A river and lake multi-medium environment pollution in-situ cooperative monitoring system and method

Abstract

The application provides a river and lake multi-medium environment pollution in-situ cooperative monitoring system and method, which comprises a floating intelligent monitoring platform, a three-phase interface environment in-situ monitoring unit and a data processing and intelligent analysis unit. The floating intelligent monitoring platform is a floating platform arranged on the water surface. The three-phase interface environment in-situ monitoring unit comprises an atmospheric interface environment monitoring unit, a water phase interface environment monitoring unit and a bottom mud interface monitoring unit. The data processing and intelligent analysis unit is a remote cloud platform and an intelligent analysis center arranged in a cloud server. Based on the application, in-situ, synchronous and continuous monitoring of the physicochemical indexes and pollutant concentrations of the key environmental interfaces of rivers and lakes can be realized. Through data fusion and model analysis, the migration and transformation rules of pollutants among the three-phase media are revealed, and comprehensive data support and decision basis for accurate tracing, risk assessment and comprehensive management are provided.

Description

Technical Field

[0001] This invention belongs to the field of environmental monitoring technology, specifically relating to an in-situ collaborative monitoring system and method for multi-media environmental pollution monitoring in rivers and lakes. Background Technology

[0002] River and lake water pollution is a complex multi-media process, involving continuous migration, transformation, and exchange of pollutants (such as heavy metals, nutrients, persistent organic pollutants, and emerging pollutants) between water bodies, sediments (bottom sediment), and the atmosphere. For example, atmospheric deposition is a significant source of pollutants such as mercury and polycyclic aromatic hydrocarbons in water bodies; bottom sediments serve as both a "sink" (accumulation) of pollutants and a "source" (release) when environmental conditions change, releasing pollutants to the overlying water through the sediment-water interface; and the water-air interface involves the exchange of gases (such as greenhouse gases like CH4, N2O, and CO2, as well as volatile organic compounds). Currently, monitoring of river and lake environments often employs single-media or multi-item monitoring models, such as: 1) Atmospheric monitoring: typically, fixed stations are set up along the shore to monitor conventional atmospheric pollutants, lacking in-situ monitoring of near-water surface dry and wet deposition fluxes above the water body. 2) Water body monitoring: Common methods include buoy-type water quality monitoring stations, shore-based stations, or unmanned surface vessels (USVs). These primarily monitor indicators such as pH, dissolved oxygen (DO), turbidity, conductivity, chemical oxygen demand (COD), ammonia nitrogen, and total phosphorus and total nitrogen. However, their sensors are typically deployed at fixed underwater depths (e.g., 0.5 meters or 1 meter), making it impossible to accurately capture gradient changes at the two key micro-interfaces: the water-air interface and the sediment-water interface. 3) Sediment monitoring: This mainly relies on manual or mechanical sampling followed by laboratory analysis. It is a non-in-situ, discontinuous, and destructive monitoring method that cannot reflect the dynamic exchange process at the sediment-water interface in real time.

[0003] The aforementioned segmented monitoring methods sever the intrinsic connections between pollutants in multi-media environments, making it difficult to accurately trace pollution sources, quantify cross-interface fluxes, and reveal migration and transformation mechanisms, thereby affecting the accuracy of pollution assessments and the scientific nature of governance decisions.

[0004] With the development of IoT, micro-sensors, and artificial intelligence technologies, environmental pollution monitoring is evolving towards "in-situ, real-time, multi-parameter, intelligent, and collaborative" approaches. Therefore, there is an urgent need for a system and method capable of integrated, in-situ, synchronous monitoring of the three-phase interface environment of sediment, water, and atmosphere, and enabling collaborative data analysis and application to fill current technological gaps. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention aims to provide an in-situ collaborative monitoring system and method for the three-phase interface environment of river and lake sediment-water-atmosphere. Its core objective is to achieve in-situ, synchronous, and continuous monitoring of the physicochemical indicators and pollutant concentrations of key environmental interfaces in rivers and lakes (atmosphere-water interface and water-sediment interface). Through data fusion and model analysis, it reveals the migration and transformation laws of pollutants in the three-phase media, providing comprehensive data support and decision-making basis for accurate source tracing, risk assessment, and integrated management.

[0006] The technical solution adopted by the present invention to solve the problems existing in the prior art is as follows: A multi-media in-situ collaborative monitoring system for river and lake environmental pollution includes a floating intelligent monitoring platform, a three-phase interface environment in-situ monitoring unit, and a data processing and intelligent analysis unit. The floating intelligent monitoring platform is a floating platform deployed on the water surface, with a main control cabin housing an edge computing and data integration unit, a power management system, and an attitude stabilization system. The three-phase interface environment in-situ monitoring unit includes three interface environment monitoring units located at different positions: an atmospheric interface environment monitoring unit, a water phase interface environment monitoring unit, and a sediment interface monitoring unit. The atmospheric interface environment monitoring unit includes near-water surface atmospheric and wet / dry deposition monitoring instruments fixed on the floating platform. The water phase interface environment monitoring unit includes gradient-type multi-parameter water quality profile monitoring instruments deployed at several layers below the water surface. The sediment interface monitoring unit includes a sediment pollution in-situ dynamic sampling instrument located below the sediment surface. The data processing and intelligent analysis unit is a remote cloud platform and intelligent analysis center deployed on a cloud server, including a data receiving engine, a distributed database, a model algorithm library, and a visual interactive interface.

[0007] The floating intelligent monitoring platform is a ship-shaped or buoy-type platform made of ultra-high molecular weight polyethylene or corrosion-resistant composite materials, possessing excellent stability, wind and wave resistance, and anti-biofouling properties. The power management system is a combination of solar panels and high-energy battery packs, or optionally, a small wind turbine. The attitude stabilization system includes a BeiDou positioning module and an attitude sensor, optionally equipped with a thruster or mooring system to achieve precise positioning and anti-drift. Specifically, the BeiDou positioning module can be model SIM65M-CB, the attitude sensor can be model IMU620, the thruster can be model Momentum-M6, and the mooring system can be model Jiesheng-CYM86.

[0008] The edge computing and data integration unit includes an industrial-grade embedded processor, a large-capacity memory, and a multi-protocol communication module. Based on this unit, real-time acquisition, preprocessing (filtering, calibration, outlier removal), and time synchronization marking of data from various sensors are performed. A lightweight edge AI model is run to perform preliminary data fusion and event recognition, such as identifying sudden increases in pollutant concentration, calculating preliminary interface throughput, and assessing data quality. Following a set strategy, such as timed or threshold-triggered events, the integrated multi-source heterogeneous data packets are compressed, encrypted, and wirelessly transmitted to a remote cloud platform. The industrial-grade embedded processor can be an AR502H-V2, the large-capacity memory can be a TGQ200, the multi-protocol communication module can be 4G / 5G / NB-IoT / satellite communication, and the lightweight edge AI model can be MobileNetV3-Tiny.

[0009] The sensor probe of the near-water surface atmospheric and wet / dry deposition monitoring instrument is located within 0.5-1.5 meters above the water surface, preferably 1 meter, to capture near-water surface atmospheric and wet / dry deposition that directly affects the water body. It includes an automatic wet / dry deposition collection and online analysis module and a near-water surface meteorological and gas monitoring module. The automatic wet / dry deposition collection and online analysis module includes a precipitation sensor with an automatically opening and closing cover and a miniature spectral analysis unit. The precipitation sensor can be an Eigenbrodt-IRSS model. 88. The automatically opening and closing cover includes a dry sedimentation collection tank, a wet sedimentation collection tank, a movable dust cover, a motor-driven four-bar linkage mechanism, and a control module. Based on the detection signal of the precipitation sensor: when precipitation is detected, the control module drives the dust cover to move away from the wet sedimentation tank and cover the dry sedimentation tank, at which time only the wet sedimentation tank is open to collect wet sedimentation; when precipitation stops, the dust cover moves in the opposite direction, moving away from the dry sedimentation tank and covering the wet sedimentation tank, at which time only the dry sedimentation tank is open to collect dry sedimentation. This alternating covering method achieves automatic separation and collection of dry and wet sedimentation. The micro-spectral analysis unit includes LIBS laser-induced breakdown spectroscopy (LIBS8000), a micro ICP-MS injection interface, and a microfluidic chip shop-MF unit, used for in-situ or quasi-in-situ analysis of heavy metals (such as Hg, Pb, Cd) and water-soluble ions (NO3) in sediments. - SO4 2- NH4 + The near-water surface meteorological and gas monitoring module includes a micro weather station and a micro gas analyzer, used to continuously monitor the concentration and flux of gases such as CH4, CO2, N2O, and VOCs (estimated by combining the gradient method or eddy covariance method). The micro weather station can be model ZWIN-WS1006, and the micro gas analyzer can be model G2508.

[0010] The gradient-type multi-parameter water quality profile monitor extends downwards from the floating platform via a retractable or flexible umbilical cable, deploying at least two key layers: a surface water monitoring layer, where the sensor array is positioned 0.2-0.5 meters below the water surface, focusing on water properties below the water-air interface; and a bottom water monitoring layer, where the sensor array is positioned 0.2-0.5 meters above the mud surface, focusing on water properties at the mud-water interface. Further, several intermediate layer sensors can be added between these two layers, or a miniature profile winch can be used to drive the sensor array for vertical periodic micro-profile scanning, for example, completing a 0-2 meter water depth scan every hour to obtain more refined vertical gradient information. The miniature profile winch can be selected from the Vesee water quality vertical profile automatic monitoring system.

[0011] The gradient-type multi-parameter water quality profile monitoring instrument includes sensors such as a conventional multi-parameter probe, a nutrient in-situ analyzer, and a heavy metal pollutant sensor. The conventional multi-parameter probe is used to monitor pH, dissolved oxygen (DO), oxidation-reduction potential (ORP), conductivity, turbidity, temperature, chlorophyll a, and cyanobacteria. The nutrient in-situ analyzer includes an in-situ nitrate probe using ultraviolet-visible spectroscopy, an in-situ DOM (dissolved organic matter) probe using fluorescence spectroscopy, and an in-situ ammonia nitrogen / phosphate analyzer based on miniaturized flow injection analysis (FIA) or sequential injection analysis (SIA) technology. The heavy metal pollutant sensor includes a heavy metal ion selective electrode array and a miniature sensor based on surface-enhanced Raman scattering (SERS) or fluorescence quenching principles, used to detect trace heavy metals and specific organic pollutants. The conventional multi-parameter probe can be selected as EXO2, the UV-Vis spectroscopy in-situ nitrate probe can be selected as SUNA V2, the fluorescence in-situ DOM probe can be selected as TriOS-nanoFlu, the ammonia nitrogen / phosphate in-situ analysis probe can be selected as ZealChem300, the heavy metal ion selective electrode array can be selected as HI4115, and the micro-sensor can be selected as Metrohm Raman-MISA.

[0012] The probe of the in-situ dynamic sediment pollution sampling instrument is inserted 10-30 cm below the surface of the sediment. It includes an in-situ sediment pore water acquisition and detection module and an in-situ sediment physicochemical sensor. The in-situ sediment pore water acquisition and detection module periodically (e.g., every 24 hours) collects pore water near the sediment-water interface using an in-situ stratified intelligent sampling device, and transports it to an optical sensor on the platform via a micro-flow path for analysis, obtaining a high spatial resolution pollutant concentration profile. The in-situ sediment physicochemical sensor uses a planar optical imaging system for two-dimensional visualization monitoring of the spatiotemporal distribution of dissolved oxygen and pH near the sediment-water interface. The in-situ stratified intelligent sampling device can be selected from the rapid in-situ stratified sediment pollution sampling device for rivers and lakes independently developed by the Yangtze River Scientific Research Institute of the Yangtze River Water Resources Commission (this device has been disclosed in patent application number CN 202410935887.7), the optical sensor can be selected as model EXPEC 3600, and the planar optical imaging system can be selected as model PO2100.

[0013] The remote cloud platform and intelligent analysis center's data receiving engine, distributed database, model algorithm library, and visual interactive interface respectively implement the following functions: 1) The data receiving engine achieves deep fusion of multi-source spatiotemporal data: it correlates and matches three-phase data from the atmosphere, water bodies, and sediments under a unified spatiotemporal coordinate system; 2) The distributed database provides massive storage and efficient retrieval support for deep fusion of multi-source spatiotemporal data, and provides data support for the model algorithm library; 3) The model algorithm library provides pollutant cross-media migration and transformation models: it integrates multi-media fugacity models based on physicochemical principles or data-based machine learning models (such as LSTM neural networks). (Network, Random Forest), quantitatively simulate and predict the flux and fate of pollutants in the atmospheric deposition-water migration-sediment adsorption / release process, as well as collaborative early warning and source tracing analysis: establish a three-phase index association rule base, when an anomaly occurs in a certain medium, automatically associate and analyze data of other media, conduct collaborative early warning and assist in pollution source tracing (for example, after the concentration of heavy metals in atmospheric deposition increases, predict and verify its subsequent changes in surface water and sediment); 4) Visual interactive interface to realize three-dimensional visualization and decision support: provide a three-dimensional dynamic view of the spatiotemporal distribution of pollutant concentration, flux heat map, migration path simulation animation, and generate a comprehensive monitoring and assessment report.

[0014] This invention provides an in-situ coordinated monitoring method for the three-phase interface environment of river and lake sediment-water-atmosphere based on the above-mentioned system. The method includes the following steps: Step 1: System Deployment and Initialization: Deploy the monitoring system to the target river or lake area, stabilize it at the preset monitoring point by anchoring or dynamic positioning, start the system, perform self-testing and calibration of each sensor, and establish a communication link between the edge computing unit and the cloud platform. Step 2: Synchronous acquisition of three-phase in-situ data: The system synchronously triggers the atmospheric interface environmental monitoring unit, the aqueous interface environmental monitoring unit, and the sediment interface environmental monitoring unit at a preset frequency (such as every minute or every hour) to collect the physicochemical indicators and pollutant concentration data of the three-phase interface. All data are labeled with the synchronous monitoring time and location. Step 3: Edge-side data preprocessing and preliminary fusion: The edge computing unit performs quality control on the raw data and performs preliminary data fusion based on a preset algorithm (e.g., calculating the vertical water quality gradient and making a preliminary estimate of the sedimentation flux). Step 4: Remote data transmission and cloud storage: The pre-processed and initially fused data packets are transmitted to a remote cloud platform via a wireless network and stored in a spatiotemporal database; Step 5: Cloud-based intelligent collaborative analysis and modeling: The cloud platform calls a multi-media migration and transformation model to perform deep correlation analysis on the three-phase data, specifically including: calculating atmospheric dry and wet deposition flux, water-air interface gas exchange flux, and mud-water interface pollutant diffusion / release flux; using the model to identify the main sources of pollutants (atmospheric deposition contribution rate, endogenous release contribution rate) and key migration paths; and training or optimizing the prediction model based on historical and real-time data to predict the development of pollution trends. Step 6: Results Visualization, Early Warning and Report Generation: The analysis results are dynamically displayed in the visualization interface in the form of charts, 3D animations, etc. When the monitored value or the model prediction value exceeds the preset threshold, multi-level early warning is triggered, and a comprehensive monitoring report covering three-phase status, flux calculation and risk assessment is automatically generated on a regular basis.

[0015] The present invention has the following advantages: 1. Achieved true multi-media in-situ collaborative monitoring: For the first time, the in-situ monitoring of three key environmental media—atmosphere (deposition and near-water surface gas), water body (vertical gradient), and sediment (pore water and interfacial processes)—was integrated into a single platform, achieving a high degree of synchronization in time and space, and providing an unprecedented complete data chain for the study of cross-media processes; 2. Highly targeted monitoring and high spatial resolution: The sensors are precisely deployed at the two micro-interfaces of water-air and mud-water and their adjacent areas, and can perform vertical micro-profile scanning and pore water profile analysis, which can capture interface gradient information and micro-processes that cannot be obtained by traditional methods. 3. High level of intelligence: It integrates edge computing and cloud AI, and has the capabilities of real-time data fusion, preliminary event recognition, deep model analysis and intelligent early warning, upgrading from "data collection" to "knowledge discovery and decision support"; 4. Advanced technology and high integration: It integrates advanced in-situ monitoring technologies such as micro-spectroscopy / mass spectrometry, planar optical polarization, SERS, and in-situ stratified intelligent sampling, as well as Internet of Things, big data and artificial intelligence models, representing the cutting-edge development direction of environmental monitoring technology; 5. Significant application value: It can provide direct, comprehensive and continuous scientific basis for the analysis of river and lake pollution sources, risk assessment of endogenous release, estimation of greenhouse gas flux, and evaluation of pollution control effectiveness, and has significant application value in environmental management. Attached Figure Description

[0016] Figure 1 A schematic diagram illustrating the structural composition, three-phase interface environment monitoring locations, equipment deployment, and monitoring content of the invention monitoring system; Figure 2 This is a flowchart of the monitoring method of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be further described in detail below through embodiments.

[0018] The system of this invention was applied to the collaborative monitoring of eutrophic lakes in cities. Specifically, to address the summer cyanobacterial blooms and endogenous release issues in a certain urban landscape lake, the system was deployed with the following configuration: Atmospheric Interface Environmental Monitoring Unit: This unit focuses on monitoring the atmospheric dry and wet deposition fluxes of nitrogen and phosphorus nutrients, as well as the near-water surface CH4 concentration. An integrated automatic dry and wet deposition collection and online analysis module is deployed approximately 1.0 m above the water surface and connected to a floating intelligent monitoring platform. This module includes a precipitation sensor, a motor-driven dust cover, dry deposition tanks, and wet deposition tanks. It is connected to a LIBS laser-induced breakdown spectroscopy and microfluidic colorimetric analysis unit for daily automatic separation, collection, and in-situ analysis of ammonium nitrogen, nitrate nitrogen, orthophosphate, and water-soluble total phosphorus in atmospheric dry and wet deposition. A miniature gas analyzer is deployed at approximately 0.8 m above the water surface on the top of the platform, along with a miniature weather station, for continuous monitoring of near-water surface CH4 and CO2 concentrations and fluxes, assisting in estimating the intensity of greenhouse gas emissions from the lake.

[0019] Aquatic interface environmental monitoring unit: Key monitoring parameters for surface and bottom water include DO, pH, ORP, chlorophyll a, ammonia nitrogen, nitrate, and phosphate. An intermediate layer micro-profiling scanner is added to capture the thermocline and dissolved oxygen cascade. A multi-parameter water quality profiler is suspended below the floating platform via a flexible umbilical cable. The specific deployment is as follows: a surface water monitoring layer sensor group is deployed at 0.3 m below the water surface, including a conventional multi-parameter probe and a fluorescence in-situ DOM probe; intermediate layer sensors are deployed at 0.5 m, 1.0 m, 1.5 m, and 1.8 m below the water surface, respectively, including a conventional multi-parameter probe and a UV-Vis nitrate probe; and a bottom water monitoring layer sensor group is deployed approximately 0.3 m above the mud-water interface, including a conventional multi-parameter probe, a miniaturized flow injection analysis-type ammonia nitrogen / phosphate in-situ analyzer, and a heavy metal ion selective electrode array. Meanwhile, a miniature profile winch is installed at the bottom of the platform. An independent multi-parameter sensor is mounted on the winch cable to perform vertical periodic micro-profile scanning in the 0-2 m water depth range once per hour, which is used to identify the fine structure and diurnal changes of the thermocline and dissolved oxygen strata.

[0020] Sediment Interface Environmental Monitoring Unit: A planar optical imaging system is used to observe the two-dimensional distribution of dissolved oxygen (DO) and pH at the sediment-water interface in real time. A high-resolution profile of reactive phosphate and iron / manganese ions in pore water is obtained using an in-situ rapid sediment sampling device. A stainless steel guide sleeve is fixed to the gravity base of the floating platform or the sinking support of the mooring system. An in-situ dynamic sediment sampling instrument is installed inside the sleeve using an electrically operated actuator. The probe of the sampling instrument is vertically inserted 30 cm below the surface of the sediment. Specifically, a planar optical imaging system is fitted to the side of the probe facing the sediment-water interface. Its photosensitive film covers an area from 1 cm above the sediment surface to 3 cm below, enabling two-dimensional visualization and monitoring of the microscale spatiotemporal distribution of dissolved oxygen and pH (imaged once per hour). An in-situ sediment pore water acquisition module (a layered sampling probe developed by the Yangtze River Scientific Research Institute, automatically extracting pore water from six layers (5 cm, 10 cm, 15 cm, 20 cm, 25 cm, and 30 cm below the sediment surface) is integrated inside the probe. The collected pore water is transported via a micro-flow path to a micro-spectroscopy-mass spectrometry unit in the main control cabin of the floating platform for analysis of reactive phosphate and iron ions (Fe). 2+ / Fe 3+ ), manganese ions (Mn) 2+ High-resolution profiles of the iron / phosphorus coupling release mechanism were obtained to evaluate the iron / phosphorus coupling release mechanism.

[0021] The in-situ coordinated monitoring method for the three-phase interface environment of river and lake sediment-water-atmosphere based on the above system configuration includes the following steps: Step 1: System Deployment and Initialization The monitoring system is deployed to the target monitoring points. The floating intelligent monitoring platform is stabilized in the predetermined position using an anchoring system. The system is then activated, and each sensor performs self-tests and calibrations: the automatic dry and wet deposition collection module, miniature gas analyzer, and miniature weather station in the atmospheric interface environment monitoring unit undergo initial calibration; the conventional multi-parameter probes, fluorescence DOM probes, UV-Vis nitrate probes, ammonia / phosphate in-situ analyzers, and heavy metal ion selective electrode arrays in the aqueous interface environment monitoring unit undergo zero-point calibration and slope calibration; the planar optical imaging system in the sediment interface environment monitoring unit performs background correction, and the sediment pore water in-situ acquisition module performs flow path cleaning and sealing tests. The edge computing unit establishes a wireless communication link with the remote cloud platform.

[0022] Step 2: Synchronous acquisition of three-phase in-situ data: The system synchronously triggers the three-phase interface environment monitoring unit to collect data at a preset frequency: (1) Atmospheric interface: The dry and wet deposition automatic collection module automatically switches between dry and wet deposition collection modes according to the precipitation sensor signal, and automatically separates and collects atmospheric dry and wet depositions every day. The ammonium nitrogen, nitrate nitrogen, orthophosphate and water-soluble total phosphorus in the depositions are analyzed in situ by LIBS laser-induced breakdown spectroscopy and microfluidic colorimetric analysis unit. The micro gas analyzer and micro weather station continuously monitor the concentration and flux of CH4 and CO2 near the water surface.

[0023] (2) Aquatic interface: The sensor groups at the surface layer 0.3 m below the water surface, the intermediate layer sensor groups at 0.5 m, 1.0 m, 1.5 m, and 1.8 m, and the bottom layer sensor group at the mud-water interface 0.3 m above the water surface simultaneously collect parameters such as DO, pH, ORP, chlorophyll a, ammonia nitrogen, nitrate, and phosphate; the micro profile winch performs vertical periodic micro profile scanning in the water depth range of 0-2 m at a frequency of once per hour.

[0024] (3) Sediment interface: The planar optical imaging system images the area from 1 cm above the sediment surface to 3 cm below the sediment surface once per hour, and monitors the microscale spatiotemporal distribution of DO and pH in two dimensions; the sediment pore water in-situ acquisition module automatically extracts pore water from six layers (5 cm, 10 cm, 15 cm, 20 cm, 25 cm, and 30 cm below the sediment surface) every 24 hours, and transports it to the micro-spectroscopy-mass spectrometry unit in the main control chamber through a micro-flow path to analyze reactive phosphate and Fe. 2+ / Fe 3+ Mn 2+ High-resolution profile.

[0025] Step 3: Data Preprocessing and Initial Fusion The edge computing unit performs quality control on the raw data from each sensor, including filtering, calibration, and outlier removal. Preliminary data fusion is performed based on a pre-defined algorithm: calculating vertical water quality gradients (such as changes in DO, pH, and nutrients with water depth), and making preliminary estimates of atmospheric dry and wet deposition fluxes; a lightweight edge AI model is run to identify anomalous events such as sudden increases in pollutant concentrations to assess data quality.

[0026] Step 4: Remote data transmission and cloud-based data entry: The pre-processed and initially fused data packets are compressed and encrypted according to a set strategy (timed or threshold-triggered), and transmitted to a remote cloud platform via a 4G / 5G wireless network, where they are stored in a distributed spatiotemporal database.

[0027] Step 5: Cloud-based intelligent collaborative analysis and modeling: The cloud platform invokes a multi-media migration and transformation model to perform deep correlation analysis on three-phase data: calculating the dry and wet deposition fluxes of atmospheric nitrogen and phosphorus nutrients, the CH4 and CO2 exchange fluxes at the water-air interface, and the reactive phosphate and Fe at the mud-water interface. 2+ / Fe 3+ Mn 2+ The diffusion / release fluxes are measured; models are used to identify the main sources of pollutants (atmospheric deposition contribution rate, endogenous release contribution rate) and key migration pathways, with a focus on analyzing the iron / phosphorus coupling release mechanism; prediction models are trained or optimized based on historical and real-time data to predict the development of eutrophication and cyanobacterial blooms.

[0028] Step 6: Result Visualization, Alerts, and Report Generation: The analysis results are dynamically displayed in a visualization interface in the form of charts, 3D animations, etc., showing the spatiotemporal distribution of pollutant concentrations, flux heat maps, and migration path simulation animations. When the monitored value or model prediction value exceeds the preset threshold, multi-level early warnings are triggered. Comprehensive monitoring reports covering three-phase states, flux calculations, and risk assessments (including greenhouse gas emission intensity assessment and endogenous release risk assessment) are automatically generated periodically.

[0029] The scope of protection of this invention is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its scope and spirit. If these modifications and variations fall within the scope of the claims of this invention and their equivalents, then the intent of this invention also includes these modifications and variations.

Claims

1. A multi-media in-situ collaborative monitoring system for environmental pollution in rivers and lakes, characterized in that: The system comprises a floating intelligent monitoring platform, a three-phase interface environment in-situ monitoring unit, and a data processing and intelligent analysis unit. The floating intelligent monitoring platform is a floating platform deployed on the water surface, with a main control cabin housing an edge computing and data integration unit, a power management system, and an attitude stabilization system. The three-phase interface environment in-situ monitoring unit includes three interface environment monitoring units located at different positions: an atmospheric interface environment monitoring unit, a water phase interface environment monitoring unit, and a sediment interface monitoring unit. The atmospheric interface environment monitoring unit includes near-water surface atmospheric and wet / dry deposition monitoring instruments fixed on the floating platform. The water phase interface environment monitoring unit includes gradient-type multi-parameter water quality profile monitoring instruments deployed at several layers below the water surface. The sediment interface monitoring unit includes a sediment pollution in-situ dynamic sampling instrument located below the sediment surface. The data processing and intelligent analysis unit is a remote cloud platform and intelligent analysis center deployed on a cloud server, including a data receiving engine, a distributed database, a model algorithm library, and a visual interactive interface.

2. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The floating intelligent monitoring platform is a ship-shaped or buoy-type platform made of ultra-high molecular weight polyethylene or corrosion-resistant composite materials; the power management system is a combination of solar panels and high-energy battery packs, or optionally equipped with a small wind turbine; the attitude stabilization system includes a Beidou positioning module and attitude sensors, and optionally equipped with a thruster or mooring system.

3. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The edge computing and data integration unit includes an industrial-grade embedded processor, a large-capacity memory, and a multi-protocol communication module. Based on this unit, the data from each sensor is collected, preprocessed, and time-synchronized and marked in real time. A lightweight edge AI model is run to perform preliminary data fusion and event recognition. After the integrated multi-source heterogeneous data packets are compressed and encrypted according to a set strategy, they are wirelessly transmitted to a remote cloud platform.

4. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The sensor probe of the near-water surface atmospheric and wet / dry deposition monitoring instrument is located within 0.5-1.5 meters above the water surface to capture near-water surface atmospheric and wet / dry deposition that directly affect the water body. The sensor of the near-water surface atmospheric and wet / dry deposition monitoring instrument includes an automatic wet / dry deposition collection and online analysis module and a near-water surface meteorological and gas monitoring module. The automatic wet / dry deposition collection and online analysis module includes a precipitation sensor, an automatically opening and closing cover plate, and a miniature spectral analysis unit for collecting wet and dry deposition samples and analyzing heavy metals, water-soluble ions, and emerging pollutants in the deposition in situ or quasi-situ. The near-water surface meteorological and gas monitoring module includes a miniature weather station and a miniature gas analyzer for continuously monitoring gas concentration and flux.

5. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 4, characterized in that: The automatically opening and closing cover includes a dry sedimentation collection tank, a wet sedimentation collection tank, a movable dust cover, a motor-driven four-bar linkage mechanism, and a control module. Based on the detection signal of the precipitation sensor: when precipitation is detected, the control module drives the dust cover to move away from the wet sedimentation tank and cover the dry sedimentation tank. At this time, only the wet sedimentation tank is open to collect wet sedimentation. When the precipitation stops, the dust cover moves in the opposite direction, moves away from the dry sedimentation tank and covers the wet sedimentation tank. At this time, only the dry sedimentation tank is open to collect dry sedimentation. The automatic separation and collection of dry and wet sedimentation is achieved through this alternating covering method.

6. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The gradient-type multi-parameter water quality profiler extends downward from the floating platform via a retractable or flexible umbilical cable, deploying at least two key layers: a surface water monitoring layer and a bottom water monitoring layer. The surface water monitoring layer places the sensor array 0.2-0.5 meters below the water surface, focusing on water properties below the water-air interface; the bottom water monitoring layer places the sensor array 0.2-0.5 meters above the mud surface, focusing on water properties at the mud-water interface. Several intermediate layer sensors are added between the two layers, or a miniature profile winch is used to drive the sensor array for vertical periodic micro-profile scanning.

7. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The gradient-type multi-parameter water quality profiler includes sensors such as a conventional multi-parameter probe, a nutrient in-situ analyzer, and a heavy metal pollutant sensor. The conventional multi-parameter probe is used to monitor pH, dissolved oxygen, redox potential, conductivity, turbidity, temperature, chlorophyll a, and cyanobacteria. The nutrient in-situ analyzer includes an in-situ nitrate probe using ultraviolet-visible spectroscopy, an in-situ DOM probe using fluorescence, and an in-situ ammonia nitrogen / phosphate analyzer based on miniaturized flow injection analysis or sequential injection analysis technology. The heavy metal pollutant sensor includes a heavy metal ion selective electrode array and a miniature sensor based on surface-enhanced Raman scattering or fluorescence quenching principles, used to detect trace heavy metals and specific organic pollutants.

8. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The probe of the in-situ dynamic sediment pollution acquisition instrument is inserted 10-30 cm below the sediment surface. It includes an in-situ sediment pore water acquisition and detection module and an in-situ sediment physicochemical sensor. The in-situ sediment pore water acquisition and detection module periodically collects pore water near the sediment-water interface through an in-situ stratified intelligent acquisition device, and transports it to an optical sensor on the platform through a micro-flow path for analysis to obtain a high spatial resolution pollutant concentration profile. The in-situ sediment physicochemical sensor adopts a planar optical imaging system for two-dimensional visualization monitoring of the spatiotemporal distribution of dissolved oxygen and pH near the sediment-water interface.

9. The in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in claim 1, characterized in that: The remote cloud platform and intelligent analysis center includes a data receiving engine, a distributed database, a model algorithm library, and a visual interactive interface. The data receiving engine enables deep fusion of multi-source spatiotemporal data: it correlates and matches three-phase data from the atmosphere, water bodies, and sediments within a unified spatiotemporal coordinate system. The distributed database provides massive storage and efficient retrieval support for the deep fusion of multi-source spatiotemporal data and provides data support for the model algorithm library. The model algorithm library provides pollutant cross-media migration and transformation models, integrating multi-media fugacity models based on physicochemical principles or data-based machine learning models to quantitatively simulate and predict the flux and fate of pollutants in the atmospheric deposition-water migration-sediment adsorption / release process, as well as collaborative early warning and source tracing analysis: it establishes a three-phase index association rule library, automatically correlates and analyzes data from other media when an anomaly occurs in a certain medium, provides collaborative early warning, and assists in pollution source tracing. The visual interactive interface enables three-dimensional visualization and decision support, providing a three-dimensional dynamic view of the spatiotemporal distribution of pollutant concentrations, flux heat maps, migration path simulation animations, and generating comprehensive monitoring and evaluation reports.

10. The monitoring method of the in-situ collaborative monitoring system for multi-media environmental pollution in rivers and lakes as described in any one of claims 1-9, characterized in that, Includes the following steps: Step 1: System Deployment and Initialization: Deploy the monitoring system to the target river or lake area, stabilize it at the preset monitoring point by anchoring or dynamic positioning, start the system, perform self-testing and calibration of each sensor, and establish a communication link between the edge computing unit and the cloud platform. Step 2: Synchronous acquisition of three-phase in-situ data: The system synchronously triggers the atmospheric interface environmental monitoring unit, the aqueous interface environmental monitoring unit, and the sediment interface environmental monitoring unit at a preset frequency to collect the physicochemical indicators and pollutant concentration data of the three-phase interfaces. All data are labeled with the synchronous monitoring time and location. Step 3: Data preprocessing and preliminary fusion: The edge computing unit performs quality control on the raw data and performs preliminary data fusion based on a preset algorithm; Step 4: Remote data transmission and cloud storage: The pre-processed and initially fused data packets are transmitted to a remote cloud platform via wireless network and stored in the spatiotemporal database; Step 5: Cloud-based intelligent collaborative analysis and modeling: The cloud platform calls the multi-media migration and transformation model to perform deep correlation analysis on the three-phase data, specifically including: calculating atmospheric dry and wet deposition flux, water-air interface gas exchange flux, and mud-water interface pollutant diffusion / release flux; using the model to identify the main sources of pollutants and key migration paths; and training or optimizing the prediction model based on historical and real-time data to predict the development of pollution trends. Step 6: Results Visualization, Early Warning and Report Generation: The analysis results are dynamically displayed in the visualization interface in the form of charts and 3D animations. When the monitored value or the model prediction value exceeds the preset threshold, multi-level early warnings are triggered, and a comprehensive monitoring report covering three-phase status, flux calculation and risk assessment is automatically generated on a regular basis.

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