Multi-layer synchronous micro-plastic observation system and method based on ocean frontal surface tracking

Abstract

The invention discloses a multi-layer synchronous micro-plastic observation system and method based on ocean frontal surface tracking. The system comprises a frontal surface tracking ship and a frontal surface crossing observation ship; a Manta trawl net and a sampling pump are installed in the sampling device; an ADCP and a CTD are installed in the latter. The method comprises the following steps: selecting one or more legs on a frontal surface; carrying out micro-plastic tracking navigation along the frontal surface direction of the frontal surface tracking ship; collecting micro-plastic particles on a surface layer and a vertical section; carrying out cross-frontal surface navigation perpendicular to the frontal surface direction of the cross-frontal surface observation ship; calculating a salinity horizontal gradient based on interpolation, calculating horizontal flow velocity divergence, and then performing observation data fitting to obtain a corresponding relation between frontal surface strength and micro-plastic abundance. According to the invention, key data are synchronously acquired through a double-working ship system, so that the acquisition of micro-plastics at the ocean frontal surface and the observation of physical elements are realized, and the influence and action relationship of the physical elements of the ocean frontal surface on the micro-plastics is established.

Description

Technical Field

[0001] This invention relates to a sampling method for marine microplastic pollution, and more particularly to a multi-layer synchronous microplastic observation system and method based on ocean front tracking, belonging to the field of marine observation technology. Background Technology

[0002] Marine microplastics (plastic particles with a diameter of <5 mm) have become a global environmental pollutant, originating from sources including the degradation of plastic waste, wastewater discharge from washing facilities, and industrial raw material leaks. Studies indicate that the global stock of microplastics in the oceans exceeds one million tons, with hundreds of thousands of tons added annually. These particles can enter the food chain through biological ingestion, adsorbing and transferring toxic substances (such as heavy metals and persistent organic pollutants), ultimately threatening marine ecological security and human health. Therefore, the extreme severity of marine microplastic pollution and the high demand for monitoring necessitate precise quantification of the spatiotemporal distribution patterns of microplastics, especially their transport and accumulation mechanisms in key marine dynamic zones, as a scientific basis for assessing pollution risks and developing remediation strategies.

[0003] Despite the continuous development of microplastic monitoring technology, existing microplastic sampling techniques still have limitations, especially traditional sampling methods which have significant shortcomings in revealing the vertical distribution of microplastics in water bodies and their response to ocean dynamic processes: 1. Limitations of Surface Sampling: While traditional trawl sampling is a common industry practice, it only collects water samples from the surface layer, approximately 0.3 meters deep, failing to reflect the distribution characteristics of microplastics in the vertical profile of the water body. In fact, large amounts of microplastics accumulate in subsurface areas such as the ocean thermocline, and under the influence of turbulence and sedimentation, microplastics can be distributed to depths of hundreds of meters. Relying solely on surface data will severely underestimate the pollution load.

[0004] 2. Asynchronous and Inefficient Depth Sampling: While shipborne pumps or layered nylon nets can collect samples at specific depths, a single operation can only target one or a few preset depths. To obtain a complete profile, the equipment needs to be lowered repeatedly, taking up to several hours. In dynamic areas such as ocean fronts, the water mass structure may change significantly under the influence of tides and runoff, leading to a spatiotemporal mismatch between samples at different depths, making it impossible to capture the instantaneous aggregation effect of microplastics in the vertical water layer. Layered sampling based on CTD water samplers can simultaneously acquire water samples and temperature and salinity data, but its core design is based on the measurement of water chemical parameters: low microplastic sampling efficiency: a single trigger only acquires a limited volume (usually 2-10 L), far lower than pump sampling (hundred liters to cubic meters), making it difficult to capture representative samples from low-concentration areas; lack of anti-contamination design: the opening and closing mechanism easily introduces wear debris from plastic parts, and the lack of a dedicated filtration unit requires additional water sample transfer, increasing the risk of microplastic loss or contamination; limited coverage: high-resolution sampling of large-scale frontal areas requires extremely high-frequency operations, making it impractical.

[0005] Furthermore, existing technologies have limitations in understanding the microplastic aggregation effects of ocean fronts. Ocean fronts are the boundaries between different water masses, characterized by narrow regions where horizontal temperature, salinity, or density gradients increase sharply. Fronts significantly drive the horizontal transport and vertical redistribution of nutrients, plankton, and pollutants by generating vertical circulation and turbulent mixing. Existing research shows that fronts can induce microplastic accumulation at hydrometeors, with concentrations several times higher than background levels. However, traditional microplastic sampling methods often rely on fixed cross-sections or gridded sampling, which cannot accurately track frontal migration paths and are insufficient to analyze the aggregation structures formed by microplastics driven by fronts.

[0006] In summary, existing technologies cannot solve the core problem of "how to simultaneously and efficiently acquire multi-depth microplastic samples and corresponding physical environmental parameters in marine frontal zones" through sampling "along the front" and "across the front," severely limiting our understanding of the front-regulated mechanisms of microplastic transport and accumulation. Therefore, there is an urgent need to develop an integrated microplastic monitoring method that supports multi-level simultaneous sampling in frontal environments. Summary of the Invention

[0007] The technical problem to be solved by this application is to overcome the shortcomings of existing marine microplastic sampling technologies in terms of sampling depth, synchronization and frontal targeting, and to provide a multi-layer synchronous microplastic observation system and method based on marine front tracking, which can accurately target the structure of marine fronts, achieve multi-layer depth synchronous sampling, and effectively distinguish the influence of the presence and intensity of fronts on the distribution of microplastics.

[0008] Specifically, the following issues need to be addressed: First, overcome the limitations of traditional sampling equipment in obtaining vertical profile data of microplastic distribution in water bodies, and achieve multi-layer synchronous sampling from the surface to the near bottom layer; second, address the problem that existing technologies cannot complete multi-depth sampling at the same time and space point, making it difficult to capture rapid changes in microplastics in frontal regions; third, change the current situation where existing methods lack systematic frontal region sampling design, and reveal the impact mechanism of fronts on the transport, accumulation, and distribution of microplastics through comparative sampling "along the front" and "across the front," providing more comprehensive and accurate support for the monitoring, assessment, and control of marine microplastic pollution.

[0009] A multi-layer synchronous microplastic observation system based on ocean front tracking is characterized by including a front-tracking vessel and a cross-front observation vessel. The frontal observation vessel navigates along the frontal trend to track microplastics and collect surface and vertical profiles of microplastic particles. A Manta trawl net is installed at the stern, with the net opening aligned with the navigation direction, to collect surface microplastics. It is also equipped with a mechanical flow meter to calculate the volume of water passing through the trawl net. A retractable sampling rod is mounted on the side of the vessel, covering a vertical profile from the subsurface to near-bottom. Sampling pumps are installed at equal intervals on the rod. Each sampling pump outlet is connected to a stainless steel filter unit with a built-in 5μm filter membrane. After extraction, the water sample passes directly through the filter membrane to trap microplastics. The cross-front observation vessel navigates perpendicular to the frontal direction to measure key physical parameters of frontal intensity. It is equipped with ADCP and CTD rods on its side. The ADCP probes are directed vertically downwards to measure the vertical velocity profile of the entire water column and to reflect the frontal dynamics by calculating the vertical velocity divergence. The CTD rods are equipped with CTDs at equal intervals in layers to measure water depth and salinity data in real time and to reflect the physical characteristics of the front by calculating the salinity gradient.

[0010] The Manta trawl net has an opening size of 1m × 0.5m and a mesh size of 333μm.

[0011] The built-in 5μm polycarbonate filter membrane was ultrasonically cleaned three times with ultrapure water for 10 minutes each time in the laboratory, and then sterilely dried for later use.

[0012] A multi-layer synchronous microplastics observation method based on ocean front tracking is characterized by utilizing the aforementioned observation system and including the following steps: (1) Obtain the position of the front; (2) Design of a cooperative route for two workboats: Select one or more segments on the front and choose the order of navigation for each segment; (3) The two workboats started operations simultaneously. For each segment, after the frontal tracking vessel reaches one end of the segment at the front, it sails along the front at a speed of 2 knots. At the same time, the Manta trawl is started for continuous sampling, and all the stratified sampling pumps on the sampling rod are started to collect water samples. Microplastics are intercepted by the filter membrane in the filtration unit, so that the water depth of the trawl net opening is stabilized at 0.2-0.3m. The cross-frontal observation vessel traversed the front along a path perpendicular to the midpoint of the front at a speed of 2 knots, simultaneously initiating ADCP to measure the vertical current velocity profile and CTD to record salinity and depth distribution. (4) Sampling recovery and observation data storage As the frontal tracking vessel departs from the sampling area boundary along the front, the Manta trawl net is retrieved, and the sampling volume V of the Manta trawl net for this segment is calculated. The sampling pump is stopped to avoid invalid collection in non-sampling areas. Microplastic samples trapped in the Manta trawl net are collected and stored in a 4°C refrigerator to prevent sample degradation or contamination. The ADCP, CTD, and turbidimeter of the cross-frontal observation vessel are simultaneously stopped. All filter membrane samples from the frontal observation vessel were transferred to a -20°C freezer (to inhibit microbial degradation); trawl samples were frozen together with the rinse water to avoid direct sunlight. The salinity and depth data from the cross-frontal observation vessel were merged and stored with ADCP data, and the sampling time, location, and route path data were labeled. (5) The two ships worked together to complete the observation of the entire route. The two ships are simultaneously adjusted to the next observation starting point, and steps (3) and (4) are repeated until sampling of all segments is completed; (6) Processing observation data (6.1) Statistical analysis of microplastic abundance in each flight segment; (6.2) Using the salinity S, horizontal current velocity u, v, and corresponding time t and depth z data collected by each cross-frontal observation vessel, construct a time-depth two-dimensional raw data matrix and interpolate in the depth direction; (6.3) Calculate the interpolated salinity level gradient |▽S| collected by each cross-frontal observation vessel; (6.4) Calculate the velocity divergence based on the interpolated ADCP velocity data and latitude and longitude coordinates of each cross-frontal observation vessel; (7) Fitting of observation data The microplastic abundance data obtained in step (6) and various marine physical element data are fitted to obtain the correspondence between frontal intensity and microplastic abundance.

[0013] Before the workboat starts operation synchronously, the mechanical flowmeter of the frontal observation vessel is calibrated with a known volume of water sample to obtain the correction coefficient R before sampling, so as to ensure that the calculation error of the sampling volume calculation formula V=R×Q×A is ≤5%, where V: sampling volume, Q: flowmeter reading difference, and A: mesh area.

[0014] The microplastic abundance of each flight segment is as follows: (1) All samples returned to the laboratory were first dried in a 30 °C oven for 24 h; (2) After cooling to room temperature, the plastic granules are selected and weighed according to industry standards; (3) Record the volume and quantity of microplastic particles for each flight segment; (4) The microplastic abundance of each section is calculated by using the flow meter readings of each section to obtain the sampling volume.

[0015] The construction of the time-depth two-dimensional original observation data matrix is ​​as follows: Using the observed time series as the first dimension (t1, t2, ..., t n The second dimension is the measured depth at each time point (z1, z2, ..., z). m Combined with the salinity S, horizontal flow velocity u, v data collected from the cross-frontal observation vessel, the original data matrices S(t,z), u(t,z), and v(t,z) are formed, where each matrix element represents the salinity and horizontal flow observation value at a certain time and depth.

[0016] The depth direction interpolation involves performing depth direction interpolation on the vertical profile at each time point for discrete depth observation data to generate regular depth data. The steps are as follows: (1) Depth grid setting: Based on the measured maximum depth (e.g., 0-10m), set the interpolated regular depth interval (e.g., 0.5m). (2) Interpolation calculation: For each time point t i The `interp1` function in MATLAB is used to perform vertical interpolation on the original depth salinity (S) and flow velocities (u, v). Taking salinity data as an example: `S_interp(t...` i ,Z) = interp1(z_obs(t i ),S_obs(t i ,z_obs), Z, 'linear'); where, z_obs (t i () represents time t i The measured depth sequence, S_obs(t) i ,z_obs) represents the corresponding measured salinity data. 'linear' indicates linear interpolation to ensure the continuity of vertical salinity data. After interpolation, regular depth grid data S_interp (t,Z), u_interp (t,Z), and v_interp (t,Z) are obtained, which are complete vertical depth profile data corresponding to each time point.

[0017] The calculation is based on the interpolated salinity level profile gradient |▽S|, and the steps are as follows: (1) Distance calculation: For adjacent time points t k and t k+1 The formula for calculating the horizontal distance between two points based on latitude and longitude coordinates is: ΔD k = 111319.5 × cos(lat k ) × |lonk+1 - lon k | × (π / 180) + 111133 × |lat k+1 - lat k | × (π / 180), where 111319.5m is the distance corresponding to 1° longitude (at the equator), 111133m is the distance corresponding to 1° latitude, (π / 180) is the angle-to-radian coefficient, ΔD k The unit is meters; (2) Salinity difference calculation: For each depth z, calculate the salinity difference between adjacent time points: ΔS k (z) = S_interp(t k+1 ,z) - S_interp(t k ,z); (3) Salinity gradient calculation: The salinity gradient is the ratio of the salinity difference to the horizontal distance, and the absolute value is taken as the quantitative index: |▽S|(t k ,z) = |ΔS k (z)| / ΔD k ; Where |▽S| is in units of psu / m, the larger the value, the higher the t. k and t k+1 The more drastic the spatial variation in salinity at that depth within a given time period, the more pronounced the changes. A key characteristic of estuarine fronts is the dramatic spatial variation in salinity between different water masses, forming distinct transition zones. The rate of spatial salinity change directly reflects the intensity of water mass convergence. Therefore, a larger salinity gradient indicates a stronger front.

[0018] The steps for calculating the horizontal velocity divergence |div| based on the interpolated ADCP velocity data and latitude and longitude coordinates are as follows: (1) Calculation of the spatial rate of change of flow velocity: for adjacent time points t k-1 t k t k+1 Calculate the spatial rate of change of the horizontal flow velocities u and v: du_dx(t k ,Z) = [u(t k+1 ,Z) - u(t k-1 ,Z)] / (ΔD k-1 + ΔD k ); dv_dy(t k ,Z) = [v(t k+1 ,Z) - v(t k-1 ,Z)] / (ΔD k-1 + ΔD k); Where, ΔD k-1 For t k-1 With t k Horizontal distance, ΔD k For t k With t k+1 The horizontal distance is calculated in the same way as above; (2) Calculation of velocity divergence: The horizontal velocity divergence is the algebraic sum of the spatial rates of change of the u and v components, and the absolute value is used as a quantitative index: div(t k ,Z) = du_dx(t k ,Z) + dv_dy(t k ,Z); |div|(t k ,Z) = |div(t k ,Z)|; Here, |div| is measured in units of 1 / s. If div > 0, it indicates water flow divergence; if div < 0, it indicates convergence. The absolute value reflects the intensity of convergence and divergence. In frontal regions, due to differences in the movement speed of different water masses, convergence or divergence of water flow is easily formed. Convergence can cause microplastics to accumulate in the frontal region. Therefore, velocity divergence can serve as a core indicator characterizing the dynamic intensity of a front, reflecting the strength of the front's hydrodynamic impact.

[0019] Compared with existing technologies, this invention not only achieves the collection of microplastics and observation of physical elements at ocean fronts, but also establishes the influence and relationship between ocean front physical elements and microplastics. Through a dual-workboat system, three types of key data are collected simultaneously: microplastic concentration, physical environmental parameters (temperature, salinity, turbidity, and depth), and dynamic parameters (front intensity calculated via CTD vertical gradient and ADCP velocity data carried by the unmanned surface vessel). Through the accompanying data integration module, a correlation curve between "front intensity" and "microplastic concentration" can be directly generated, providing direct data support for revealing the mechanism of "front-driven microplastic aggregation."

[0020] The data acquisition and observation process of this invention features multi-layered synchronization, thus improving data timeliness and correlation. Traditional methods require multiple deployments of equipment to collect samples at different depths (e.g., each layer sampling takes 5-10 minutes), while this invention, through an integrated design using multi-layered CTD poles on the workboat covering the surface to near-bottom layers, can simultaneously complete synchronous sampling of the surface, middle, and near-bottom layers. This feature solves the "time difference error" caused by rapid changes in water structure in frontal regions (e.g., the thermocline depth can change by 1-2m within 10 minutes), ensuring that multi-layered microplastic concentration data strictly matches the temperature, salinity, and turbidity parameters at the corresponding depths, providing a reliable data foundation for analyzing vertical distribution patterns.

[0021] The samples obtained by this invention are more representative and exhibit better contamination control. The sampling pump is directly connected to a stainless steel filter unit (avoiding contact between plastic parts and the water sample), and a 5μm pore size polycarbonate filter membrane is used (resistant to seawater corrosion and with no plastic leaching). The water sample is filtered immediately after being extracted by the pump, reducing the contamination risk of the multiple "water sample storage-transfer-filtration" steps in traditional methods.

[0022] The operation of this invention is more feasible and has strong adaptability to different scenarios.

[0023] The equipment is designed with actual marine operating conditions in mind: the multi-layer CTD pole is made of carbon fiber (weight ≤10kg) and can be manually extended and adjusted (tilt angle 0°-60° to adapt to different ship heights); it can be kept vertical by anchoring devices (the weight of the counterweight is calculated according to the water depth, e.g., 5kg counterweight for 10m water depth), and its wind and wave resistance reaches Beaufort scale 4 (wind speed 6-8m / s). It can operate in various frontal environments (temperature front, salinity front, density front) such as nearshore, estuary, and open sea areas. Sampling (workboat + unmanned surface vessel collaboration) can cover an area of ​​5-10km, taking about 1-2 hours, which is 80% more efficient than traditional methods (6-8 hours for the same range). Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the navigation trajectories of two ships in a frontal zone at a river estuary.

[0025] Figure 2 This is a three-dimensional schematic diagram of a multi-layer synchronous microplastic observation system based on ocean front tracking.

[0026] Figure 3 This is a schematic diagram of a Manta trawl net.

[0027] Figure 4 This is a schematic diagram of the CTD (Content Detection and Control) pole for a cross-frontal tracking vessel.

[0028] Figure 5 A schematic diagram of the equipment configuration for a frontal observation vessel.

[0029] Figure 6 The graph shows the correlation between microplastic abundance and frontal intensity parameters (salinity gradient and divergence).

[0030] in, Figures 1 to 6 The correspondence between the reference numerals and the components is as follows: 1. Frontal tracking vessel; 2. Cross-frontal observation vessel; 3. Manta trawl net, 301 is a lightweight hard aluminum float, 302 is a mechanical flow meter, and 303 is a net cover; 4. CTD rod assembly, 401 is a CTD rod, 402 is a telescopic rope, and 403 is a CTD; 5. Sampling rod assembly, 501 is a sampling pump. Detailed Implementation

[0031] This invention provides a system and method for observing marine microplastics, particularly a method for observing microplastics near fronts. A dual-worker collaborative observation platform is employed to correlate the distribution characteristics of microplastics in the frontal region with frontal intensity parameters through synchronous operation. This method can accurately collect microplastic samples at the front and simultaneously measure key indicators such as frontal salinity gradient and vertical current divergence, thereby revealing the driving mechanism of frontal intensity on microplastic aggregation. The observation system includes two collaboratively operating specialized observation vessels and their onboard dedicated equipment, as detailed below.

[0032] I. System Composition (e.g.) Figure 2 (As shown) 1. Tracking boat along the front It tracks and navigates along the frontal plane, primarily used to collect surface and vertical profiles of microplastic particles, providing sample support for the analysis of microplastic distribution characteristics. Its core configuration includes: Manta trawling: such as Figure 3 As shown, the netting, installed at the stern with its opening facing the same direction as the navigation, is used to collect microplastics from the ocean surface (approximately 30cm deep). It includes a lightweight rigid aluminum float 301, a net 303, and is equipped with a mechanical flow meter 302. The volume of the sampled water is accurately calculated using the calibration formula (V=R×Q×A, where V is the sampling volume, R is the calibration coefficient, Q is the flow meter reading, and A is the net opening area).

[0033] Sampling rod: such as Figure 5 As shown, a telescopic carbon fiber rod is fixed to the side of the ship, with stratified sampling pumps 501 installed at even intervals on the rod, covering a vertical profile from the subsurface to near the bottom. The sampling rod, sampling pumps 501, and related accessories constitute the sampling rod assembly 5. Each sampling pump 501 outlet is connected to a stainless steel filter unit (with a built-in 5μm filter membrane). After extraction, the water sample is directly passed through the filter membrane to trap microplastics. After sampling, the filter membrane is aseptically removed and marked with information such as depth, location, and volume, and then refrigerated for laboratory analysis (extraction, identification, and counting).

[0034] 2. Cross-frontal observation vessel It navigates across fronts perpendicular to their direction, primarily for measuring key physical parameters of frontal intensity, providing data support for quantifying frontal intensity. Its core configuration includes: ADCP (Acoustic Doppler Current Profiler): Installed on the side of the ship, with the detection direction vertically downward, it is used to measure the vertical velocity profile of the entire water column and reflect the dynamic characteristics of the front by calculating the vertical velocity divergence.

[0035] CTD pole 401: such as Figure 4 As shown, consistent with sampling rod 5, it is fixed to the side of the ship. CTD403 (temperature, salinity, and depth sensors) are evenly spaced on the rod. A turbidity meter can also be added to measure the salinity, temperature, and turbidity distribution of the water in real time, and the physical characteristics of the front are reflected by calculating the salinity gradient. A telescopic rope 402 for adjusting the angle is provided at the end of the rod. The CTD rod 401, telescopic rope 402, and CTD403 constitute the CTD rod assembly.

[0036] Frontal intensity quantification: Salinity horizontal gradient (|▽S|) and velocity divergence (|div|) are used as the core indicators to characterize frontal intensity.

[0037] II. A multi-layer synchronous microplastics observation system and method based on ocean front tracking, as detailed below: S1. Preliminary Preparation Stage 1.1 Methods for obtaining the position of the front Existing technologies can be used to acquire sea color and sea surface temperature (SST) data for the target sea area by accessing and downloading satellite remote sensing data and images (such as Sentinel-3 ocean color satellite and HY-1C China Ocean Color Satellite). This data can be combined with historical frontal data for the target sea area (including frequency, location, migration range, and type) and high-precision weather forecasts (covering wind speed, wind direction, waves, and precipitation) to achieve accurate frontal location. It is crucial to ensure that wind speeds are below 8 m / s and there is no severe weather during the sampling window. The specific dates suitable for dual-ship collaborative sampling and the specific location of the frontal core area should be determined as the core coverage area for dual-ship observation.

[0038] 1.2 Design of a cooperative route for two workboats Select one or more segments on the frontal surface. The segment length is selected according to the actual situation, such as 1km. Select the order of navigation for each segment.

[0039] The observation vessel's route along the front: A continuous tracking path is designed along the direction parallel to the front, such as... Figure 1 As shown by the red line, the route length is approximately 1km, and the speed is 2 knots. Cross-front observation vessel route: Design a cross-sectional path perpendicular to the frontal trend, such as... Figure 1As shown by the blue line, the width is 1km (sufficient to cover the width of the front), and the speed is 2 knots; The two ships are set to start synchronously (with an error of ≤1 minute).

[0040] 1.3 The specific equipment is as follows: 1.3.1 Frontal observation vessel (sails along the frontal surface to collect microplastics) Manta planktonic trawl: Net opening size 1m × 0.5m, mesh size 333μm, fixed to the stern of the vessel. Equipped with a mechanical flow meter, a correction factor R (e.g., R = 0.16) must be obtained by calibrating with a known volume of water sample before sampling to ensure that the calculation error of the sampling volume calculation formula V = R × Q × A (V: sampling volume, Q: flow meter reading, A: net opening area) is ≤5%.

[0041] Sampling pump array: Select carbon fiber poles with a length sufficient to cover the subsurface to near-bottom depth. For example, in estuary areas, 10m long, 5cm diameter carbon fiber poles can be used, fixed to the side of the boat. Ten stratified sampling pumps (stainless steel pump heads, silicone pump tubing) are evenly installed on the poles at 1m intervals. Each pump outlet is connected to a 316 stainless steel filter cup (with a built-in 5μm polycarbonate membrane; the membrane must be ultrasonically cleaned three times with ultrapure water for 10 minutes each time in the laboratory, and then sterilely dried for later use).

[0042] 1.3.2 Cross-frontal observation vessel (crossing frontal routes to measure frontal intensity) ADCP (Acoustic Doppler Current Profiler, Model: Signature500): Installed on the side of the ship (≥1m from the hull to avoid turbulence interference), with the detection direction vertically downward, it is used to measure the vertical velocity profile of the entire water column.

[0043] Sensor array: A 10m carbon fiber rod of the same model is fixed to the side of the ship. CTD (temperature, salinity, depth meter, model: RBR concerto) and turbidity meter (MRS Scientific) are evenly attached to the rod at 1m intervals to measure the temperature, salinity, depth and turbidity of the vertical profile of the water body.

[0044] S2, Dual Ship Arrival and Equipment Deployment Calibration The two workboats arrived at the reference point simultaneously and completed the equipment installation and calibration respectively: Equipment preparation for frontal tracking vessels Manta trawling deployment: Secure the trawl net at the stern using a special fixing device, adjust the rope length to 15m, and control the water depth at the net opening to 0.2-0.3m; calibrate the flow meter on-site using a standard volume water sample and record the correction coefficient R.

[0045] Sampling pump deployment: A carbon fiber telescopic rod is fixed to the side of the ship, ensuring a secure installation and smooth extension. After extending the rod to a horizontal position, it is slowly lowered into the water using an electric winch. After submersion, the system is allowed to stand for 5 minutes, and the CTD salinity corresponding to each depth of the sampling pump is monitored using the data acquisition system. No significant fluctuations are observed (fluctuation ≤ 0.01 psu), ensuring sensor stability. The sampling pump is then started, and the pumping-filtration process is tested (no blockages or leaks), confirming a proper connection between the filter membrane and the storage bottle.

[0046] Equipment preparation for cross-frontal observation vessel ADCP Installation: Fix the ADCP on the side of the ship, ensuring the detection direction is vertically downward to avoid interference from the ship hull; preheat for 10 minutes and test the stability of flow rate data acquisition.

[0047] Sensor deployment: A carbon fiber telescopic rod is fixed to the side of the ship, and a CTD and a turbidity meter are attached at 1m intervals (the turbidity meter is attached to the CTD); the rod is slowly lowered into the water (the process is the same as that of the front observation ship). After being submerged, the rod is left to stand for 5 minutes. The CTD salinity and turbidity meter readings are monitored to ensure that there are no significant fluctuations (CTD salinity fluctuation ≤ 0.01 psu), thus ensuring that the sensor is working properly.

[0048] S3, both ships begin observation simultaneously. The two work vessels started operations simultaneously according to the preset time, with the frontal front as the core work area. The frontal observation vessel conducted continuous sampling along the frontal front, while the gradient observation vessel simultaneously carried out cross-frontal observations. The specific process is as follows: 3.1 Start-up Phase 3.1.1 Frontal tracking vessel: Upon reaching the boundary of the sampling area at the front, the vessel will sail at a speed of 2 knots along the predetermined trajectory, immediately activate the Manta trawler for continuous sampling, and simultaneously record the initial reading Q1 of the mechanical flow meter as the starting data for calculating the sampling volume of this section.

[0049] All stratified sampling pumps on the sampling rod are started simultaneously to collect water samples, which are then filtered through a 316 stainless steel filter cup (with a built-in 5μm polycarbonate filter membrane) to remove microplastics.

[0050] After startup, monitor the equipment's operating status in real time to ensure that the water inlet depth of the trawl net is stable at 0.2-0.3m, the sampling pump's water pumping-filtration process is smooth and unblocked, and the CTD salinity fluctuation is ≤0.01psu.

[0051] 3.1.2 Cross-frontal observation vessel: Simultaneously activate ADCP to measure vertical velocity profile, activate CTD and turbidity meter on telescopic mast to record salinity and turbidity distribution, and set sail along a route perpendicular to the frontal direction, with speed also controlled at 2 knots.

[0052] 3.2 Voyage Sampling Phase 3.2.1 Frontal tracking boat Navigating at 2 knots along the frontal trend within the frontal zone, the ship uses real-time depth data obtained from the onboard depth sounder to monitor the angle and depth changes of the boom in real time. If the boom is about to touch the bottom, the angle is adjusted to shorten it, preventing damage to the equipment or data distortion. The position of the trawl net and the status of the sampling pump are also monitored in real time.

[0053] 3.2.2 Cross-frontal observation vessel The flow path continuously traverses the frontal region along the vertical frontal direction. The ADCP outputs vertical velocity data in real time, while the CTD and turbidity meter continuously record changes in salinity and turbidity.

[0054] 3.3 Leaving the sampling area 3.3.1 Frontal observation vessel As the vessel approaches the boundary of the sampling area at the front, the Manta trawl net is retrieved, and the flow meter's final reading Q2 is recorded. The cumulative reading is calculated using the formula Q = Q2 - Q1, and then the trawl net sampling volume V for this segment is accurately calculated using V = R × Q × A (where R is the correction coefficient, such as 0.16; A is the net opening area).

[0055] Stop the sampling pump on the telescopic pole to avoid invalid sampling in non-sampling areas.

[0056] 3.3.2 Cross-frontal observation vessel Simultaneously stop ADCP, CTD and turbidimeter.

[0057] 3.4 After completing sampling at the frontal zone 3.4.1 Equipment recovery and cleaning along the frontal tracking vessel Slowly retrieve the sampling rod and manta trawl net to the deck, avoiding equipment collisions during retrieval. Check the trawl net for damage and ensure the sampling rod connection is secure, recording the equipment status. Carefully collect the microplastic samples trapped in the manta trawl net and place them in pre-numbered 140-mesh 106µm nylon nets, ensuring each sample corresponds to the sampling area and time. Store the sample vials containing the microplastic samples in a 4°C refrigerator to prevent degradation or contamination. Thoroughly rinse the manta trawl net and collection cup with sufficient purified water at least three times, with each rinse using at least 500mL of water. Collect the rinse water samples and bring them back in the refrigerator. This rinsing process collects residual microplastics from the trawl net, ensuring net cleanliness and sampling accuracy for sampling in the next area.

[0058] Immediately remove the filter membrane from each filter cup using strictly sterilized sterile forceps. Do not touch the filter membrane surface during the process. Place the membrane into a pre-numbered sterile sample bag, systematically numbered according to sampling station + sampling time + sampling depth. Then quickly transfer the sample bag to a 4°C refrigerator for storage.

[0059] 3.4.2 Data and equipment recovery from cross-frontal observation vessels Export ADCP flow rate data and salinity and turbidity data from the CTD and turbidimeter on the telescopic rod. Recover the ADCP and telescopic rod, rinse the equipment surfaces with fresh water to remove salt, and inspect the sensor probes to ensure they are free of biofouling or physical damage.

[0060] 3.4.3 Dual-ship coordinated preparation for repeated observations When multiple segments are selected, the segments at different locations of the front are repeatedly observed. The two ships are simultaneously adjusted to the next observation starting point (still within the range of the front). The sampling rod and manta trawl are redeployed along the front tracking ship. After deployment, the necessary post-entry checks and tests are carried out again, including sampling pump function tests.

[0061] The cross-front observation vessel synchronously adjusts its course and conducts necessary post-entry checks and tests, including stability tests of the CTD and turbidimeter sensors. Maintaining synchronization with the front observation vessel, the above observation procedure is repeated until the preset number of observations is completed.

[0062] S4: On-site sample and data processing (end of daily assignment) 4.1 Sample Processing All filter membrane samples from the front observation vessel were transferred from a 4°C refrigerator to a -20°C freezer (to inhibit microbial degradation); trawl samples were frozen together with the rinse water to avoid direct sunlight.

[0063] The salinity and turbidity data from the cross-frontal observation vessel were merged and stored with ADCP data, and the sampling time, location, and route path data were labeled.

[0064] 4.2 Data Processing Data from both vessels were imported into a dedicated computer and processed using specialized software (such as MATLAB): data from the frontal observation vessel included surface microplastic sampling volume and vertical sampling volume; data from the gradient observation vessel included basic physical parameters such as salinity, flow velocity, temperature, and turbidity.

[0065] 4.2.1 Microplastic abundance data 1) Drying and weighing: All samples returned to the laboratory were first dried in a 30 °C oven for 24 h; after cooling to room temperature, the dry weight was recorded using a balance with an accuracy of 0.0001 g (accurate to 0.1 mg).

[0066] 2) Selection of plastic granules: Adopting industry standards, use metal tweezers to pick up granules that meet all of the following criteria: ① No visible cells or organic structures; ② No friction noise when picked up; ③ Uniform coloring; ④ Moderate hardness / toughness, not easy to break, and smooth surface; ⑤ Neat edges; ⑥ Fine filaments with smooth surface, uniform thickness, three-dimensional curvature, and no branching.

[0067] 3) Record the volume and quantity of microplastic particles for each flight segment; 4) Calculate the microplastic abundance at a station by obtaining the sampling volume from the flow meter readings of each flight segment.

[0068] 4.2.2 Preprocessing of data across fronts The salinity (S), horizontal velocity components (u, v), and corresponding time (t), depth (z) data collected by the cross-frontal observation vessel were processed to construct a two-dimensional time-depth raw data matrix. Specifically, the first dimension (t1, t2, ..., t...) is used as the observation time series. n The second dimension is the measured depth at each time point (z1, z2, ..., z). m This forms the original data matrices S(t,z), u(t,z), and v(t,z), where each matrix element represents an observation at a certain time and depth. 4.2.3 Using MATLAB for depth interpolation For discrete depth observation data, MATLAB is used to interpolate the depth direction of the vertical profile at each time point to generate regular depth data. The steps are as follows: 1) Depth grid setting: Based on the measured maximum depth (e.g., 0-10m), set the interpolated regular depth interval (e.g., 0.5m).

[0069] 2) Interpolation calculation: For each time point t i The `interp1` function in MATLAB is used to perform vertical interpolation on the original depth salinity (S) and flow velocities (u, v). Taking salinity data as an example: S_interp(t i ,Z) = interp1(z_obs(t i ), S_obs(t i ,z_obs), Z, 'linear'); where, z_obs (t i () represents time t i The measured depth sequence, S_obs (t i,z_obs) represents the corresponding measured salinity data. 'linear' indicates linear interpolation to ensure the continuity of vertical salinity data. After interpolation, regular depth grid data S_interp (t,Z), u_interp (t,Z), and v_interp (t,Z) are obtained, which are complete vertical depth profile data corresponding to each time point.

[0070] 4.2.3 Calculation of Salinity Horizontal Gradient (|▽S|) Based on the salinity gradient from the interpolated salinity vertical profile data, the steps are as follows: 1) Distance calculation: For adjacent time points t k and t k+1 The formula for calculating the horizontal distance between two points based on latitude and longitude coordinates is: ΔD k = 111319.5 × cos(lat k ) × |lon k+1 - lon k | × (π / 180) + 111133 × |lat k+1 - lat k | × (π / 180), where 111319.5m is the distance corresponding to 1° longitude (at the equator), 111133m is the distance corresponding to 1° latitude, (π / 180) is the angle-to-radian coefficient, ΔD k The unit is meters; 2) Salinity difference calculation: For each depth z, calculate the salinity difference between adjacent time points: ΔS k (z) = S_interp(t k+1 ,z) - S_interp(t k ,z); 3) Salinity gradient calculation: The salinity gradient is the ratio of the salinity difference to the horizontal distance, and the absolute value is used as the quantitative indicator: |▽S|(t k ,z) = |ΔS k (z)| / ΔD k ; Where |▽S| is in units of psu / m, a larger value indicates a more dramatic spatial variation in salinity at that depth within that time interval. The core characteristic of estuarine fronts is the dramatic spatial variation in salinity between different water masses, forming distinct transition zones. The rate of spatial variation in salinity directly reflects the intensity of water mass convergence. Therefore, a larger salinity gradient implies a stronger front. 4.2.4 Calculation of velocity divergence (|div|) The horizontal velocity divergence is calculated based on the interpolated ADCP velocity data and latitude and longitude coordinates, following these steps: 1) Calculation of the spatial rate of change of flow velocity: for adjacent time points t k-1 t k t k+1 Calculate the spatial rate of change of the horizontal flow velocities u and v: du_dx(t k ,Z) = [u(t k+1 ,Z) - u(t k-1 ,Z)] / (ΔD k-1 + ΔD k ); dv_dy(t k ,Z) = [v(t k+1 ,Z) - v(t k-1 ,Z)] / (ΔD k-1 + ΔD k ); Where, ΔD k-1 For t k-1 With t k Horizontal distance, ΔD k For t k With t k+1 The horizontal distance is calculated using the same method as step 1 in 4.2.3. 2) Velocity divergence calculation: The horizontal velocity divergence is the algebraic sum of the spatial rates of change of the u and v components, and the absolute value is used as a quantitative indicator. div(t k ,Z) = du_dx(t k ,Z) + dv_dy(t k ,Z); |div|(t k ,Z) = |div(t k ,Z)|; Here, |div| is measured in units of 1 / s. If div > 0, it indicates water flow divergence; if div < 0, it indicates convergence. The absolute value reflects the intensity of convergence and divergence. In frontal regions, due to differences in the movement speed of different water masses, convergence or divergence of water flow is easily formed. Convergence can cause microplastics to accumulate in the frontal region. Therefore, velocity divergence can serve as a core indicator characterizing the dynamic intensity of a front, reflecting the strength of the front's hydrodynamic impact.

[0071] 4.3) Data Fitting: This invention utilizes a frontal observation vessel to collect microplastics at the frontal zone, and then obtains microplastic abundance data through statistical analysis. After processing and calculating the data collected by the cross-frontal observation vessel using the above steps, the marine physical elements of the observation route can be obtained. After integrating these data, the correspondence between frontal intensity and microplastic abundance can be obtained. Furthermore, by using MATLAB for calculation, the fitting relationship between the variables can be obtained.

[0072] like Figure 6 As shown, in one observation, the fitted formula is: Microplastic abundance = 108×|▽S| +1351×div - 2.86.

[0073] S5: Equipment Cleaning and Maintenance All parts that come into contact with the water sample (sampling pump tubing, filter cup, tweezers, and trawl) should be rinsed three times with ultrapure water (≥500mL each time) to remove residual microplastics and salts; the filter membrane support should be wiped with 75% alcohol for disinfection and then air-dried for later use.

[0074] Check equipment status: flow meter calibration accuracy, ADCP flow rate measurement deviation, CTD salinity error (recalibrate to ≤±0.002psu) to ensure that equipment performance meets standards for the next day's operation.

Claims

1. A multi-layer synchronous microplastics observation system based on ocean front tracking, characterized by: This includes frontal tracking vessels and cross-frontal observation vessels; The frontal tracking vessel navigates along the frontal trend to track microplastics and collect surface and vertical profiles of microplastic particles. A manta trawl net is installed at the stern, with the net opening aligned with the navigation direction, to collect surface microplastics. It is also equipped with a mechanical flow meter to calculate the volume of water passing through the trawl net. A retractable sampling rod is mounted on the side of the vessel, covering a vertical profile from the subsurface to near-bottom. Sampling pumps are installed at equal intervals on the rod. Each sampling pump outlet is connected to a stainless steel filter unit with a built-in 5μm filter membrane. After extraction, the water sample passes directly through the filter membrane to trap microplastics. The cross-front observation vessel navigates perpendicular to the frontal direction to measure key physical parameters of frontal intensity. It is equipped with ADCP and CTD rods on its side. The ADCP probes are directed vertically downwards to measure the vertical velocity profile of the entire water column and to reflect the frontal dynamics by calculating the vertical velocity divergence. The CTD rods are equipped with CTDs at equal intervals in layers to measure water depth and salinity data in real time and to reflect the physical characteristics of the front by calculating the salinity gradient.

2. The multi-layer synchronous microplastic observation system based on ocean front tracking as described in claim 1, characterized in that: The Manta trawl net has an opening size of 1m × 0.5m and a mesh size of 333μm.

3. The multi-layer synchronous microplastic observation system based on ocean front tracking as described in claim 1, characterized in that: The built-in 5μm polycarbonate filter membrane was ultrasonically cleaned three times with ultrapure water for 10 minutes each time in the laboratory, and then sterilely dried for later use.

4. A multi-layer synchronous microplastic observation method based on ocean front tracking, characterized by: This method utilizes the system of claim 1 and includes the following steps: (1) Obtain the position of the front; (2) Design of a cooperative route for two workboats: Select one or more segments on the front and choose the order of navigation for each segment; (3) The two workboats started operations simultaneously. For each segment, after the frontal tracking vessel reaches one end of the segment at the front, it sails along the front at a speed of 2 knots. At the same time, the Manta trawl is started for continuous sampling, and all the stratified sampling pumps on the sampling rod are started to collect water samples. Microplastics are intercepted by the filter membrane in the filtration unit, so that the water depth of the trawl net opening is stabilized at 0.2-0.3m. The cross-frontal observation vessel traversed the front along a path perpendicular to the midpoint of the front at a speed of 2 knots, simultaneously initiating ADCP to measure the vertical current velocity profile and CTD to record salinity and depth distribution. (4) Sampling recovery and observation data storage When the frontal tracking vessel leaves the sampling area boundary along the front, the Manta trawl net is retrieved, and the sampling volume V of the Manta trawl net for this segment is calculated; the sampling pump is stopped to avoid invalid collection in non-sampling areas; microplastic samples trapped in the Manta trawl net are collected and stored in a 4°C refrigerator to prevent sample degradation or contamination; the cross-frontal observation vessel simultaneously stops ADCP and CTD. All filter membrane samples from the frontal tracking vessel were transferred to a -20°C freezer; trawl samples were frozen together with the rinse water, avoiding direct sunlight. The salinity and depth data from the cross-frontal observation vessel were merged and stored with ADCP data, and the sampling time, location, and route path data were labeled. (5) The two ships worked together to complete the observation of the entire route. The two ships are simultaneously adjusted to the next observation starting point, and steps (3) and (4) are repeated until sampling of all segments is completed; (6) Processing observation data (6.1) Statistical analysis of microplastic abundance in each flight segment; (6.2) Using the salinity S, horizontal velocity u, v, and corresponding time t and depth z data collected by each cross-frontal observation vessel, a two-dimensional time-depth raw data matrix is ​​constructed, and interpolation is performed in the depth direction; (6.3) Calculate the interpolated salinity level gradient |▽S| collected by each cross-frontal observation vessel; (6.4) Calculate the velocity divergence based on interpolated ADCP velocity data and latitude and longitude coordinates collected by each cross-frontal observation vessel; (7) Fitting of observation data The microplastic abundance data obtained in step (6) and various marine physical element data are fitted to obtain the correspondence between frontal intensity and microplastic abundance.

5. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 4 is characterized in that, before the work vessel starts synchronously, the mechanical flow meter of the front tracking vessel is calibrated with a known volume of water sample to obtain the correction coefficient R before sampling, so as to ensure that the calculation error of the sampling volume calculation formula V=R×Q×A is ≤5%, where V: sampling volume, Q: flow meter reading difference, and A: mesh area.

6. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 4, characterized in that: The microplastic abundance of each flight segment is as follows: (1) All samples returned to the laboratory were first dried in a 30 °C oven for 24 h; (2) After cooling to room temperature, the plastic granules are selected and weighed according to industry standards; (3) Record the volume and quantity of microplastic particles for each flight segment; (4) The microplastic abundance of each segment is calculated by using the flow meter readings of each segment to obtain the sampling volume.

7. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 4, characterized in that: The construction of the time-depth two-dimensional original observation data matrix is ​​as follows: Using the observed time series as the first dimension (t1, t2, ..., t n The second dimension is the measured depth at each time point (z1, z2, ..., z). m Combined with the salinity S, horizontal flow velocity u, v data collected from the cross-frontal observation vessel, the original data matrices S(t,z), u(t,z), and v(t,z) are formed, where each matrix element represents the salinity and horizontal flow observation value at a certain time and depth.

8. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 7, characterized in that: The depth direction interpolation involves performing depth direction interpolation on the vertical profile at each time point for discrete depth observation data to generate regular depth data. The steps are as follows: (1) Depth grid setting: Based on the measured maximum depth, set the interpolated regular depth interval; (2) Interpolation calculation: For each time point t i The `interp1` function in MATLAB is used to perform vertical interpolation on the original depth salinity (S) and flow velocities (u, v). Taking salinity data as an example: `S_interp(t...` i ,Z) = interp1(z_obs(t i ), S_obs(t i ,z_obs), Z, 'linear'); where, z_obs (t i Let S_obs(t) be the measured depth sequence at time tᵢ. i ,z_obs) represents the corresponding measured salinity data. 'linear' indicates linear interpolation to ensure the continuity of vertical salinity data. After interpolation, regular depth grid data S_interp (t,Z), u_interp (t,Z), and v_interp (t,Z) are obtained, which are complete vertical depth profile data corresponding to each time point.

9. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 4, characterized in that: The calculation is based on the interpolated salinity level profile gradient |▽S|, and the steps are as follows: (1) Distance calculation: For adjacent time points t k and t k+1 The formula for calculating the horizontal distance between two points based on latitude and longitude coordinates is: ΔD k = 111319.5 × cos(lat k ) × |lon k+1 - lon k | × (π / 180) + 111133 × |lat k+1 - lat k | × (π / 180), where 111319.5m is the distance corresponding to 1° longitude, 111133m is the distance corresponding to 1° latitude, (π / 180) is the angle-to-radian coefficient, and ΔD k The unit is meters; (2) Salinity difference calculation: For each depth z, calculate the salinity difference between adjacent time points: ΔS k (z) = S_interp(t k+1 ,z) - S_interp(t k ,z); (3) Salinity gradient calculation: The salinity gradient is the ratio of the salinity difference to the horizontal distance, and the absolute value is taken as the quantitative index: |▽S|(t k ,z) = |ΔS k (z)| / ΔD k ; Where |▽S| is in units of psu / m, the larger the value, the higher the t. k and t k+1 The more drastic the spatial variation in salinity at that depth within a given time period, the more pronounced the change.

10. The multi-layer synchronous microplastic observation method based on ocean front tracking as described in claim 9, characterized in that: The steps for calculating the horizontal velocity divergence |div| based on the interpolated ADCP velocity data and latitude and longitude coordinates are as follows: (1) Calculation of the spatial rate of change of flow velocity: for adjacent time points t k-1 t k t k+1 Calculate the spatial rate of change of the horizontal flow velocities u and v: du_dx(t k ,Z) = [u(t k+1 ,Z) - u(t k-1 ,Z)] / (ΔD k-1 + ΔD k ); dv_dy(t k ,Z) = [v(t k+1 ,Z) - v(t k-1 ,Z)] / (ΔD k-1 + ΔD k ); Where, ΔD k-1 t k-1 With t k Horizontal distance, ΔD k t k With t k+1 The horizontal distance is calculated using the same method as in claim 9; (2) Calculation of velocity divergence: The horizontal velocity divergence is the algebraic sum of the spatial rates of change of the u and v components, and the absolute value is used as a quantitative index: div(t k ,Z) = du_dx(t k ,Z) + dv_dy(t k ,Z); |div|(t k ,Z) = |div(t k ,Z)|; The unit of |div| is 1 / s. If div > 0, it indicates water flow divergence; if div < 0, it indicates convergence. The absolute value reflects the intensity of convergence and divergence.

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