137 results about "Environmental analysis" patented technology

The invention discloses an urban ventilation corridor construction method based on local climate region classification and remote sensing inversion, and belongs to the technical field of urban climate regulation and space optimization. According to the method, a multi-scale urban thermal environment analysis framework is constructed, a coupling mechanism of an urban form and a thermal effect is systematically identified from macroscopic, mesoscopic and microscopic levels, and fine modeling and regulation and control path identification of the thermal environment are realized. Meanwhile, in combination with machine learning and interpretability analysis methods, scientificity and transparency of thermal environment driving factor identification are enhanced. Through combination of remote sensing inversion, morphological factor construction and three-dimensional analogue simulation, a complete technical path of cold source identification, resistance modeling, path optimization and microclimate response evaluation is provided, and the aeration-cooling potential identification capability of blue-green infrastructures is effectively improved. The method is suitable for wind gallery planning and climate adaptation type update design of various urban spaces, and has wide popularization and application prospects.

The invention provides a Yangtze river export deep and far sea environment data association analysis method based on multi-modal fusion, belongs to the technical field of far sea environment analysis, and achieves accurate data registration by establishing a multi-source data space-time standardization model and adopting an adaptive space-time Kriging interpolation algorithm. A sparse coding ocean signal separation algorithm is utilized to construct an over-complete dictionary separation mixed signal to extract pure features, a feature extraction network is constructed based on an attention mechanism to automatically learn deep feature representation of physicochemical biological parameters, and a matrix rank loss detection algorithm is adopted to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism is constructed based on wavelet transform to fuse multi-scale features, a Shapley value interpretability evaluation system is established to quantify correlation feature importance, and the technical problem that correlation feature extraction is inaccurate in the multi-source heterogeneous marine environment data fusion process is solved.

A system and method for contextual three-dimensional messaging in augmented reality (AR) environments is disclosed. The system receives chat messages with specified real-world destinations and stores them associated with those locations. When a user wearing an AR device enters a destination location, the system detects their presence using techniques like GPS, Wi-Fi positioning, or computer vision. It then generates a 3D visual representation of the message and determines an appropriate spatial position within the physical environment based on environmental analysis and object detection. The 3D message is displayed at the determined position in the AR view. The system can analyze message content to identify topics and match them to detected real-world objects for contextual placement. Users can interact with displayed messages through gestures or voice commands to reply, forward, delete, or reposition messages. This enables immersive, location-aware messaging experiences that seamlessly blend digital content with the physical world.

The invention discloses a rapid diagnosis method for blueberry continuous cropping soil obstacle factors, and belongs to the technical field of soil environment analysis. Based on combined analysis of soil physical and chemical factors, metagenome and metabolome, pathogenic bacteria types and key metabolites significantly related to the blueberry continuous cropping obstacle are extracted, and a characteristic diagnostic index system is formed. The index system comprises main pathogenic bacteria types, typical harmful metabolites, key soil physical and chemical factors and appropriate or risk threshold ranges thereof, and provides a scientific basis for rapid identification of soil continuous cropping obstacles. Comparative analysis is carried out by establishing a standardized index library, rapid comparison of related indexes and standard indexes in a newly sampled soil sample is realized, and whether the soil has continuous cropping obstacle risks or not is judged in an auxiliary manner by integrating the deviation degree of physical and chemical factors and biological factors.

The invention discloses an ultratrace mercury isotope analysis method, and relates to the technical field of environmental analysis. The method comprises the following steps: purging a liquid sample to be detected by nitrogen in a stannous chloride atmosphere, and trapping and concentrating mercury into a gold trapping tube; pyrolyzing the pyrolytic gold trapping tube to release mercury vapor; pyrolytic mercury vapor and thallium isotope internal standard aerosol are mixed to serve as a sample injection sample, and the sample injection sample is introduced into a multi-receiver inductively coupled plasma mass spectrometry; acquiring a mercury instantaneous signal and a thallium isotope signal; and calculating the mercury isotope ratio by adopting least square linear regression fitting in combination with a thallium internal standard ratio correction algorithm. According to the method, the instantaneous mercury isotope signal is generated by online combination of gold trapping and multi-receiver inductively coupled plasma mass spectrometry, the instantaneous signal is strategically collected and processed, the determination concentration of isotope analysis can be greatly reduced, the sensitivity of the method is remarkably improved, and direct determination of mercury isotope composition in a water sample with the concentration of 10 ng L <-1 > is met.

The invention discloses a forest tree planting environment analysis and optimization method based on big data, and relates to the field of forest tree planting, and the method comprises the steps: obtaining high-resolution vegetation index data of a target region for continuous N years; eliminating fluctuation interference of clouds and seasons of the high-resolution vegetation index data to construct a pixel-by-pixel vegetation growth track; obtaining artificial forest tending data, meteorological observation data and topographic data of the target area for continuous N years; according to the pixel-by-pixel vegetation growth track, the artificial forest tending data, the meteorological observation data and the topographic data, carrying out region attribute division to obtain a region division result; and optimizing forest planting strategies corresponding to the fluctuation area and the degradation area in the area division result in combination with artificial forest tending data. According to the method, the problems of unstable remote sensing data, insufficient adaptive modeling, extensive optimization strategy and the like in the prior art are solved, and the method has remarkable ecological value and application prospect.

The invention relates to the field of environmental analysis, and provides a gas hydrate three-phase coexistence region modeling method and system. The method comprises the following steps: acquiring three-dimensional seismic data and original logging data, and preprocessing the original logging data to obtain corrected logging data; respectively performing logging interpretation and structural interpretation according to the corrected logging data and the three-dimensional seismic data to obtain interpretation results; converting a structure interpretation result in the interpretation results into a three-dimensional geological structure model, and performing grid division on the research area by adopting a corner grid system to obtain a structure grid model; and performing attribute modeling on the constructed grid model based on variation function analysis, and predicting porosity and saturation in a three-dimensional space through a Kriging interpolation algorithm to obtain a three-phase coexistence region model. According to the method, the influence of complex geological conditions on the accuracy of the model is reduced, and the precision of the three-phase coexistence region model is remarkably improved.

The invention discloses a forest fire intelligent monitoring and early warning method and system based on a multi-modal large model, and the method comprises the steps: carrying out the fire recognition and environment analysis based on a multi-modal data fusion mechanism of the multi-modal large model in combination with multi-source data collected by an unmanned plane; an auxiliary early warning solution is automatically generated for the fire by combining a multi-modal model with a forest ranger inspection report, an unmanned aerial vehicle inspection video and a fire analysis result, and emergency processing suggestions are provided; massive multi-source heterogeneous data in the forest fire intelligent monitoring and early warning system is efficiently stored, managed and retrieved, the distributed training and reasoning process of a multi-modal large model is optimized, and it is ensured that the system can achieve rapid and accurate fire monitoring and early warning in a complex natural environment. According to the invention, full-process automatic management and comprehensive analysis from data acquisition, fire monitoring to analysis and decision making are realized, and problems of insufficient intelligent identification capability, high false alarm rate and low data integration analysis efficiency in the existing forest fire monitoring and early warning process are solved.

A system and method for managing autonomous aerial vehicle ingress and payload exchange is disclosed. A beacon unit receives a digitally encoded ingress request from an autonomous aerial vehicle, the request comprising an identity token. A smart contract engine evaluates the identity token against mission-specific conditions to authorize ingress. An environmental analysis processor generates a map of the region surrounding the beacon unit using data from multiple sensor modules, including LiDAR, radar, infrared, audio, and weather sensors. A trajectory guidance engine computes an ingress path based on the environmental map. A virtual protected area generation module defines a three-dimensional protected zone for descent, and a classification engine assigns a safety classification to the zone based on predefined criteria. A beacon control interface transmits the ingress path to the vehicle and monitors descent for compliance. A user authentication subsystem verifies the identity of a human user at the landing zone prior to payload release.

The invention relates to the crossing field of computer vision and biomedical engineering, and discloses a method and a system for sperm kinetic analysis, comprising the following steps: concurrently performing environmental analysis and target detection on a microscope image sequence, generating a mask for identifying the position of an interferent and an index for quantifying scene complexity, positioning sperms by the latter; the core is a self-adaptive trajectory tracking module which receives the two paths of information and performs tracking based on a dual feedback mechanism: on one hand, the correlation cost of a detection result in an interferent mask area is set as a maximum value, so that wrong matching is avoided; and on the other hand, the internal parameters of the tracking model are dynamically adjusted according to the scene complexity index. According to the method, dynamic parameters such as VCL, VSL, ALH and BCF are accurately calculated by generating the robust motion trail, a comprehensive report containing a quantitative result and analysis quality control evaluation is finally output, and the accuracy and credibility of an analysis result are remarkably improved.

The invention discloses a multifunctional dust and bacterial colony detection automatic sampling robot and method, and belongs to the field of environmental monitoring and biological experiment automation equipment.The multifunctional dust and bacterial colony detection automatic sampling robot comprises a trolley, a rotating holder, a supporting frame, double supporting plates, a double limiting structure and a mechanical claw clamping system; the arc-shaped piece of the first limiting structure abuts against the box, the air cushion and the top block of the second limiting structure fix the culture dish, and mechanical claw clamping is matched to replace suction cup type grabbing, so that stability is improved; a bacterial colony detection culture dish and a dust fall detection culture dish are respectively borne by double supporting plates, and stations are switched by combining a rotary holder, so that dust fall and bacterial colony double-object sampling is realized; the rotation angle of the supporting plate is dynamically adjusted along with the number of culture dishes to support fixed-point interval detection; the method comprises the steps of installation adjustment, automatic detection, fixed-point continuous detection and processing ending. The device is suitable for culture dishes of different specifications, the automation degree is high, bacterial colonies and dust falling dynamic states can be carefully captured, and data support is provided for multi-dimensional environment analysis.

The invention relates to the technical field of environmental analysis and testing, and discloses a method for detecting perfluorinated compounds in soil, which comprises the following steps: (1) crushing and sieving a soil sample to be detected, then carrying out pressurized fluid extraction, carrying out rotary evaporation concentration on the obtained extract, and dissolving with methanol again to obtain a concentrated solution; (2) purifying the concentrated solution through a solid-phase extraction column, and then concentrating to a constant volume to obtain a to-be-detected solution; (3) detecting the type and the content of the perfluorinated compounds in the to-be-detected liquid by adopting a liquid chromatography-tandem mass spectrometry method; wherein in the step (1), an extracting solvent is a NaOH methanol solution; in the step (3), in the liquid chromatography-tandem mass spectrometry, the liquid chromatographic condition is as follows: a liquid chromatographic column is a C18 chromatographic column. The detection method provided by the invention is simple to operate, high in accuracy, good in repeatability, capable of analyzing multiple PFAS types (17 types) and low in detection limit, meets the analysis requirements, and can be used for analyzing and monitoring common PFAS in soil.

The invention relates to the technical field of power transmission line meteorological environment analysis, in particular to a power transmission line wind speed correction method and system based on terrain parameters, and constructs a set of systematized and computable power transmission line wind speed correction process with high engineering practicability. The problem that in the prior art, wind speed correction is difficult to achieve rapidly and systematically between complex terrains is effectively solved. Through progressive analysis of terrain space data preprocessing, terrain feature vector construction and terrain type recognition, an abstract terrain form is converted into a quantifiable parameter system, and a data foundation is laid for accurate modeling; and through the core steps of wind speed acceleration ratio model construction and standard wind speed model coupling, computable expression of wind speed field terrain influence is realized, a three-dimensional correction result better conforming to actual wind field physical characteristics is generated, and data availability and engineering efficiency are significantly improved.

The invention discloses a method for enriching and extracting free glutamic acid from an environmental water body and / or sediment. The method combines freeze drying, mechanical grinding, chemical extraction, cation exchange resin purification and low-temperature concentration. According to the method, the extraction efficiency, the yield and the purity of the free glutamic acid can be remarkably improved, sample background interference and glutamic acid degradation are avoided, and glutamic acid can be separated from other amino acids possibly existing in a sample, so that the purpose of enrichment extraction is achieved. Meanwhile, the method is easy and convenient to operate, efficient in extraction, capable of being used for on-site rapid treatment, wide in raw material source, low in cost and wide in application prospect in the field of environment analysis and ecological monitoring.

The invention belongs to the technical field of environmental analytical chemistry, and particularly relates to a separation and purification and high-throughput target quantitative analysis method for multiple types of environmental pollutants in a complex matrix biological sample. The method comprises the following specific steps: S1, carrying out ultrasonic extraction on a biological sample to obtain an extracting solution; s2, performing dispersive solid-phase extraction and purification treatment on the extracting solution to obtain a solution to be detected; s3, determining the environmental pollutants in the liquid to be detected by adopting a selected ion scanning mode of the gas chromatograph-mass spectrometer. The pretreatment method disclosed by the invention can effectively reduce complex matrix interference of the biological sample, and can quickly and efficiently perform high-throughput target analysis on multiple types of environmental pollutants in the biological sample; the method disclosed by the invention is low in detection limit and capable of realizing trace detection of a biological sample; the invention provides a new method for researching the occurrence condition of the environmental pollutants in the 17 marine organisms in Liaoning Bay, and has important significance for the progress of environmental science.

This invention provides a multimodal fusion-based method for correlation analysis of deep-sea environmental data outside the Yangtze River Estuary, belonging to the field of deep-sea environmental analysis technology. This invention achieves accurate data registration by establishing a spatiotemporal standardization model for multi-source data and employing an adaptive spatiotemporal kriging interpolation algorithm. It utilizes a sparse coding marine signal separation algorithm to construct an overcomplete dictionary to separate mixed signals and extract pure features. Based on an attention mechanism, a feature extraction network is constructed to automatically learn deep feature representations of physical, chemical, and biological parameters. A matrix rank deficiency detection algorithm is used to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism based on wavelet transform is constructed to fuse multi-scale features. A Shapley value interpretability evaluation system is established to quantify the importance of correlated features. This invention solves the technical problem of inaccurate correlated feature extraction during the fusion of multi-source heterogeneous marine environmental data.

The application provides a power generation loss analysis method and system for a photovoltaic power station, and relates to the technical field of photovoltaic technology. The method comprises the following steps: collecting current time information through an environment analysis station, and identifying an obtained shading loss coefficient; collecting a meteorological data sequence in a future preset time range through a meteorological analysis station, performing power generation loss identification and dust influence parameter analysis, obtaining a meteorological loss coefficient and a dust influence parameter; collecting a plurality of dust parameters of all photovoltaic panels or part of the photovoltaic panels in the target power station through a dust analysis station, combining the dust influence parameter, calculating and obtaining a dust parameter array, constructing a dust distribution fitting image, performing cascade image generation analysis, obtaining a dust loss coefficient of the target power station, and combining the shading loss coefficient and the meteorological loss coefficient to calculate and obtain a power generation loss coefficient and a power generation loss amount. The application solves the technical problems of incomplete and inaccurate calculation and analysis of the power generation loss amount of the photovoltaic power station in the prior art.

The method for constructing urban ventilation corridors based on local climate zone classification and remote sensing inversion belongs to the technical field of urban climate regulation and space optimization. The present application constructs a multi-scale urban thermal environment analysis framework, from macro, meso to micro level, to identify the coupling mechanism of urban form and thermal effect, and to realize the fine modeling and regulation path identification of thermal environment. At the same time, combined with machine learning and explainable analysis method, the scientificity and transparency of thermal environment driving factor identification are enhanced. Through remote sensing inversion, form factor construction and three-dimensional simulation simulation, a complete technical path of "cold source identification-resistance modeling-path optimization-microclimate response evaluation" is put forward, which effectively improves the ventilation and cooling potential identification ability of blue-green infrastructure, and is suitable for ventilation corridor planning and climate adaptive updating design of various urban spaces, and has wide application prospect.

This application provides an iron-based thin-film probe, an in-situ analysis method for soil micro-interface pollutants, a screening method for iron-based materials for soil remediation, and a soil remediation method, belonging to the field of environmental analysis and testing technology. The iron-based thin-film probe, used to study the role of iron-containing mineral micro-interface pollutants in soil, is prepared from an iron sheet through in-situ surface modification; wherein the modified surface formed by the in-situ surface modification is selected from any one of nano-zero-valent iron, iron oxide, and iron sulfide; the iron-based thin-film probe is used to simulate the adsorption, distribution, and redox reactions of iron-containing mineral micro-interface pollutants in soil.

The application discloses a kind of distributed intelligent well logging system and well logging method, it is related to intelligent well logging technical field, the system of the present application includes winch control module, environmental analysis module, tension analysis module, component control module and safety warning module, the present application first winch control module gathers in-well basic data, sets up winch basic control scheme;Second, environmental data are analyzed by environmental analysis module, and the winch correction control scheme is obtained;Tension analysis module sets up the control scheme of rope according to the analysis of rope tension data;Component control module analyzes distributed component measurement data, and sets up component sensor control scheme;Finally, through safety warning module, the above scheme analysis control change data and early warning, each module specific analysis and scheme setting process involves a variety of data analysis, for accurately controlling winch and component operation, improve well logging safety and accuracy.

The present application relates to the field of environmental analysis, in particular to a forest litter decomposition rate estimation method, system, device and storage medium. The present application aims at the problems of long cycle, great environmental influence, time-consuming and laborious of the existing nylon mesh bag method for determining the forest litter decomposition rate, and the problem of being unable to carry out decomposition research on large-scale forests, and provides a forest litter decomposition rate estimation method, system, device and storage medium, measures and calculates the current year input of the forest litter p and the annual input increment, determines the residual rate constant r of the forest litter through experimental method or searching for relevant data in the past, and combines the residual rate constant r with the OLson single index decomposition model of the forest litter to establish a solution equation of the forest litter decomposition rate. This method has short cycle, does not need to be measured in the field regularly and frequently, has small environmental influence, the parameters and variables in the equation are easy to obtain, time and labor are saved, and decomposition rate research can be carried out on large-scale forests.

This invention discloses a method and system for environmental performance verification and supervision of green procurement, relating to the field of environmental data analysis technology. The method and system include: S1, collecting and preprocessing environmental behavior data, node characteristic data, and structural difference data during the environmental performance verification process to construct a standardized verification status dataset; S2, performing environmental analysis on the environmental performance of the verification process and dynamically adjusting equipment operating intensity; S3, evaluating the status of the logs during the verification process and correcting the node field writing method and record density; and S4, conducting a consistency evaluation of the consistency of parallel verification results across nodes and real-time adjusting the node record link and batch processing flow. This solves the problems of insufficient reliability of environmental emission reductions caused by the inability to trace back the calculation link, the unverifiable calculation process, and the difficulty in maintaining consistency of verification results across nodes in multi-parameter environmental performance accounting.

The invention belongs to the technical field of deep learning and geophysical exploration, and relates to a ground penetrating radar underground water content detection data inversion method based on a U-Net neural network, which comprises the steps of model construction, data simulation and processing, time-depth conversion and propagation time calculation, data and model alignment, water content prediction and network structure inversion. According to the ground penetrating radar data nonlinear inversion method based on the U-Net deep neural network, accurate prediction of the underground water content is successfully realized; according to the method, through high-simulation electromagnetic wave propagation simulation, strict data preprocessing and fine model structure design and training configuration, the limitation of a traditional method in complex nonlinear underground environment analysis is effectively overcome; experimental results show that the method has high prediction precision and stability and is suitable for wide engineering application; in future research, more complex geological models and application of real scene data are explored, and the practicability and generalization performance of the models are further improved.

This utility model discloses an automated sampling robot for dust and bacterial colony detection, belonging to the field of automated equipment for environmental monitoring and biological experiments. It includes a cart, a rotating gimbal, a support frame, double support plates, a double limiting structure, and a mechanical gripper clamping system. The first limiting structure uses an arc-shaped plate to press against the box, while the second limiting structure uses an air cushion and a top block to fix the culture dish. The mechanical gripper replaces suction cup gripping, improving stability. The double support plates respectively carry the culture dishes for bacterial and dust detection, and the rotating gimbal allows for switching between workstations, enabling dual sampling of dust and bacteria. The rotation angle of the support plates dynamically adjusts according to the number of culture dishes, supporting fixed-point interval detection. This utility model is adaptable to culture dishes of different sizes, has a high degree of automation, and can precisely capture the dynamics of bacterial and dust colonies, providing data support for multi-dimensional environmental analysis.

The present application relates to the technical field of marine ecological environment analysis, and discloses a marine ecological environment analysis method and system based on big data, which comprises the following steps: obtaining environment monitoring and management object working condition time series data, determining a transmission lag time window based on flow field transmission logic; calculating cross-correlation coefficients in the window, and if they fall into a gray verification interval, generating a pseudo-random working condition control sequence orthogonal to the background main frequency; driving the management object to perform irregular actions through an administrative interface, calculating the local waveform matching degree of the environment data and the sequence; and determining responsibility and generating a punishment instruction when the threshold is exceeded. The system comprises a data acquisition and space-time mapping module, a cross-correlation calculation module, an active attribution module, and a fingerprint verification and decision module. Through the active pseudo-random disturbance and frequency domain orthogonal verification mechanism, the present application realizes exclusive locking of the responsible subject under complex hydrological environment, and solves the attribution problem that passive monitoring is difficult to distinguish between natural background fluctuations and human emissions.

The invention belongs to the technical field of environmental analysis instruments and intelligent detection, and discloses a water sample micro-plastic detection device based on fluorescent staining and an AI algorithm, an integrated micro-fluidic chip is adopted to replace a traditional pretreatment process, and online digestion and fluorescence labeling of a water sample are automatically completed through a sequential injection analysis flow path; the configured high-sensitivity fluorescence imaging module can capture feature images of the micro-plastics; a built-in lightweight multi-scale feature fusion network model can identify and count micro-plastic targets, output quantity, particle size distribution and morphological parameters in real time. According to the invention, full-process automation from sample input to result output is realized, the problems of tedious pretreatment, high manual dependency and difficulty in on-site rapid quantification in the prior art are solved, and an efficient technical means is provided for water environment micro-plastic pollution monitoring.

The invention discloses an automatic rapping control method and system of an electric dust remover, and relates to the technical field of temperature control. The method comprises the following steps: acquiring equipment dust deposition data; presetting a dust deposition threshold value, and comparing the equipment dust deposition data with the dust deposition threshold value; if the equipment dust deposition data is greater than the dust deposition threshold value, analyzing the equipment dust deposition data, and obtaining equipment dust deposition analysis data; acquiring the environment dust content in the predetermined area, and constructing an environment analysis unit according to the equipment dust deposition analysis data and the environment dust content; constructing an equipment analysis unit according to the equipment state of the target electric precipitator; constructing a rapping strategy model according to an environment analysis unit and the equipment analysis unit; and generating a first rapping strategy based on the rapping strategy model, and controlling the target electric dust remover to automatically rap according to the first rapping strategy. The technical problem that in the prior art, vibration is conducted according to fixed time, equipment loss is serious, and the dust removal effect is poor is solved, and the technical effect of improving the dust removal effect is achieved.

The present disclosure relates to an environmental analysis system (200) for vehicles (10), comprising: - a vehicle-side environmental sensor system (12, 210) configured to detect a floor area in a vehicle environment and to provide corresponding detection data; - a vehicle-side condition determination module (220) configured to determine a moisture level for the ground area based on the detection data; - a vehicle-side friction coefficient determination module (230) configured to determine a friction coefficient for the ground area; and - a vehicle-side communication module (240) configured to transmit soil information (BI) relating to the moisture level and the friction coefficient to a central unit (250) for creating and / or updating a friction coefficient map with road segments (SEG1, SEG2) of the same or similar roadway properties.

The application provides a lake dissolved organic matter quantitative tracing method based on molecular fingerprint and application thereof, and relates to the technical field of environmental analysis and water ecological management. The method comprises the following steps: collecting end member samples such as lake water and sediments, surface soil, plant litter, chemical fertilizer, livestock and poultry manure, tail water of a sewage treatment plant, tail water of aquaculture, etc., and enriching DOM through solid phase extraction; then obtaining molecular formula data through mass spectrometry; screening stubborn inert molecules that satisfy H / C < 1.5, conversion times of 0 and exist only in a single end member, and verifying the ecological conservation thereof through -2 < betaNTI < 2 and -0.95 < RCBray < 0.95; adopting SHAP algorithm to optimize a high-contribution molecular feature subset, and inputting the high-contribution molecular feature subset into a MixSIAR model to output the contribution proportion of each end member and the 95% confidence interval. The method guarantees the reliability of the tracer from the mechanism, breaks through the bottleneck of spectral overlap, and realizes accurate and reliable quantitative disassembly of endogenous and exogenous DOM.

The invention provides a method for determining the redox potential of soluble black carbon, and belongs to the technical field of environmental analysis. The method comprises the following steps: reducing the soluble black carbon by quinone reducing bacteria under an anaerobic condition, sterilizing, adding ferrihydrite, reacting the reduced soluble black carbon with ferrihydrite, measuring the total amount of generated Fe (II), and calculating the redox potential of the soluble black carbon by taking the electronic equivalent of a standard substance AQDS as a reference. According to the method, the electron transfer of the soluble black carbon in the natural environment is simulated by adopting the microbial reduction process, the result is closer to the real environment, the operation is simple and convenient, the repeatability is good, and the method is suitable for evaluating the electron shuttling capability of the soluble black carbon in the environment.