106 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 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 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 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 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 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 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 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.

The invention provides a soil pollution intelligent detection system and method based on the Internet of Things, and relates to the technical field of soil pollution detection, soil pollution detection points are laid, and the soil pollutant concentration value of each detection point is collected according to a preset frequency; a spatial continuity algorithm is adopted to calculate the pollutant concentration value of an undetected area, and then the pollutant concentration values of all the areas are obtained; constructing a pollution change function model based on the pollutant concentration values of the sampling points in all the areas, and calculating pollution change function values under different distance intervals; and calculating the pollution degree value of the region based on the pollution change function values under different distance intervals, thereby judging the pollution condition of the region.

This utility model relates to the field of soil research technology and discloses an equidistant sampling device suitable for the study of soil pollutants in agricultural land. It includes a support plate with a scale fixedly connected to its top. Two I-shaped grooves are formed at the top of the support plate, and two I-shaped sliders are slidably connected to the inner walls of the two grooves. Two pedals are fixedly connected to the tops of the two sliders. The operator first determines the sampling interval according to the research requirements. Then, the operating parameters of the bidirectional motor, such as speed and direction of rotation, are set via the control panel. After starting the bidirectional motor, its output drives a bidirectional screw to rotate. Due to the bidirectional thread characteristic of the bidirectional screw, the two moving sleeves connected to the surface of the bidirectional screw will move in opposite directions at equidistant intervals along the screw. The operator can then observe the position of the pointer on the scale.

The application relates to the technical field of soil monitoring, and discloses a method and system for monitoring soil pollutants in a power transmission and transformation project, wherein the method comprises the following steps: collecting hyperspectral image data in a power transmission and transformation project area; processing the hyperspectral image data by adopting a multistage spectral transformation mechanism to obtain characteristic wave bands representing pollutant contents; inputting the characteristic wave bands into a preset spectral inversion model to generate a concentration spatial distribution map of soil pollutants; 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 discloses a preparation method and application of Zr-MOF modified magnetic straw biochar filler, and belongs to the technical field of water pollution treatment and ecological remediation, the method comprises the following steps: adding powdery straw into a solution of ferrous ions and ferric ions, stirring and performing ultrasonic treatment, and performing high-temperature pyrolysis on the dried powdery straw to prepare magnetic biochar; zirconium salt, the magnetic straw biochar and terephthalic acid are added into an N, N-dimethylformamide solution, the mixture is stirred and subjected to ultrasonic treatment, then the mixture is put into a polytetrafluoroethylene reaction kettle for a reaction, after the reaction is finished, N, N-dimethylformamide and absolute ethyl alcohol are used for cleaning, and after drying, the Zr-MOF modified magnetic straw biochar filler is obtained. Plant straw is used as a biochar raw material, biochar is modified through Zr-MOF and ferric salt, the porous structure and the specific surface area of the Zr-MOF modified magnetic straw biochar filler can be remarkably improved, the structural stability and the adsorption activity of the filler can be enhanced, refractory organic pollutants in a water body are efficiently removed, and soil pollutants are adsorbed and fixed.

The invention relates to the technical field of soil pollution treatment, in particular to a soil pollution treatment method and system, and the system comprises a treatment module which is used for treating polluted soil; the detection module is connected with the treatment module and comprises a pollutant concentration sensor for detecting the pollutant concentration of the soil; the flow guide adjusting module is connected with the treatment module and the detection module and used for determining the directional flow guide intensity of underground water according to the maximum difference quantity of the concentrations of the soil pollutants at equal intervals and equal depths; the putting adjustment module is connected with the treatment module, the detection module and the flow guide adjustment module and used for determining the putting concentration of the microbial nutrient according to the evaporation rate of the water in the soil within unit time; and the gas-water ratio adjusting module is used for determining the gas-water ratio of the soil pores according to the medicament concentration in the underground water. According to the invention, the treatment stability of soil pollution is improved.

The application discloses a kind of organic contaminated soil medium neutron quantitative inversion method of migration, system and medium, it is related to soil pollutant data inversion technical field, the method includes based on the first neutron transmission image sequence of target test sample of preset time window acquisition;First neutron transmission image sequence in each picture is sequentially preprocessed, multi-scale feature extraction obtains corresponding first multidimensional feature matrix;Wherein, first multidimensional feature matrix includes one or more of color space component feature map, gray attenuation mean feature map and image texture feature map;First multidimensional feature matrix is input into preset based on ViT's physical-data double-driven general inversion model and obtains the predicted value of the absolute mass concentration of organic pollutant per pixel;Based on the preset time window and corresponding predicted value obtains spatiotemporal evolution atlas.The application can improve the data precision and data reliability of the data inversion of soil pollutant migration.

The invention discloses intelligent optimization of soil microbial community and plant synergistic remediation in a phytoremediation experimental facility, and a system monitors soil pollutants, microbial metabolites and plant root exudates in real time, utilizes a microbial sensor and a nano-robot modified by synthetic biology, and an optogenetics technology to realize intelligent optimization of soil microbial community and plant synergistic remediation. Plant-microorganism interaction, a quantum annealing algorithm and a federated learning framework are optimized to generate an optimal repair strategy, the bionic mechanical arm and the laser-nanotechnology execute precise operation, the microbial fuel cell and the piezoelectric energy recovery unit realize self-energy supply of the system, and the system has the characteristics of high efficiency, intelligence and environmental friendliness and is suitable for large-scale popularization and application. The method is suitable for repairing complex soil pollution.

The present invention relates to the field of soil collection, and specifically relates to a portable soil pollutant monitoring device capable of collecting soil at different depths. It includes a base and a turntable. The turntable is rotatably arranged at the center of the top of the base. It also includes a drilling mechanism and a sampling mechanism arranged on the turntable. There are two first through holes on the turntable. The drilling mechanism includes a rotating pipe that can move along the axis direction of the turntable. The rotating pipe is slidably arranged in the corresponding first through hole. A threaded rod is rotatably arranged at the center of the rotating pipe. The sampling mechanism includes a sampling cylinder that can move along the axis direction of the turntable. The sampling cylinder is slidably arranged in the corresponding first through hole. A plurality of material extraction holes are equidistantly arranged along the axis direction of the sampling cylinder. A sampling pipe for extracting soil is slidably arranged in the material extraction hole. There is a second through hole on the base. Through the cooperation of the sampling pipe and the sampling cylinder, independent sampling of soil at different depths can be carried out. Through the cooperation of the turntable and the rotating pipe, the damaged ground can be restored.

The application discloses a soil pollution source analysis method and device, medium and equipment, and relates to the field of environmental science and technology. The application determines the median absolute deviation of the soil background content of the target pollutant in the soil environment background data, considers the uncertainty sources of the target pollutant in different concentration ranges according to the median absolute deviation and the concentration of the method detection limit of the target pollutant, comprehensively considers various uncertainty sources such as laboratory errors, chemical stability and sample uniformity of the target pollutant, constructs a perfect uncertainty calculation method system of spatial heterogeneity, ensures that the uncertainty of the target pollutant can be effectively quantified in various cases, provides a more robust input for the orthogonal matrix decomposition method in soil pollution source analysis, and thus improves the accuracy and reliability of soil pollutant source analysis.