129 results about "Soil Pollutants" patented technology

The embodiment of the invention discloses a causal relationship-based soil pollution tracing method, equipment and medium, and the method comprises the steps: obtaining the soil pollutant concentration detection data of a to-be-traced region, and the data of two emission sources of enterprises and traffic; performing positive matrix factorization on the detection data, and determining contribution of each hidden pollution source to each pollutant; determining at least one pollutant which is contributed by each hidden pollution source and is associated with the enterprise and / or traffic as at least one target pollutant to be traced; aiming at each type of target pollutants, through emission list spatialization and GCCM causal analysis, the causal relationship and the significance degree of the enterprise and the traffic and the target pollutants are verified respectively; and according to a verification result, carrying out auxiliary decision on the preferentially controlled blocks in the region and the types of pollutants and emission sources preferentially controlled by each block. According to the embodiment of the invention, accurate tracing of soil pollution in a complex environment can be realized.

The invention relates to the technical field of soil monitoring, and discloses a power transmission and transformation project soil pollutant monitoring method and system, and the method comprises the steps: collecting hyperspectral image data in a power transmission and transformation project region; processing the hyperspectral image data by adopting a multi-stage spectrum transformation mechanism to obtain a characteristic wave band representing the pollutant content; inputting the characteristic wave band into a preset spectrum inversion model to generate a concentration spatial distribution diagram of the soil pollutants; and constructing a soil and groundwater diffusion model according to the concentration spatial distribution map, and generating a migration path identification map of soil pollutants and an underground pollution risk area identification map based on the soil and groundwater diffusion model. The method has the beneficial effect of improving pollution identification precision and migration prediction accuracy.

The invention provides an agricultural non-point source load simulation calculation method, and relates to the field of agricultural non-point source pollution calculation, and the method comprises the steps: constructing an agricultural non-point source load calculation model, reading surface runoff time sequence data of each hydrological response unit in a drainage basin, and setting corresponding model parameters; setting a time step length, sequentially calculating the thickness of soil capable of being scoured in the current time step length, the amount of pollutants capable of being scoured in unit area and the amount of pollutants actually scoured in unit area by utilizing surface runoff time sequence data and model parameters, and finally obtaining the updating amount of the concentration of the soil pollutants in the current time step length. All hydrological response units are respectively subjected to the above calculation in the simulation time period to obtain a time sequence of the soil pollutant concentration updating amount, and the agricultural non-point source load of the drainage basin in the simulation time period is calculated in combination with the surface runoff time sequence data. According to the method, the natural process in the agricultural non-point source scouring process is fused into the model, and the obtained agricultural non-point source load is more accurate and more interpretable.

The invention relates to the technical field of environmental protection and pollution control, in particular to a soil pollutant on-line monitoring and risk assessment method and system.The method comprises the steps that soil pollutant monitoring areas are divided, and high-precision sensors are deployed, so that the accuracy and reliability of monitoring data are improved; the fluctuation condition of the pollutant concentration is calculated and analyzed according to historical data, a reasonable sampling frequency is determined, and the concentration change can be better captured; by establishing a composite risk assessment function, the risk level of a sampling point is assessed more comprehensively and accurately; the prevention and control measure intensity and range corresponding to the sampling point are dynamically adjusted according to the change of the composite risk assessment value, and the timeliness and effectiveness of prevention and control work are ensured. The method is used for solving the technical problems of low monitoring efficiency, poor risk assessment and lack of pertinence of prevention and control measures caused by no online monitoring of the pollutant concentration in soil and no quantitative assessment of the soil pollution risk in the existing scheme.

The invention provides a soil pollutant detection system and method, and the method comprises the steps: carrying out the continuous spectrum compensation of a target compensation region of a soil Raman spectrum signal of a to-be-detected soil sample, and obtaining soil Raman spectrum compensation data; identifying a background baseline response interval in the soil Raman spectrum compensation data through iterative differential analysis, and segmenting the soil Raman spectrum compensation data into a plurality of peak-containing spectrum segments according to the background baseline response interval; determining a signal fidelity constraint of the soil Raman spectrum signal during smooth iteration; recognizing a local background baseline corresponding to each peak-containing spectrum section based on an incremental smooth window in combination with signal fidelity constraint, and determining a clean characteristic spectrum according to all background baseline response intervals and the local background baselines; and identifying according to the clean characteristic spectrum to obtain the pollutant concentration of the to-be-detected soil sample. According to the technical scheme provided by the invention, adaptive fidelity extraction can be carried out on the pollutant characteristics under the condition of the violently changing background base line.

The invention relates to the technical field of soil pollutant migration and early warning, and particularly discloses a geophysical soil pollutant migration and early warning simulation method, which comprises the steps of S1, mounting a geophysical detection equipment component, S2, data acquisition, S3, data processing and S4, data imaging. The induction electromagnetic method is generally used for rapid exploration investigation, stratum conductivity distribution is rapidly obtained, a conductivity abnormal area is found out, and help is provided for subsequent geophysical method construction. The ground penetrating radar is mainly suitable for stratums, underground pipeline positions, underground storage tank positions, shallow waste burying thickness and distribution, underground tank leakage, shallow DNAPL / LNAPL pollution and heavy metal pollution. In an underground pollution survey project, a ground penetrating radar method is mainly used for finding out positions of underground metal, pipelines and electromagnetic wave attenuation, measuring line arrangement and construction are facilitated through a high-density electrical method, and the application range of the high-density electrical method comprises hydrogeological detection, large underground structure detection, underground groove leakage detection and the like.

The invention discloses a data analysis method for monitoring soil pollution spatial distribution based on image fusion. The method comprises the following steps: step 1, collecting soil pollution monitoring data; 2, preprocessing the soil pollution monitoring data; step 3, performing image fusion calibration; step 4, extracting soil pollutant characteristics; 5, generating a soil health index; and step 6, monitoring the soil environment. Compared with the prior art, the soil pollution monitoring method has the advantages that all-directional monitoring of soil pollution is achieved through the image fusion technology, the limitation of a traditional monitoring method is broken through, the spatial distribution characteristics of pollutants can be comprehensively reflected, and the soil pollution monitoring range and accuracy are effectively improved.

The invention belongs to the technical field of environmental treatment, and particularly relates to a combined treatment method for polluted soil and carbon emission reduction and a system utilizing the combined treatment method. The polluted soil and carbon emission reduction combined treatment method provided by the invention comprises the following steps: sequentially filling a reaction tower with a mixture of polluted soil, calcium peroxide and slag, a first mixture of the polluted soil and the calcium peroxide and a second mixture of the polluted soil and the calcium peroxide from bottom to top; the reaction tower filled with the filler is obtained; the content of calcium peroxide in the second mixture is higher than that of the first mixture; activating the filler in the reaction tower filled with the filler so as to decompose organic pollutants in the polluted soil, and then introducing waste gas containing carbon dioxide to perform carbon immobilization, so as to respectively obtain purified soil and purified waste gas; the activating treatment mode comprises the step of introducing steam into the reaction tower. The synergistic interaction of soil pollutant removal and carbon immobilization is achieved, industrial waste heat and waste are fully utilized, and the resource utilization rate is increased.

The invention relates to the technical field of soil pollution monitoring, in particular to a soil pollutant detection and evaluation method and system based on high-density resistivity. The method comprises the following steps: acquiring soil information data; performing soil uniformity analysis on the soil information data to generate soil uniformity data; performing electrode arrangement mode selection based on the soil uniformity data to generate soil electrode arrangement mode data; performing soil resistivity data acquisition according to the soil electrode arrangement mode data to obtain soil resistivity data; performing resistivity inversion on the soil resistivity data to generate a soil resistivity distribution diagram; and performing resistivity anomaly identification on the soil resistivity distribution map to generate abnormal resistivity identification data. By optimizing soil uniformity analysis, electrode arrangement, resistivity inversion and pollutant diffusion analysis, the accuracy in the soil pollutant detection and evaluation process is improved.

The invention relates to a simulation monitoring device and method for a frozen soil change process. The simulation monitoring device comprises a constant temperature box, an image shooting device, a light source, an objective table, a frozen soil structure simulation device and a temperature control device are arranged in the constant temperature box, the light source is arranged opposite to the image shooting device, the frozen soil structure simulation device and the temperature control device are arranged on the objective table, and an image processing device is arranged outside the constant temperature box. The frozen soil structure simulation device is used for simulating soil pore structure characteristics by arranging a plurality of convex parts and arranging coating layers on the convex parts, and constructing a high-simulation natural soil simulation environment, pore characteristics of natural soil in a high-reduction freeze-thaw environment and a migration environment of soil pollutants. The simulation monitoring method realizes simulation and monitoring of the migration behavior of the micro-plastic particles in the soil, has excellent simulation performance and extremely high experimental precision, and is of great significance to evaluation and treatment of pollution site environmental problems in widely distributed cold regions.

The invention relates to the technical field of pollutant monitoring, in particular to a monitoring method for soil pollutants in a mine remediation area. Comprising the following steps: acquiring a soil sample, detecting the soil sample by adopting a pollutant monitoring technology to obtain pollutant data, preprocessing the pollutant data, and intelligently processing the preprocessed pollutant data by utilizing a self-adaptive multi-dimensional nonlinear pollutant fusion algorithm to obtain comprehensive pollutant data; constructing a pollution prediction model, and performing prediction analysis on the comprehensive pollutant data by using the pollution prediction model to obtain a layered prediction result; and performing risk assessment on the pollutants based on the comprehensive pollutant data to obtain a comprehensive risk assessment value, further obtaining a comprehensive risk assessment result, and making a coping strategy based on the hierarchical prediction result and the comprehensive risk assessment result. The technical problems of insufficient pollution data processing precision and inaccurate risk assessment are solved.

The invention discloses a regional soil pollution cause mode analysis method, belongs to the technical field of soil pollution analysis, and can solve the problem that an existing analysis method can only quantify or determine the current situation of soil pollutants singly and cannot quantify or determine the intermediate pollution process of soil pollution. The method comprises the following steps: S1, carrying out grid division on a research area, obtaining soil pollution data and potential pollution sources of each grid area, and determining a pollution mode of each grid area according to the soil pollution data; s2, training the machine learning model by using the soil pollution data, the potential pollution sources and the pollution modes of all the grid regions to obtain a pollution source prediction model; and S3, according to the soil pollution data of the to-be-detected area, predicting a pollution source of the to-be-detected area by using the pollution source prediction model to obtain a pollution source prediction result of the to-be-detected area. The method is used for analyzing the soil pollution cause mode.

The invention provides a soil pollutant intelligent detection method and system. The method comprises the following steps: removing soil matter creation conditions in example soil acquisition component data; obtaining soil component attribute data of the influencing soil matters according to the types of the influencing soil matters, and obtaining the influencing soil matters according to the sample soil collection component data, the multiple soil pollutant information sets and the soil component attribute data of the influencing soil matters through a deep learning-based influencing soil matter pollutant detection network. According to the method, regression analysis information about the range of pollutant data in sample soil acquisition component data is obtained, and the soil matter pollutant detection network is optimized according to the difference between the regression analysis information and annotation information, so that the trained soil matter pollutant detection network can be used for detecting soil matter pollutants in the sample soil acquisition component data. The method has the capability of detecting the matters influencing the soil based on the multi-dimensional information, and the pollutant data can be accurately detected by the pollutant detection network influencing the soil matters.

The invention relates to the technical field of environment monitoring and intelligent sensors, and particularly discloses a soil pollutant detection and analysis system based on an intelligent sensor. The system comprises a sensor array module, a data preprocessing and fusion module, an ecological toxicity dynamic evaluation module and a decision output module. According to the invention, the biological response sensing unit capable of directly reflecting the ecological effect is integrated, and the ecological toxicity dynamic evaluation model fusing the concentration, the biological response and the environmental factors is innovatively constructed, so that direct and dynamic quantification from the pollutant content to the ecological risk is realized. According to the method, the problem that an existing assessment method is insufficient in biological correlation is solved, the risk assessment result is closer to the real ecological environment effect, and a reliable basis is provided for precise treatment.

The invention discloses a soybean producing area soil combined pollution micro-ecological risk assessment method and system, and belongs to the technical field of agricultural environment monitoring. The method comprises the following steps: acquiring soil pollutant data and microbial community data, calculating a risk entropy, constructing a micro-ecological health index, and respectively obtaining a first result and a second result by utilizing a risk assessment neural network and a comprehensive model combined with principal component analysis, a clustering algorithm and a hunter optimization algorithm; and determining a final risk level and high-risk pollutants after key factor matching and weighted correction mechanism verification. According to the method, the problems of single evaluation dimension, insufficient dynamic adaptability and the like in the prior art are solved, accurate diagnosis and risk early warning of soil combined pollution are realized through multi-source data fusion and multi-method cooperation, the evaluation accuracy and decision-making efficiency are improved, and technical support is provided for soybean producing area soil micro-ecological risk management and control and agricultural sustainable development.

The invention relates to the technical field of soil remediation, and discloses a soil ecological remediation system which comprises a monitoring module, a pretreatment module, a remediation module, an electrochemical module, an improvement module and a vegetation module. The monitoring module is used for collecting soil pollutants and environmental data; the preprocessing module is used for processing soil by using a physical means and transmitting processed data; a composite microbial agent is injected into the remediation module to regulate the soil environment; the electrochemical module collects electric energy and treats pollutants; spraying a composite modifier in the later stage of the improvement module; the vegetation module constructs an artificial vegetation layer, and all the modules are electrically connected to achieve data interaction. Through cooperation of physical treatment, microbial remediation, electrochemical action, vegetation construction and other means, remediation and ecological function recovery of the contaminated soil are achieved.

The invention provides an industrial site soil pollutant concentration prediction method using three-dimensional distribution interpolation, and belongs to the field of soil pollution prediction, and the method comprises the following steps: S1, extracting soil pollution distribution characteristics based on sample point positions and attribute information; s2, measuring the anisotropy of the pollution concentration value in the two directions by estimating the ratio R of the vertical direction gradient to the horizontal direction gradient of the soil pollutant concentration through the soil sample point pollution concentration and a difference method, and multiplying the z value in the original coordinate space by the R by taking the R as an expansion factor to obtain a new vertical coordinate value; s3, expanding the spatial position representation module of the DKNN from a two-dimensional space to a three-dimensional space; s4, selecting a space encoder; and S5, on the basis of the spatial encoder, performing spatial prediction by using a general Kriging equation. According to the method, a GeoAI framework based on deep learning and geoscience knowledge fusion is introduced and expanded, the problem of three-dimensional distribution simulation of industrial site soil pollutants can be solved, and soil pollution can be accurately predicted.

The invention provides a method for extracting perfluorophosphoric acid in soil through coupling of an acid-base extracting agent, and relates to the technical field of soil pollutant extraction. The soil is subjected to alkaline extraction by using alkaline methanol, and then is subjected to acidic extraction by using acidic methanol. Perfluorophosphoric acid in soil tends to be strongly combined with soil organic matters. According to the method disclosed by the invention, the alkaline methanol and the acidic methanol are used for carrying out acid-alkali extractant coupling extraction, so that the perfluorophosphoric acid combined with the organic matter can be more sufficiently released, the extraction rate of the perfluorophosphoric acid is high, the recovery rate of each perfluorophosphoric acid is greater than 60%, and the average recovery rate is 75.7%. Compared with alkaline methanol, acidic methanol and pure methanol as extractants, the acid-base extractant coupling method provided by the invention has the advantages that the comprehensive extraction effect on the perfluorophosphoric acid in the soil is obviously improved, and a powerful guarantee is provided for screening and management and control of the perfluorophosphoric acid in the soil.

The invention provides a method and system for dynamically monitoring soil pollutants based on an unmanned aerial vehicle, and relates to the technical field of soil pollution abatement, and the method comprises the steps: constructing a continuous monitoring network, setting the route weight of each route in the continuous monitoring network in different environments, and collecting the average soil pollutant pollution concentration of each route in the corresponding environment; state judgment is carried out on the collected average soil pollutant pollution concentration of each route in the corresponding environment, and the soil pollutant pollution state of the corresponding area is obtained; based on a visualization technology, carrying out visual rendering on pollution states of soil pollutants in different areas in the continuous monitoring network; and carrying out pollution risk assessment when an abnormal soil pollutant pollution state occurs in the continuous monitoring network, and constructing a soil pollutant pollution diffusion model according to a pollution risk assessment result to obtain a corresponding pollution risk processing scheme.

The utility model discloses a soil pollutant detection device, which comprises a vehicle body and a detection disc arranged in a groove at the bottom of the vehicle body, a second rotating shaft is arranged in the vehicle body, rear driving wheels are arranged at two ends of the second rotating shaft, the soil pollutant detection device is characterized in that a worm is sleeved on the second rotating shaft, a worm gear meshed with the worm is further arranged in the vehicle body, and the worm gear is meshed with the worm. A convex block is arranged on the worm gear; a movable shaft is further arranged in the vehicle body, the movable shaft is sleeved with a connecting rod, the connecting rod is connected with the side wall of the detection disc, strip-shaped openings distributed in the axial direction of the connecting rod are formed in the connecting rod, the protruding blocks are located in the strip-shaped openings, and the turbine is used for driving the connecting rod to swing on the horizontal plane around the movable shaft. The rear driving wheel is used for driving the worm gear and the worm to rotate in the rotating process, so that the connecting rod arranged in the vehicle body is driven to swing in the horizontal direction, the soil detection area of the detection disc is enlarged, and the detection efficiency of soil heavy metal pollutants is improved.

The present invention provides a method for simulating and calculating agricultural non-point source loads, which relates to the field of agricultural non-point source pollution calculation. The method comprises: constructing an agricultural non-point source load calculation model, reading surface runoff time series data of each hydrological response unit in a watershed, and setting corresponding model parameters; setting a time step, and using the surface runoff time series data and the model parameters, sequentially calculating the soil thickness that can be washed within the current time step, the amount of pollutants that can be washed per unit area, and the amount of pollutants actually washed per unit area, ultimately obtaining an updated amount of soil pollutant concentration for the current time step; performing the above calculations for all hydrological response units within a simulation period, obtaining a time series of the updated amount of soil pollutant concentration, and calculating the agricultural non-point source load of the watershed within the simulation period in combination with the surface runoff time series data. The present invention incorporates the natural processes of agricultural non-point source washout into the model, resulting in a more accurate and interpretable agricultural non-point source load.

The invention discloses a method for preparing a soil conditioner for gardenia cultivation by using immobilized compound bacteria, which comprises the following steps: extracting gardenia lignin by using gardenia waste as a raw material, and preparing an inner-layer wall material to embed a mixed bacteria solution to obtain lignin inner-layer microcapsules; preparing an outer-layer wall material through modified chitosan, and compounding and curing the inner-layer microcapsule, the hydrogenated streptomyces liquid and the outer-layer wall material to obtain the immobilized composite microbial agent. And finally, mixing the immobilized complex microbial inoculant with matrixes such as leaf mold and peat soil to obtain the modifier. Ordered release of compound bacteria is realized through dual response, functional synergy of Rafissonia, Ochrobactrum and Streptomyces hydrogenii can be enhanced through population signal molecule modification, soil nutrients can be activated, effective iron can be chelated to solve the problem of iron deficiency yellowing of cape jasmine, soil pollutants and pesticide residues are degraded, and the soil quality is improved. Pathogenic bacteria reproduction is inhibited, and rhizosphere micro-ecological balance is maintained; plant hormones can be secreted to promote the growth of the cape jasmine, and the cape jasmine is converted into more components with high medicinal value.

The invention relates to the technical field of soil detection, in particular to an accurate determination method and system for soil pollutants, a pre-sampling position is determined through a first pre-positioning program, a first sampling program is executed at the pre-sampling position, and if rootstocks exist in the soil at the pre-sampling position, the rootstocks are sampled; the diameter of the rhizome is judged under the action of a first judgment program, if the diameter of the rhizome accords with a first target type, once the rhizome is damaged in the state, juice in the rhizome is easy to leak into a soil sample, so that the accuracy of soil pollutant detection is reduced, and the detection accuracy is improved. In the state that the diameter of the rhizome accords with the first target type, the prediction program is executed to predict the trend of the rhizome, the re-sampling position is determined by predicting the trend of the rhizome, and the second sampling program is executed at the re-sampling position, so that the rhizome is prevented from existing in the re-sampling position, and the quality of the rhizome is improved. Therefore, the juice of the rhizome is prevented from influencing the determination of soil pollutants by a detection program.

The invention discloses a soil pollution in-situ detection device and method.The detection device comprises a control module, a drill rod mechanism, a first detection module, a second detection module and a third detection module, and the control module is connected with the drill rod mechanism, the first detection module, the second detection module and the third detection module; the first detection module, the second detection module and the third detection module are respectively arranged at the bottom of a drill rod body of the drill rod mechanism; the control module is used for calculating a detection interval according to the real-time pH value and the real-time temperature detected by the first detection module and the second detection module respectively in the drilling process, and controlling the third detection module to detect the soil pollutants according to the detection interval. According to the invention, continuous in-situ detection of soil by each detection module is realized, the detection precision is improved, and the problem of detection result deviation caused by separation of an ex-situ detection method from an original state is avoided.

The invention provides a soil pollution accumulation prediction method based on nesting of multiple self-correlation scales, and the method comprises the steps: analyzing a multi-scale nested space structure of soil pollutants through a semi-variation function, determining a block gold effect, an offset abutment value and a range parameter corresponding to each scale, and calculating the contribution degree of the block gold effect, the offset abutment value and the range parameter to overall variation; in combination with original sampling data, identifying main driving factors of pollutant accumulation under different scales, and comprehensively evaluating and sequencing the importance of the factors by adopting various quantitative analysis methods; constructing a cross-scale prediction model set, taking each scale dominant driving factor as an input feature, carrying out modeling by using multiple basic models, screening and optimizing the models through clustering and a multi-objective optimization algorithm, and forming an integrated learning framework of dynamic weight distribution; and carrying out weighted fusion on prediction results according to contribution degrees of all scales, generating a soil pollutant spatial distribution prediction map reflecting multi-scale nested features, and outputting the prediction map through a visual tool, thereby improving prediction precision and spatial interpretation capability.

The utility model relates to the technical field of soil detection and collection, in particular to soil pollutant collection equipment. Comprising a frame body assembly, a sleeve assembly, a driving assembly and a sample pushing assembly, the frame body assembly comprises a collection frame and a positioning nail, the sleeve assembly comprises a positioning sleeve, the driving assembly comprises a sampling barrel and a driving screw rod, the sample pushing assembly comprises a bulldozing rod, connecting rods are connected to the inner wall of the collection frame at equal intervals, and the bulldozing rod is connected to the inner wall of the collection frame. A limiting rod is connected to the inner side of the positioning sleeve, a guide plate is slidably connected to the outer ring of the limiting rod, a driving ring is welded to the outer ring of the top of the driving screw rod, and a bearing seat is connected to the top of the sampling barrel. A handle is held, a driving ring is rotated, the driving ring drives a driving screw rod to coaxially rotate in the rotating process, the stability of the driving screw rod in the rotating process can be improved through a threaded guide sleeve, and soil is conveniently cut and collected through the arrangement of a soil breaking cone.

The invention relates to the field of soil treatment, in particular to pollutant separation equipment for soil detection. A sliding plate is arranged at the upper end of the filter screen; a masher containing a middle pipe with a liquid cavity and a sleeve is arranged in the hot cylinder; a scraping plate is arranged at the lower end of the top cover; a main cutter is arranged at the lower end of the middle pipe, an auxiliary cutter is arranged above the main cutter and provided with a spray head communicated with the liquid cavity, and a spray head is arranged on the side wall of the hot cylinder. A pneumatic sliding table driving sliding plate is arranged on the support, a reciprocating air cylinder driving sleeve is arranged on the top cover, and a main motor drives a middle pipe through a bevel gear and a magnetic shaft. During operation, soil is put in from the feed port, blending liquid and clear water are injected into the spray head and the nozzle respectively, the main and auxiliary cutters cut up the soil, the rigid paddle and the elastic paddle stir, the hot cylinder heats, steam is discharged through the air pipe, the scraper prevents condensation, the sliding plate moves to enable slurry to enter the dehydrator through the filter screen, and the soil is recycled after dehydration. The equipment is high in separation efficiency, durable in parts and suitable for separation of soil pollutants.

The invention belongs to the field of soil environment big data, and particularly relates to a method and system for evaluating hysteresis of a regional scale industrial source to soil pollution, and the method comprises the steps: collecting industrial source space density data and soil pollutant concentration distribution data in different time periods in a region, and associating the industrial source space density data and the soil pollutant concentration distribution data in space to form data groups in different time periods; indexes such as pollution intensity P, regional area S, statistical time T and lag time L are proposed, and a pollutant cumulant estimation equation set is established; lagging time L and statistical time T are calculated, a lagging coefficient C is calculated, the lagging degree of pollution in a specified time period is evaluated, and scientific and technological support is provided for precise management of the regional scale soil environment.

The present invention provides a soil pollutant identification and route tracking method and system based on artificial intelligence, which relates to the field of pollution monitoring technology, including collecting soil samples in a target area, obtaining sample location information, sample spectral data and sample chemical composition corresponding to the soil samples; inputting the sample spectral data and the sample chemical composition into a pre-trained pollutant identification model, the pollutant identification model is constructed based on a convolutional neural network, extracting sample component characteristics according to the sample spectral data and the sample chemical composition, and identifying the sample pollutant type and sample pollutant concentration by classifying the sample component characteristics; constructing a pollutant heat map based on the sample pollutant type and the sample pollutant concentration in combination with the sample location information; inputting the pollutant heat map into a pre-trained route tracking model, the route tracking model is constructed based on a graph neural network, and predicting the migration route and diffusion state of the pollutant by constructing temporal and spatial relationships.

The application belongs to the technical field of soil pollutant remediation, in particular to a device for efficiently degrading high-concentration petroleum hydrocarbon in soil, which comprises a feeding module, a conveying module and a thermal desorption module, the conveying module is arranged below the feeding module, the feeding module and the thermal desorption module are connected through the conveying module, together forming a petroleum hydrocarbon degradation device, and the device further comprises a motor and a bracket, the bracket is installed on the surface of the feeding module, a rotating shaft is rotatably connected to the surface of the bracket, and the rotating shaft is driven by the motor; the impurities in the soil can be picked out through the cooperation of the picking rod and the comb plate, so as to avoid the situation that the soil is wrapped in plastic bags, which leads to the reduction of degradation efficiency and the adhesion of the soil to the cylinder wall of the thermal desorption cylinder, and the soil with plastic bags is inconvenient to clean in the later period, the degradation efficiency is improved, and the soil with plastic bags can also avoid causing environmental pollution after backfilling.