Integrated passive sampler and its application in evaluation of aquaculture tail water treatment process

Abstract

The present application relates to the technical field of environmental monitoring, in particular to an integrated passive sampler and its application in process efficiency evaluation of aquaculture tail water treatment. The sampler comprises a sampler main body, a silica gel membrane sampling unit attached to the outer surface thereof, and a thin film diffusion gradient sampling unit installed in an independent sampling chamber in the sampler main body. The silica gel membrane sampling unit is used for enriching non-polar organic pollutants. The thin film diffusion gradient sampling unit is composed of a filter membrane layer, a diffusion layer and an adsorption layer which are stacked in sequence. The adsorption layer is formed by mixing and solidifying porous adsorption resin particles and agarose gel, and is used for enriching polar organic pollutants. The sampler main body is provided with an exposed window covered with a protective net at the position corresponding to the chamber. Based on the sampler, an efficiency evaluation method is also provided. By deploying the sampler at key points of the treatment process, the time-weighted average concentration of pollutants is obtained, and the removal rate of the treatment unit is calculated. The present application realizes the simultaneous in-situ monitoring and quantitative evaluation of the process efficiency of multiple types of organic pollutants in aquaculture tail water.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and more specifically, to an integrated passive sampler and a method for evaluating the efficiency of aquaculture wastewater treatment processes using the integrated passive sampler. Background Technology

[0002] With the intensive and large-scale development of aquaculture, the amount of aquaculture wastewater discharged continues to increase. This wastewater often contains both non-polar organic pollutants such as pyrethroid pesticides and organochlorine pesticides, and polar organic pollutants such as antibiotics and hormones. These pollutants are characterized by their tendency to accumulate and their biotoxicity, posing potential threats to aquatic ecosystems and human health. Therefore, effective monitoring and performance evaluation of aquaculture wastewater treatment processes are crucial to ensuring the stable operation of treatment systems and achieving compliant wastewater discharge.

[0003] Currently, the evaluation of aquaculture wastewater treatment effectiveness mainly relies on active sampling methods, which involve collecting instantaneous water samples at key points such as the influent and effluent of the treatment process, followed by laboratory analysis. However, this method has significant limitations: First, instantaneous sampling cannot reflect the dynamic changes in pollutant concentrations over time, and cannot obtain time-weighted average concentrations representing the entire operating cycle; second, active sampling typically requires large sample volumes, and subsequent pretreatment processes such as solid-phase extraction and purification are complex, time-consuming, and difficult to simultaneously monitor organic pollutants of different polarities.

[0004] In recent years, passive sampling technology has attracted attention due to its advantages such as ease of operation, long-term in-situ deployment, and ability to obtain time-weighted average concentrations. Among these, silica gel membrane passive sampling technology is suitable for the enrichment and monitoring of non-polar organic pollutants, while thin-film diffusion gradient technology is suitable for the enrichment and monitoring of polar organic pollutants. For example, Chinese patent application CN110927023A discloses a passive sampling device based on a low-density polyethylene membrane for the simultaneous detection of multiple non-polar organic pollutants in water; Chinese patent application CN110702802A discloses a thin-film diffusion gradient device using adsorption resin as the adsorption membrane for monitoring antibiotics in water.

[0005] Although the above-mentioned devices have shown some effectiveness in monitoring specific pollutants, the following technical problems still exist when applied to on-site monitoring and performance evaluation of aquaculture wastewater treatment processes:

[0006] First, existing devices are mainly designed for relatively stable water bodies such as lakes and rivers, and do not fully consider the characteristics of aquaculture wastewater treatment processes, such as frequent water flow disturbances, large fluctuations in pollutant concentrations, and complex water composition. For example, the uptake rate of pollutants by passive samplers such as silica gel membranes and thin-film diffusion gradients is controlled by the water-side boundary layer. Drastic fluctuations in flow velocity will cause changes in the sampling rate, directly affecting the accuracy of concentration calculation results.

[0007] Second, existing technologies lack integrated solutions. Due to the significant differences in the physicochemical properties of non-polar and polar organic pollutants, different passive samplers are usually deployed separately. This split deployment method is not only cumbersome to operate, but more importantly, the inconsistent local hydrodynamic microenvironments of the different samplers result in insufficient comparability of monitoring data for the two types of pollutants, failing to provide accurate and reliable data support for evaluating the synergistic effectiveness of treatment processes.

[0008] Third, the internal environment of aquaculture wastewater treatment units is complex, and biofilm formation is common. During long-term operation, treatment units such as biofilters and ecological ponds easily form biofilms on their surfaces due to microorganisms and other suspended solids in the water. Existing passive sampling devices, when deployed long-term, are prone to biofilm buildup on their filter or adsorption membranes, leading to a decrease in diffusion flux and severely impacting sampling stability and data reliability. Furthermore, separately deployed devices face risks of displacement due to water flow impacts or even human-caused damage in outdoor environments.

[0009] In summary, there is an urgent need in the existing technology for an integrated passive sampling device and corresponding standardized evaluation method that can adapt to the complex environment of aquaculture wastewater treatment processes, simultaneously and in situ obtain the time-weighted average concentrations of non-polar and polar organic pollutants, and can be directly used for dynamic evaluation of process efficiency. Summary of the Invention

[0010] This invention aims to address the technical problem that existing passive sampling technologies are ill-suited to the complex environment of aquaculture wastewater treatment processes, failing to simultaneously and accurately obtain the time-weighted average concentrations of non-polar and polar organic pollutants, thus hindering the provision of reliable data support for process performance evaluation. Specifically, the technical problems this invention seeks to solve include: how to achieve simultaneous in-situ enrichment of non-polar and polar organic pollutants within the same device; how to overcome the adverse effects of water flow disturbance and biofouling on the passive sampling rate and accuracy; and how to establish a standardized sampling and analysis calculation method that can be directly used for dynamic evaluation of aquaculture wastewater treatment process performance.

[0011] To achieve the above objectives, the present invention adopts the following technical solution:

[0012] In a first aspect, the present invention provides an integrated passive sampler, comprising:

[0013] A sampler body, wherein the sampler body has at least two independent sampling chambers inside;

[0014] At least one silicone membrane sampling unit is attached to the outer surface of the sampler body for enriching non-polar organic pollutants in the water.

[0015] At least two thin-film diffusion gradient sampling units are respectively and detachably installed in the sampling chamber. Each thin-film diffusion gradient sampling unit includes a filter membrane layer, a diffusion layer, and an adsorption layer that are stacked and tightly attached in sequence. The adsorption layer is formed by mixing and curing porous adsorption resin particles with high specific surface area with agarose gel, and is used to enrich polar organic pollutants in the water. The porous adsorption resin is a resin with high adsorption capacity for polar organic pollutants, such as styrene-divinylbenzene copolymer type macroporous adsorption resin, to ensure effective enrichment of antibiotic and hormone pollutants in the water.

[0016] The sampler body has at least one exposure window at the location corresponding to each of the sampling chambers. The exposure window connects the sampling chamber to the external water body, and the window is covered with a protective net with an aperture of 1-2 mm.

[0017] By integrating the silica gel membrane sampling unit and the thin-film diffusion gradient sampling unit into the same sampler body, non-polar and polar organic pollutants can be simultaneously enriched in a completely uniform local hydrodynamic microenvironment. A protective mesh ensures free water flow while preventing large particles from entering the sampling chamber, thus avoiding physical damage or blockage to the thin-film diffusion gradient sampling unit. Independently designed sampling chambers prevent cross-contamination between different types of sampling units, ensuring the independence of their respective enrichment processes and the accuracy of the analytical results.

[0018] Furthermore, the silicone membrane sampling unit is made of addition-cured silicone material with a thickness of 0.5-2.0 mm, and is detachably attached to the sampler body via a slot-type structure. This thickness range ensures that the silicone membrane has sufficient mechanical strength and is not easily damaged, while providing an appropriate path for pollutant diffusion and avoiding excessively long enrichment equilibrium time due to excessive membrane thickness.

[0019] As a preferred embodiment, in the thin-film diffusion gradient sampling unit: the filter membrane layer is a polyethersulfone filter membrane with a pore size of 0.45 μm and a thickness of 0.14 mm; the diffusion layer is an agarose hydrogel membrane with a thickness of 0.8 mm; and the adsorption layer is a 0.5 mm thick disc formed by mixing porous adsorption resin powder (passed through a 200-mesh sieve) with a 1.5% hot agarose solution at a mass-to-volume ratio of 1 g:10 mL and then solidifying the mixture. By systematically optimizing the thickness, pore size, and material ratio of each layer, it is ensured that pollutants undergo stable mass transfer in the diffusion layer according to Fick's first diffusion law, while simultaneously guaranteeing that the adsorption layer has sufficient adsorption capacity.

[0020] Furthermore, the sampler body is a streamlined, biomimetic fish shape. This streamlined shape effectively reduces water flow resistance and minimizes local turbulence caused by the sampler itself, resulting in a more uniform distribution of the hydrodynamic boundary layer around the sampler. This improves the enrichment rate of the two types of sampling units and the consistency of monitoring data. In addition, a counterweight can be installed inside the sampler body to ensure stable suspension in the water. Simultaneously, the silicone membrane sampling unit is shaped like a biomimetic fish fin or tail and attached to the corresponding position on the sampler body, ensuring sufficient exposure area while further enhancing the biomimetic effect and structural integrity of the sampler.

[0021] As a specific specification of the sampler body material, the sampler body is formed by curing a mixture of liquid silica gel and hydrogen-based siloxane in a 1:1 weight ratio. This addition-cure silica gel material has good chemical stability and biocompatibility, and is not prone to swelling or degradation under long-term immersion in aquaculture wastewater, ensuring the long-term integrity of the sampler structure and the repeatability of sampling.

[0022] Secondly, based on the aforementioned integrated passive sampler, the present invention also provides a method for evaluating the efficiency of aquaculture wastewater treatment processes, comprising the following steps:

[0023] Step 1: Deploy the integrated passive sampler at the inlet, inside at least one treatment unit, and at the outlet of the aquaculture wastewater treatment process;

[0024] Step 2: After continuous deployment for 7-30 days, retrieve the sampler, extract organic solvent from the silica membrane sampling unit to obtain the first test sample containing non-polar organic pollutants; remove the adsorption layer of the thin film diffusion gradient sampling unit and elute it with solvent to obtain the second test sample containing polar organic pollutants.

[0025] Step 3: Based on the analysis results of the first sample to be tested, obtain the mass of the target pollutant in the extract of the silica membrane sampling unit. Then, based on the extract volume and the mass of the silica membrane sampling unit, calculate the concentration of the target pollutant in the silica membrane sampling unit. Combined with the silica membrane-water partition coefficient, calculate the time-weighted average concentration of non-polar organic pollutants in the water. Based on the analysis results of the second sample to be tested, obtain the cumulative amount of the target pollutant on the adsorption layer. Combined with the deployment time, diffusion layer thickness, effective exposure area, and temperature-corrected diffusion coefficient, calculate the time-weighted average concentration of polar organic pollutants in the water using Fick's first diffusion law.

[0026] Step 4: Based on the time-weighted average concentration of the target pollutant measured by samplers deployed upstream and downstream of the same treatment unit, calculate the removal rate R of the target pollutant by the treatment unit. The calculation formula is as follows:

[0027] R = (C in - C out ) / C in × 100%

[0028] Among them, C in C represents the concentration measured by the upstream sampler. out The concentration measured by the downstream sampler.

[0029] This method integrates the deployment, retrieval, sample processing, concentration calculation, and removal rate assessment of integrated passive samplers into a standardized process, achieving full coverage from sampling to performance evaluation. Specifically, the formula for calculating the concentration C of non-polar organic pollutants in water in step three is as follows:

[0030] C = C s / K sw

[0031] Among them, C s K represents the concentration of the target pollutant in the silica membrane sampling unit. sw This is the silica gel membrane-water partition coefficient. Based on the principle of pollutant distribution equilibrium between the silica gel membrane and the aqueous phase, this formula accurately reflects the concentration of non-polar organic pollutants in the water body.

[0032] The silica membrane-water distribution coefficient K sw The acquisition methods include: for known pollutants, refer to K reported in existing literature. sw For pollutants not documented in the literature, the concentration can be determined by a static adsorption equilibrium experiment. The method for this static adsorption equilibrium experiment is as follows: a known mass of silica gel membrane is immersed in an aqueous solution containing a known initial concentration of the target pollutant. The membrane is continuously shaken at a constant temperature until adsorption equilibrium is reached. The concentrations of the pollutant in the aqueous phase and the silica gel membrane phase are then measured separately, according to K...sw = C s / C w Calculate the allocation coefficient, where C s To determine the concentration of contaminants in the silica membrane at equilibrium, C w This represents the concentration of pollutants in the aqueous phase at equilibrium.

[0033] Furthermore, the temperature-corrected diffusion coefficient D used in step three... t Calculated using the following formula:

[0034] D t = D 25 × (T+273) / 298 × η 25 / η T

[0035] Among them, D 25 η is the diffusion coefficient of the target at 25°C, T is the average temperature of the water body during deployment, and η is the diffusion coefficient of the target at 25°C. 25 η is the viscosity of water at 25°C. T Here, T represents the viscosity of water at T℃. This temperature correction takes into account the effect of water viscosity changes with temperature on the diffusion rate of pollutant molecules, ensuring the accuracy of concentration calculations under different seasons or water temperature conditions.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] First, it achieves simultaneous integrated monitoring of multiple pollutants. By integrating a silica membrane sampling unit and a thin-film diffusion gradient sampling unit onto the same sampler body, it is the first time that simultaneous in-situ enrichment of non-polar organic pollutants and polar organic pollutants in aquaculture effluent has been achieved. The two types of sampling units are in completely identical local hydrodynamic environments, fundamentally solving the problem of insufficient data comparability caused by separate deployments, and providing a reliable data foundation for evaluating the synergistic effectiveness of treatment processes.

[0038] Secondly, it significantly improves the representativeness and accuracy of monitoring data. This invention obtains a time-weighted average concentration over the deployment period, which, compared to traditional instantaneous active sampling, more accurately reflects the stable treatment effect of the process throughout its entire operation cycle, effectively avoiding assessment errors caused by instantaneous fluctuations in pollutant concentration. Simultaneously, the synergistic design of the biomimetic fish-like streamlined shape and the exposure window improves the local flow field around the sampler, reducing the impact of water-side boundary layer inhomogeneity on the enrichment rates of different sampling units, further enhancing the accuracy and reproducibility of the monitoring results.

[0039] Third, it enhances adaptability and long-term deployment stability in complex environments. The addition-cure silicone material used in the sampler body possesses excellent chemical stability and mechanical properties. After long-term immersion under typical pH and temperature conditions in aquaculture wastewater, its tensile strength retention rate and mass change rate both meet the requirements for repeated use. The streamlined, biomimetic shape provides a certain degree of water flow compliance and concealment, reducing the risk of water flow impact and human interference. The protective netting installed at the exposed window, along with corresponding regular inspection and cleaning measures, effectively mitigates the impact of biofouling on sampling throughput, ensuring the stability of long-term in-situ monitoring.

[0040] Fourth, it simplifies the operation process and reduces monitoring costs. This invention adopts an integrated design, replacing multiple dispersed samplers with a single device, significantly reducing the workload of on-site deployment and retrieval. The slot-type detachable structure of the sampling unit makes sample retrieval and unit replacement convenient and efficient, and the main body of the sampler is reusable, greatly reducing the manpower and material costs of long-term monitoring.

[0041] Fifth, a standardized methodological system for evaluating process efficiency has been established. This invention constructs a complete closed-loop process from sampler preparation, on-site deployment, sample pretreatment, concentration calculation to removal rate assessment, enabling passive sampling data to be directly and quantitatively applied to the determination of treatment unit efficiency and process optimization. This method is highly operable and easy to promote and apply in different types of aquaculture wastewater treatment projects, providing a scientific basis for precise process control and compliance with discharge standards. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the structure of an integrated passive sampler according to an embodiment of the present invention.

[0043] Among them, 101—dorsal fin silicone membrane sampling unit; 102—anal fin silicone membrane sampling unit; 103—pectoral fin silicone membrane sampling unit; 201—first thin film diffusion gradient sampling unit; 202—second thin film diffusion gradient sampling unit; 301—upper exposure window of the first chamber; 302—upper exposure window of the second chamber; 303—lower exposure window of the second chamber; 304—lower exposure window of the first chamber. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments described herein are for illustrative purposes only and are not intended to limit the scope of protection of this invention.

[0045] Example 1: Fabrication and Assembly of an Integrated Passive Sampler

[0046] This embodiment provides a specific preparation process and assembly method for an integrated passive sampler.

[0047] See Figure 1 The integrated passive sampler of this invention includes a sampler body with a streamlined, biomimetic fish shape. The sampler body is prepared as follows: using a common freshwater fish (such as crucian carp or silver carp) as the biomimetic model, liquid silica gel and hydrogen-based siloxane are mixed evenly in a 1:1 weight ratio. After vacuum degassing for 10 minutes, the mixture is poured into a pre-made fish-shaped mold. The mold has pre-reserved positions for the sampling chamber, exposure window, and silica gel membrane slot. A stainless steel counterweight is built into the fish's head to ensure stable suspension in water after deployment. After curing at room temperature for 24 hours, the sampler is demolded to obtain the streamlined biomimetic fish body. In this embodiment, the biomimetic fish body has a total length of 25 cm and a maximum width of 7 cm.

[0048] The sampler body contains two independent sampling chambers: a first sampling chamber and a second sampling chamber. Each sampling chamber has a diameter of 2.8 cm and a depth of 1.0 cm. On both sides of the sampler body, corresponding to the position of each sampling chamber, at least one exposure window (301, 302, 303, 304) is provided. In this embodiment, an upper exposure window (301) and a lower exposure window (304) are provided in the first sampling chamber, and an upper exposure window (302) and a lower exposure window (303) are provided in the second sampling chamber. Each exposure window measures 2.5 cm × 1.3 cm and is covered with a stainless steel protective mesh with a pore size of 1-2 mm, sealed with silicone to allow access to external water and prevent the entry of large particles.

[0049] The silicone membrane sampling unit is attached to the outer surface of the sampler body. In this embodiment, the silicone membrane sampling unit is made of the same material as the sampler body, namely, an addition-type silicone material made by mixing and curing liquid silicone and hydrogen-based siloxane in a 1:1 weight ratio. During preparation, the pectoral fin, pelvic fin, and tail of a biomimetic fish are used as positive molds. The vacuum-degassed mixed silicone is poured into the corresponding molds, cured at room temperature for 24 hours, and then demolded to obtain a silicone membrane with a thickness of 1.0 mm. This silicone membrane constitutes the dorsal fin silicone membrane sampling unit (101), the anal fin silicone membrane sampling unit (102), and the pectoral fin silicone membrane sampling unit (103), respectively. To remove residual impurities and unreacted monomers on the membrane surface, the prepared silicone membrane is placed in a brown glass bottle and purified by soaking in a mixed solvent composed of ethyl acetate and n-hexane in a 1:1 volume ratio for 24 hours, with the solvent being replaced with fresh solvent every 8 hours. After purification, it is air-dried naturally, sealed in an aluminum foil bag, and stored at 4°C in the dark for later use. The silicone membrane is detachably attached to the corresponding position of the sampler body through a pre-made slot structure on the fish body, and the edges are sealed with silicone to ensure a tight fit.

[0050] The thin-film diffusion gradient sampling unit of this invention adopts a multi-layer stacked structure. The sampling unit includes a filter membrane layer, a diffusion layer, and an adsorption layer that are stacked and tightly bonded together in sequence. Each layer is installed between the outer shell and the base of the thin-film diffusion gradient sampling unit and is fixed by bolts.

[0051] The specific specifications and preparation methods for each layer are as follows:

[0052] The filter membrane layer is made of polyethersulfone, with a pore size of 0.45 micrometers, a thickness of 0.14 millimeters, and a diameter of 2.5 centimeters.

[0053] The diffusion layer is an agarose hydrogel membrane with a thickness of 0.8 mm and a diameter of 2.5 cm. Its preparation method is as follows: 0.60 g of agarose is mixed with 40 mL of ultrapure water and heated to 95 °C in a water bath, stirred until the solution is completely transparent, yielding a 1.5% concentration hot agarose solution; while still hot, it is poured into a 0.8 mm thick glass mold, cooled and solidified, then cut into the required circular slices and stored in ultrapure water at 4 °C for later use.

[0054] The adsorption layer is formed by mixing and solidifying porous adsorption resin particles with high specific surface area and agarose gel. The preparation method is as follows: First, take a commercially available porous adsorption resin, such as XDA-1 resin, with a specific surface area of ​​not less than 1000 m² / g and an average pore size of approximately 3-5 nm. Rinse it three times with ultrapure water, and then rinse it twice with methanol to remove surface impurities. After grinding, pass it through a 200-mesh sieve and collect the powder passing through the sieve. Then, weigh 1 gram of the above-treated resin powder and mix it thoroughly with 10 ml of the above-mentioned 1.5% hot agarose solution at a mass-to-volume ratio of 1:10 g / ml. Finally, pour the mixture while hot into a 0.5 mm thick glass mold. After cooling and solidification, cut it into discs with a diameter of 2.5 cm and store them in ultrapure water at 4°C for later use.

[0055] When assembling the integrated passive sampler, the prepared first thin-film diffusion gradient sampling unit (201) and second thin-film diffusion gradient sampling unit (202) are placed into the first and second sampling chambers inside the sampler body, respectively. The chamber openings are sealed with sealing rings, ensuring that the corresponding exposure windows of each chamber are accurately aligned with the filter membrane layer of the thin-film diffusion gradient sampling unit. At this point, the integrated passive sampler assembly is complete. The assembled sampler is sealed in a clean aluminum foil bag and stored at 4°C in the dark, awaiting field deployment.

[0056] Example 2: Application of Integrated Passive Sampler in Performance Evaluation of Aquaculture Wastewater Treatment Process

[0057] This embodiment uses a wastewater treatment project at an intensive aquaculture base as an example to illustrate the standardized method for evaluating process efficiency using this invention. The project employs a combined treatment process of "equalization tank, biological filter, and ecological pond," with a designed treatment capacity of 500 cubic meters per day and a hydraulic retention time of 24 hours. The monitored target pollutants include non-polar organic pollutants (methanil, cypermethrin, bifenthrin) and polar organic pollutants (sulfamethoxazole, ofloxacin, sulfamethoxazole, 17β-estradiol).

[0058] Step 1: Deployment of Samplers: The integrated passive samplers prepared in Example 1 were deployed at key points in the treatment process. Specifically, point 1 was located at the outlet of the equalization tank, serving as the main process inlet; point 2 was located at the outlet of the biological filter; and point 3 was located at the outlet of the ecological pond, serving as the main process outlet. Three samplers were deployed in parallel at each point, directly placed in the upper and middle layers of the water body using a configured counterweight unit, at a depth of 0 to 0.5 meters from the water surface, avoiding contact with bottom sediments. The deployment time and environmental parameters of the water body, including water temperature, pH, flow rate, and dissolved oxygen, were recorded simultaneously. During deployment, the water temperature was 22-26℃, the pH was 7.6-8.2, the dissolved oxygen was 6.8-8.5 mg / L, and the flow rate in the water layer where the samplers were located was 0.02-0.10 m / s.

[0059] Step 2: Sampler Recovery and Sample Processing: Samplers were continuously deployed for 30 days. On day 7 of deployment, the thin-film diffusion gradient sampling units from all samplers were recovered; after 30 days of deployment, the silica gel membrane sampling units were recovered. During the 30-day deployment period, the integrity and positional stability of the sampler structure were checked every 7 days, and surface biofouling was removed. Upon recovery, the sampler surface was rinsed with deionized water, and then the adsorption layers of the silica gel membrane and the thin-film diffusion gradient sampling units were removed separately and placed in brown sealed containers, transported to the laboratory at 4°C in the dark.

[0060] The sample pretreatment procedures were as follows: For the silica membrane sampling unit, the silica membrane was placed in a centrifuge tube, 6 mL of ethyl acetate was added, the mixture was vortexed for 5 minutes, and ultrasonically extracted for 15 minutes. This extraction process was repeated once. Then, 6 mL of n-hexane was added, and the extraction was repeated twice. All extracts were combined, concentrated to near dryness under nitrogen at 40°C, and brought to a final volume of 300 μL with n-hexane. The extract was then filtered through a 0.22 μm organic phase filter membrane to obtain the first sample containing non-polar organic pollutants. For the thin-film diffusion gradient sampling unit, the adsorbed layer was removed and placed in a brown glass bottle, 5 mL of methanol was added, and the mixture was ultrasonically eluted for 20 minutes. This elution was repeated once. The eluent was combined, concentrated to near dryness under nitrogen at 40°C, and brought to a final volume of 1 mL with 30% acetonitrile aqueous solution. The extract was then filtered through a 0.22 μm organic phase filter membrane to obtain the second sample containing polar organic pollutants.

[0061] Step 3: Calculate the time-weighted average concentration: The first sample was analyzed using gas chromatography-tandem mass spectrometry (GC-MS) to determine the concentration C of each target pollutant in the silica gel membrane. s The second sample was analyzed using liquid chromatography-tandem mass spectrometry (LC-MS / MS) to determine the concentration C of each target pollutant in the eluent. e .

[0062] For nonpolar organic pollutants, the silica membrane-water partition coefficient K of each target analyte is considered. sw According to the formula C = C s / K sw Calculate the time-weighted average concentration in the water body. In this embodiment, the silica membrane-water partition coefficients Ksw of cypermethrin, fenvalerate, and bifenthrin were obtained by the above static adsorption equilibrium experiment, and their logKsw values ​​were 3.84, 4.59, and 4.55, respectively.

[0063] For polar organic pollutants, based on the measured eluent concentration C e elution volume (V) e =10 ml) and elution efficiency f e (92%-95%), calculate the cumulative amount of the target substance on the adsorption layer M = C e × V e / f e Based on the average water temperature of 22°C during deployment, query the water viscosity data (η). 25 =0.890 mPa·s, η 22 =0.957 mPa·s), combined with the known diffusion coefficient D of each target object at 25℃. 25 According to formula D t = D 25 × (T+273) / 298 × η 25 / η T Calculate the temperature-corrected diffusion coefficient D t .

[0064] Finally, considering the diffusion layer thickness Δg (0.008 cm), the effective exposure area A (4.91 square centimeters), and the deployment time t (604800 seconds), the formula C is applied according to Fick's first diffusion law. DGT = (M × Δg) / (D t Calculate the time-weighted average concentration C of polar organic pollutants in water bodies using the formula: × A × t). DGT .

[0065] Step 4: Calculate the removal rate of each treatment unit: Based on the concentration data at each location, calculate the removal rate of the target pollutant for each treatment unit. The formula for calculating the removal rate R is: R = (C in- C out ) / C in × 100%, C in C represents the concentration measured upstream of the unit. out The concentration was measured downstream of the unit.

[0066] The calculation results show that the biological filter unit achieved removal rates of 82.3%, 78.9%, and 80.5% for cypermethrin, fenvalerate, and bifenthrin, respectively; and removal rates of 75.6%, 68.2%, 72.8%, and 85.1% for sulfamethoxazole, ofloxacin, sulfamethoxazole, and 17β-estradiol, respectively. The ecological pond unit achieved removal rates of 8.7% to 15.3% for all the above pollutants. Therefore, it can be quantitatively concluded that the biological filter is the primary removal unit, contributing the vast majority of the treatment efficiency; while the ecological pond plays a supporting role in advanced treatment.

[0067] Comparative Analysis: Verification of Integration Effectiveness, Biomimetic Shape, and Long-Term Deployment Stability

[0068] To verify the advantages of this invention over traditional split-type deployment schemes, the following three sets of comparative experiments were conducted: Group A consisted of the integrated passive sampler of Embodiment 1 of this invention; Group B consisted of a separate silicone membrane sampler with a silicone membrane of the same material and area fixed on a conventional flat plate support; Group C consisted of a separate thin-film diffusion gradient sampler with a thin-film diffusion gradient sampling unit of the same specifications fixed in a conventional cylindrical shell. The three sets of devices were deployed in parallel in the same mandarin fish farming pond at a water level of 0.30±0.05 meters above the water surface, with 6 parallel samples in each group. During deployment, the average water temperature was 22.1±1.2℃, pH was 7.4±0.3, and the flow rate was 0.12±0.04 m / s.

[0069] The results of the comparison of silica membrane enrichment showed that after 30 days of deployment, the average enrichment of cypermethrin, fenvalerate, and bifenthrin on the silica membrane unit of group A were 81.36 ng, 121.94 ng, and 92.26 ng, respectively, which were 16.7%, 18.9%, and 12.3% higher than those of group B, respectively. All differences were statistically significant (p<0.05). Moreover, the relative standard deviation (RSD) of group A was between 5.68% and 6.36%, showing good repeatability.

[0070] The cumulative concentrations of the thin-film diffusion gradient sampling units showed that after 7 days of deployment, the average cumulative concentrations of sulfamethoxazole, ofloxacin, and 17β-estradiol on the adsorption layer of group A were 0.19 ng, 0.55 ng, and 0.20 ng, respectively, representing increases of 26.6%, 22.2%, and 17.6% compared to group C. All differences were statistically significant (p<0.05). The RSD of group A ranged from 4.9% to 6.2%, demonstrating good repeatability. This gain is attributed to the fact that the biomimetic streamlined shape of this invention effectively improves the local flow field around the sampler, resulting in a more uniform distribution of the water-side boundary layer and thus enhancing the enrichment efficiency of the sampling unit for pollutants.

[0071] To examine long-term deployment stability, fish samples made of addition-cure silica gel were continuously immersed in an aqueous solution at pH 7.5. Before the experiment, the initial tensile strength of the same batch of materials was 0.6 MPa, and the initial mass of the test samples was 50.0 g. After immersion for 30, 60, and 90 days, the tensile strength remained at 0.58 MPa, 0.55 MPa, and 0.52 MPa, respectively, with tensile strength retention rates of 96.7%, 91.7%, and 86.7%. The masses changed to 50.2 g, 50.5 g, and 51.1 g, respectively, with mass change rates of 0.4%, 1.0%, and 2.2%. This indicates that the material possesses excellent chemical and dimensional stability in simulated aquaculture wastewater. After continuous deployment in outdoor aquaculture wastewater for 30 days, inspection revealed that the sampler's external structure remained intact, the silica gel membrane slots did not detach, the chamber was well-sealed, and the dry weight of the biofilm on the window and silica gel membrane surface was only 0.18 ± 0.03 mg / cm². Periodic inspections and cleaning every 7 to 14 days can effectively control the degree of biofouling, restore the throughput of target materials, and ensure the long-term stability of sampling.

[0072] In summary, the integrated passive sampler and its application method provided by this invention successfully achieve simultaneous, in-situ, and dynamic monitoring and performance evaluation of multiple organic pollutants in aquaculture wastewater treatment processes. It has advantages such as strong data representativeness, good environmental adaptability, simple operation, and low cost, providing reliable technical support for the optimization of aquaculture wastewater treatment processes.

[0073] The above description is merely a preferred embodiment of the present invention and does not limit the scope of the patent. Any equivalent structural modifications made based on the inventive concept of the present invention and the description and drawings, or direct / indirect applications in other related technical fields, are included within the scope of patent protection of the present invention.

Claims

1. An integrated passive sampler, characterized in that, include: A sampler body, wherein the sampler body has at least two independent sampling chambers inside; At least one silicone membrane sampling unit is attached to the outer surface of the sampler body for enriching non-polar organic pollutants in the water. At least two thin-film diffusion gradient sampling units are respectively and detachably installed in the sampling chamber. Each thin-film diffusion gradient sampling unit includes a filter membrane layer, a diffusion layer and an adsorption layer that are stacked and tightly attached in sequence. The adsorption layer is formed by mixing and solidifying porous adsorption resin particles with high specific surface area and agarose gel, and is used to enrich polar organic pollutants in water. The sampler body has at least one exposure window at the location corresponding to each of the sampling chambers. The exposure window connects the sampling chamber to the external water body, and the window is covered with a protective net with an aperture of 1-2 mm.

2. The integrated passive sampler according to claim 1, characterized in that, The silicone membrane sampling unit is made of addition-cured silicone material with a thickness of 0.5-2.0 mm, and is detachably attached to the sampler body via a slot-type structure.

3. The integrated passive sampler according to claim 1, characterized in that, In the thin film diffusion gradient sampling unit: The filter membrane layer is a polyethersulfone filter membrane with a pore size of 0.45 μm and a thickness of 0.14 mm; The diffusion layer is an agarose hydrogel membrane with a thickness of 0.8 mm; The adsorption layer is a 0.5 mm thick disc formed by mixing porous adsorption resin powder that has passed through a 200-mesh sieve with a 1.5% hot agarose solution at a mass-volume ratio of 1 g: 10 mL and then solidifying it.

4. The integrated passive sampler according to claim 1, characterized in that, The sampler body is a streamlined, biomimetic fish shape.

5. The integrated passive sampler according to claim 4, characterized in that, The sampler body has a counterweight inside.

6. The integrated passive sampler according to claim 4, characterized in that, The silicone membrane sampling unit is shaped like a biomimetic fish fin or tail and is attached to the corresponding position of the sampler body.

7. The integrated passive sampler according to claim 1, characterized in that, The sampler body is formed by curing a mixture of liquid silicone and hydrogen-based siloxane in a 1:1 weight ratio.

8. A method for evaluating the efficiency of aquaculture wastewater treatment processes, characterized in that, Using the integrated passive sampler according to any one of claims 1 to 7, and comprising the following steps: Step 1: Deploy the integrated passive sampler at the inlet, inside at least one treatment unit, and at the outlet of the aquaculture wastewater treatment process; Step 2: After continuous deployment for 7-30 days, retrieve the sampler, extract organic solvent from the silica membrane sampling unit to obtain the first test sample containing non-polar organic pollutants; remove the adsorption layer of the thin film diffusion gradient sampling unit and elute it with solvent to obtain the second test sample containing polar organic pollutants. Step 3: Based on the analysis results of the first sample to be tested, obtain the mass of the target pollutant in the extract of the silica membrane sampling unit. Then, based on the extract volume and the mass of the silica membrane sampling unit, calculate the concentration of the target pollutant in the silica membrane sampling unit. Combined with the silica membrane-water partition coefficient, calculate the concentration of non-polar organic pollutants in the water. Based on the analysis results of the second sample to be tested, obtain the cumulative amount of the target pollutant on the adsorption layer. Combined with the deployment time, diffusion layer thickness, effective exposure area, and temperature-corrected diffusion coefficient, calculate the time-weighted average concentration of polar organic pollutants in the water using Fick's first diffusion law. Step 4: Based on the time-weighted average concentration of the target pollutant measured by samplers deployed upstream and downstream of the same treatment unit, calculate the removal rate R of the target pollutant by the treatment unit. The calculation formula is as follows: R = (C in - C out ) / C in × 100% Among them, C in C represents the concentration measured by the upstream sampler. out The concentration measured by the downstream sampler.

9. The method for evaluating the efficiency of aquaculture wastewater treatment process according to claim 8, characterized in that, In step three, the formula for calculating the concentration of non-polar organic pollutants in the water body is: C = C s / K sw Among them, C s K represents the concentration of the target pollutant in the silica membrane sampling unit. sw The silica membrane-water partition coefficient.

10. The method for evaluating the efficiency of aquaculture wastewater treatment process according to claim 8, characterized in that, In step three, the temperature-corrected diffusion coefficient is calculated using the following formula: D t =D 25 × (T+273) / 298 × n 25 / the T In the formula, D 25 η is the diffusion coefficient of the target at 25°C, T is the average temperature of the water body during deployment, and η is the diffusion coefficient of the target at 25°C. 25 η is the viscosity of water at 25°C. T Let T represent the viscosity of water at T℃.

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