaculture is one that does not include aquaculture feed loss in the seawater unit, retains only ocean current input, does not include aquaculture feed loss and farmed fish feces in the sediment unit, and does not include feeding on escaped aquaculture feed in the biological unit. The difference between the simulation results obtained by running the models with and without aquaculture scenarios is used to calculate the contribution rate of aquaculture activities.

8. A system for simulating the marine environmental behavior of pollutants and food web migration, characterized in that, It includes a processor and a memory, the memory storing a computer program, and when the processor executes the program, it is used to construct and solve a model of the simulated marine environmental behavior of the target pollutant and the migration of the food web as described in any one of claims 1-5, and to perform the steps of the method described in claim 6 or 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of claim 6 or 7.

10. A method for pollution source apportionment and risk assessment, characterized in that, The model simulating the marine environmental behavior and food web migration of the target pollutant according to any one of claims 1-5 is used to quantitatively calculate the contribution rate of aquaculture by running comparative scenarios with and without aquaculture activity input sources; and / or assess the health risks of food consumption based on the bioaccumulation level of pollutants in organisms output by the model output; wherein the target pollutant includes PFAS compounds.

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