28311 results about "Environmental chemistry" patented technology

The invention relates to the technical field of remote sensing image recognition, in particular to a remote sensing sewage area recognition method and system based on a graph structure and multi-stage enhancement. The method comprises the steps of performing data preprocessing and representation enhancement on an acquired remote sensing image; performing sewage salient region preliminary screening on the enhanced remote sensing image, including abnormal enhancement mapping construction based on local statistical distribution; pollution candidate graph extraction based on spatial structure prior driving; enhancing the response of the stable region based on a structure consistency enhancing mechanism of the polluted region; high-precision segmentation and identification of the sewage area comprises the following steps: constructing a multi-resolution residual pyramid structure; carrying out fine-grained boundary structure modeling and uncertainty suppression; generating a sewage distribution probability graph and optimizing structural consistency; according to the method, the multi-resolution residual pyramid structure is constructed, image context information under different perception scales is fully mined, and the sensitivity and edge integrity of the model to a sewage area under a complex texture background are remarkably enhanced.

The invention discloses a landslide prediction and early warning system and method based on a remote sensing technology, and is applied to the technical field of landslide early warning. Comprising a data acquisition module for acquiring multi-source data in a monitoring area; the cloud computing module is used for large-range landslide risk assessment and deformation monitoring; the edge calculation module is used for landslide risk assessment and deformation monitoring of a specific area; the end-cloud cooperative communication module is used for realizing data interaction between the cloud computing module and the edge computing module; the federal learning module is used for realizing cooperative training under data privacy protection of different areas; and the landslide early warning module is used for carrying out early warning based on landslide risk assessment and deformation monitoring results of the cloud computing module and the edge computing module. According to the invention, by using the deep learning model, the end-cloud collaborative architecture and the federal learning driven data fusion framework, efficient, low-cost and high-precision landslide risk prediction is realized.

A system and method for maintaining an oxygen concentration of a biological sample. The oxygen concentration can be maintained by measuring the oxygen concentration within the biological sample and adjusting a rate of an oxygen supplier in response to this measurement. For example, when the oxygen concentration is below a threshold, oxygen can be delivered to the biological sample at a higher rate.

The invention relates to the technical field of soil pollution identification, and discloses a soil heavy metal pollution identification system. A multispectral remote sensing sensing module of the system obtains surface reflectance data and soil in-situ spectral data through a satellite load and a vehicle-mounted mobile platform respectively, and the surface reflectance data and the soil in-situ spectral data are processed by a heterogeneous data fusion gateway to generate multiband spectral response signals. In the pollution risk assessment module, a spatial distribution analysis unit outputs a heavy metal spatial distribution map, a migration risk prediction unit generates a pollution migration probability cloud map in combination with meteorological and hydrological data, and a pollution threshold defining unit outputs a soil remediation safety threshold. In the treatment decision execution module, an in-situ remediation execution unit adjusts passivator injection parameters, a pollution source management and control unit regulates pollution source blocking equipment and collects monitoring signals, and a three-dimensional dynamic early warning platform generates a comprehensive pollution risk index. According to the system, the cooperative operation of soil heavy metal pollution identification, evaluation and treatment is realized.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

A system for the hypothermic transport of biological samples, such as tissues, organs, or body fluids. The system includes a self-purging preservation apparatus to suspend a sample in preservation fluid and perfuse a tissue with preservation fluid. The self-purging preservation apparatus is placed in an insulated transport container having a cooling medium. When assembled, the system allows for transport of biological samples for extended periods of time at a stable temperature.

The present disclosure provides a landslide identification method, a device and a storage medium based on multi-path feature fusion, and relates to the field of geological hazard monitoring and early warning. The device and storage medium are used to implement the method. The beneficial effects of the present disclosure are as follows: a landslide identification method based on multi-path is provided, deep feature-level interaction among different types of landslide image data is achieved, high-resolution feature information is preserved, landslide identification accuracy is significantly improved, the computational costs are reduced, the real-time performance of landslide identification is significantly enhanced and the real-time monitoring and early warning are achieved.

The invention relates to the field of water quality monitoring analysis, in particular to a multi-modal water quality monitoring data intelligent processing method and system. The method comprises the following steps: obtaining a water quality monitoring parameter stream and a water quality monitoring image, and carrying out adaptive processing to obtain a filtering optimization parameter stream and an optimization monitoring image; performing water quality state evolution perception according to the adaptive filtering optimization parameter flow, and constructing a water quality state evolution graph; and performing biological index response analysis and water quality ecological influence evaluation based on the water quality state trend evolution graph to obtain a water quality evaluation report. And carrying out pollutant spatial distribution change analysis based on the optimized monitoring image, and executing final water quality monitoring evaluation according to a water quality evaluation report. The invention provides efficient and accurate water quality status analysis.

The invention discloses a forest carbon reserve and carbon sink monitoring and evaluating method based on a multi-source remote sensing technology. The method comprises the following steps: multi-source remote sensing data acquisition: respectively acquiring optical remote sensing data and radar remote sensing data; tree species classification and identification: carrying out tree species classification on the forest in the research area to realize tree species scale space distribution information extraction; for different tree species, biomass model parameters obtained through field investigation are combined, a biomass estimation model based on the tree species is established, model input parameters are biomass model parameters, and vegetation biomass is output; calculating the carbon reserve: calculating the vegetation carbon reserve by utilizing the inverted vegetation biomass and combining the carbon content coefficients of different tree species; estimating the soil carbon reserve, and finally obtaining the total carbon reserve of the forest ecosystem: calculating the carbon reserve variation of the forest ecosystem at different time points based on the multi-source remote sensing data of the long-term sequence. According to the invention, large-range, high-precision and continuous forest carbon reserve and carbon sink monitoring and evaluation considering tree species difference is realized.

The invention discloses a plot pollution monitoring, predicting and early warning system and method, and relates to the technical field of environment monitoring and pollution early warning, and the method comprises the steps: obtaining multi-source data of a target plot; performing preprocessing, feature extraction and fusion on the multi-source data; inputting the multi-source data into the dynamic pollution diffusion model to obtain a pollutant concentration field of the target plot; jointly inputting the fusion data and the pollutant concentration field into a land parcel pollutant concentration prediction model for prediction to obtain a pollutant concentration prediction value of the target land parcel in a future target time period; comparing the pollutant concentration predicted value of the target land parcel in the future target time period with the early warning threshold values of all levels, and generating an early warning instruction of the corresponding level according to a comparison result; generating corresponding early warning information according to the early warning instruction; and executing corresponding early warning measures according to the early warning information. According to the invention, through multi-dimensional data integration and model optimization, scientific assessment and hierarchical management and control of pollution risks can be realized.

A long-term fire retarding biochemical liquid composition including: a dispersing agent realized in the form of a major amount of water, for dispersing alkali metal ions dissolved in the water; a major amount of a first fire retarding agent realized in the form of a primary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, tripotassium citrate, for providing metal potassium ions dispersed in the water when the at least one alkali metal salt is dissolved in the water to form a mixed retardant solution; a minor amount of a second fire retarding agent realized in the form of a secondary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, potassium, sodium, calcium and / or magnesium benzoate, for providing benzoate ions dispersed in the water when the secondary alkali metal salt is dissolved in the mixed retardant solution, for functioning as a secondary fire retardant agent.

A non-invasive liquid integrity monitoring system using dielectric fingerprinting and machine learning to detect and identify contamination in sealed containers is described. The system may employ externally-mounted sensors that measure dielectric properties through electromagnetic interrogation, comparing measurements against baseline signatures to detect deviations indicating contamination, tampering, or degradation. Industry-specific ML models enable identification of specific contaminants with confidence, providing alerts without breaching container integrity.

The invention relates to the technical field of data twinning, in particular to a saline-alkali soil water-salt motion simulation method based on big data analysis. The method comprises the following steps: collecting saline-alkali soil multi-source monitoring data; based on the saline-alkali soil multi-source monitoring data, salt soil layer correlation feature analysis and water-salt driving factor coupling feature analysis are carried out, and salt soil layer correlation feature data and water-salt driving factor coupling feature data are obtained; simulation relation model design of saline-alkali soil water-salt movement is carried out through the saline-alkali soil level correlation feature data and the water-salt driving factor coupling feature data, and a saline-alkali soil water-salt movement simulation model is generated; based on the saline-alkali soil water-salt motion simulation model, designing saline-alkali soil farmland irrigation simulation parameters; and carrying out water-salt motion simulation prediction and feedback of the saline-alkali soil farmland irrigation on the saline-alkali soil farmland irrigation simulation parameters. According to the saline-alkali soil water-salt motion simulation analysis method, multi-driving-factor fusion and accurate spatial heterogeneity description are achieved.

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment control process based on dynamic regulation and control of aeration and carbon source addition, which comprises the following steps: acquiring microbial metabolism heat change data in real time; biochemical treatment: monitoring the dielectric constant of a water body and the Reynolds number of sewage flow in real time, and constructing a multi-parameter coupling regulation and control model and dynamically regulating and controlling the aeration rate in combination with microbial metabolism heat change data obtained in the pretreatment step; accurately adding the carbon source according to a calculation result of the carbon source demand prediction model; sewage subjected to biochemical treatment is subjected to ultrafiltration through a nanofiber membrane and then subjected to combined disinfection treatment through ultraviolet rays and ozone, treatment parameters are regulated and controlled in real time according to the membrane flux attenuation trend in the treatment process, and dynamic and accurate control over sewage treatment is achieved. According to the method, the problem of energy consumption waste caused by excessive aeration or low degradation efficiency caused by insufficient aeration in a traditional process is solved, and accurate matching of dissolved oxygen supply and microbial requirements is realized.

The invention discloses a sewage denitrification dosing method and system based on machine learning and a storage medium, and belongs to the technical field of sewage treatment.The method includes the steps that data are collected and preprocessed, and variable data influencing biochemical pool carbon source dosing behaviors are obtained; and lagging influence of carbon source input on the denitrification amount index is analyzed, and the duration time range of the drug effect is determined. And adopting the trained prediction model, and based on the denitrification amount index and the prediction variable of the future t + X period, obtaining the dosage of the (t + 1) th period. Through a correlation analysis method, the correlation rule of nitrogen conversion in the future X period after the carbon source is added is analyzed, the duration time of the drug effect is determined, the lag effect is accurately quantified, and the problem of mismatching of regulation and control opportunities is avoided. The hysteresis effect is captured and subjected to multi-factor coupling analysis based on the prediction model, the carbon source adding amount and time are optimized, system load fluctuation caused by excessive carbon sources or incomplete nitrogen removal caused by insufficient carbon sources are avoided, and the stability of an original sewage ecological system is gradually improved.

The invention discloses a soil water and salt dynamic monitoring and quality evaluation method based on multispectral remote sensing, and relates to the field of geological monitoring, and the method comprises the steps: carrying out the scattering deviation correction and roughness correction of an observation spectrum through a satellite remote sensing image, an unmanned aerial vehicle multispectral image, a ground sample and meteorological driving data; the soil intrinsic reflectivity, the vegetation coverage component and the salt crusting component are obtained; a water-salt inversion model is established by combining thermal infrared and red edge wave band information, and multi-temporal soil volumetric moisture content and surface salinity index are inverted; by introducing meteorological conditions and vegetation dynamic characteristics, a water-salt coupling partial differential equation and a graph space-time constraint model are constructed, and continuous space-time distribution of soil water content and salinity is obtained; extracting salinity, moisture, vegetation response and soil health indexes, establishing a soil quality comprehensive evaluation model, and outputting high-risk plaques and a treatment priority sequence. The method realizes dynamic monitoring and quality grading evaluation of soil water and salt, and is suitable for saline-alkali soil treatment and ecological restoration.

The invention relates to the technical field of remote sensing, discloses a geological environment monitoring method and system based on multi-source remote sensing, and aims to solve the monitoring problems of heterogeneous multi-source remote sensing data, difficulty in dynamic capture, disjunction of geological mechanism and interpretation and the like. According to the method and the system, multi-source remote sensing data is acquired and standardized, multi-modal geologic features are extracted, through cross-modal deep fusion and space-time modeling, abnormity is analyzed and identified, risks are evaluated, and visualization and decision support are realized. According to the technical scheme, comprehensive, accurate and high-timeliness monitoring of the geological environment can be realized, the premonition of the geological disaster can be effectively identified, the trend can be predicted, and support is provided for prevention and control of the geological disaster.

The present disclosure provides a carbon dioxide absorption composition, which includes a solution of an amino compound in a solvent comprising water and a glycol, as well as a method of using such composition to capture CO2. The present composition can be particularly advantageous for indoor use, with additional benefit for managing total volatile organic compounds and humidity to enhance overall indoor air quality.

The invention discloses a drinking water disinfection by-product generation prediction method based on a reaction kinetic model, and belongs to the technical field of drinking water treatment and drinking water quality prediction, and the method is realized based on the following steps: 1) constructing a disinfection by-product generation kinetic model of a model compound and determining the reaction rate of each step; 2) constructing and optimizing a disinfection by-product generation kinetic model of the natural organic matter on the basis of the obtained reaction rate to obtain a disinfection by-product generation kinetic model of an actual water body; 3) establishing a prediction method for the concentration of each component in the model; and 4) inputting the measured concentration of each component in the actual water body into the constructed model, and calculating and predicting a disinfection by-product generation kinetic result of the actual water body through the model. The method fully considers the generation kinetics of the disinfection by-products of the actual water body under different space (time) distribution, can quickly predict the generation of various disinfection by-products which are managed and controlled and are not managed and controlled but have high toxicity, provides early warning for the effluent quality of drinking water treatment, and ensures the safety of drinking water.

The invention discloses a karst underground river system multi-source pollution comprehensive quantitative traceability method, which comprises the following steps: S1, multi-dimensional sample collection and new pollutant screening: carrying out multi-period sampling on a water body, measuring conventional water quality indexes and nitrogen and oxygen isotopes, screening new pollutants, and carrying out targeted quantification on characteristic new pollutants; s2, principal component analysis dimension reduction and pollution factor identification: carrying out principal component analysis on conventional indexes and new pollutant data, extracting principal components of which the cumulative contribution rate exceeds 85%, identifying composite pollution factors, and eliminating secondary interference factors; s3, nitrogen and oxygen isotope auxiliary verification and denitrification elimination: eliminating denitrification interference by utilizing the ratio of delta 15N-NO3 <-> to delta 18O-NO3 <-> in combination with underground water burial depth and runoff velocity, and distinguishing the nitrate source as a chemical fertilizer, soil nitrogen or sewage and wastewater; and S4, PMF model optimization and pollution source quantification: inputting the conventional indexes and the new pollutant concentration matrix into a PMF model, and analyzing the contribution rate of each pollution source.

A direct air capture (DAC) of CO2 system includes a reaction reactor having a solid, amine-functionalized sorbent configured to sequester CO2 from air; an in-situ dual-function device configured as a CO2 conversion reactor and an exchange fluid regeneration device; and the exchange fluid, recirculating between the reaction reactor and the dual-function device, configured to capture the sequestered CO2 from the solid sorbent in the reaction reactor and release the captured CO2 in the conversion reactor, the exchange fluid including one or more amino acids.

The invention relates to the technical field of soil environment monitoring, and discloses a soil remediation construction site environment monitoring method based on edge computing cloud collaboration. The method comprises the following steps: deploying an edge computing node at a restoration construction site, and collecting real-time data of soil humidity, heavy metal concentration, volatile organic compound content and meteorological parameters through a multi-source sensor; inputting the data into a spatio-temporal feature extraction network, and generating a spatio-temporal fusion feature matrix by means of hierarchical convolution and a cross-channel attention mechanism; on the basis of the matrix, the index anomaly probability is calculated by using a depth probability network, and a risk feature sequence with uncertainty measurement is generated; constructing a dynamic risk field model in combination with repair process parameters, and predicting a pollution diffusion path through a space-time propagation algorithm; and in combination with an equipment operation state, an edge side local regulation and control instruction and a cloud global optimization strategy are generated by a collaborative decision engine, and efficient and accurate environment management requirements of a construction site are met.

An atmospheric CO2 capture system includes a compartment housing a solid CO2 sorbent, an exchange fluid including a chemical component with selectivity towards CO2, and an electrochemical cell or mineralization reactor in fluid communication with the compartment, the system having a cycle including a first state of sorbing CO2 from incoming air onto the solid CO2 sorbent until a saturation point is reached; a second state of regenerating the sorbent by flooding the compartment with the exchange fluid to detach CO2 from the saturated sorbent and bind the detached CO2 to the chemical component; and a third state of regenerating the chemical component and utilizing the CO2 in the electrochemical cell or mineralization reactor.

The invention provides a special charcoal-based slow-release fertilizer for sandy soil as well as a preparation method and application thereof, and belongs to the technical field of fertilizers. The special charcoal-based slow-release fertilizer for the sandy soil is prepared from amino modified biomass charcoal, urea, urea formaldehyde, monoammonium phosphate, potassium sulfate, polyglutamic acid, fulvic acid, clay, attapulgite, a compound microbial agent and sodium alginate. The compound microbial agent is prepared from halomonas (ACCC 11681), bacillus subtilis (ACCC 60429) and bacillus mucilaginosus (ACCC 10094), and the compound microbial agent is prepared from bacillus subtilis (ACCC 60429) and bacillus mucilaginosus (ACCC 10094). The invention further provides a preparation method and application of the special charcoal-based slow-release fertilizer for the sandy soil. The special charcoal-based slow-release fertilizer for the sandy soil can remarkably improve the water and fertilizer retention capacity of the sandy soil, improve the farmland productivity of the sandy soil, save fertilizer and water input and improve the yield and quality of crops.

The invention belongs to the technical field of river and lake water quality monitoring, and discloses a river and lake water quality intelligent traceability monitoring system and method.Dissolved organic matter fluorescent fingerprints are analyzed in real time through a three-dimensional fluorescent monitoring unit, pollution markers are detected, and parameters such as COD, ammonia nitrogen and total phosphorus are synchronously detected through a full-spectrum monitoring unit; the video monitoring unit is used for collecting section images / videos of rivers and lakes, other sensors are used for collecting real-time values of chlorophyll, pH, conductivity, turbidity and dissolved oxygen in a water body, then the data processing module is used for carrying out normalization processing on multi-source data, and the analysis and early warning module is used for analyzing water quality early warning scores, spectrum early warning scores and video early warning scores. All scores are synthesized to obtain a comprehensive early warning score, traceability is started when comprehensive early warning is larger than or equal to the grade II, pollution sources are recognized based on three-dimensional fluorescence spectrum comparison and upstream patrol, and a river and lake water body monitoring-early warning-traceability-verification closed loop is achieved.

The invention discloses a biomass charcoal composite hydrogel slow-release fertilizer as well as a preparation method and application thereof, and belongs to the field of composite hydrogel and fertilizer preparation. The invention provides a biomass charcoal composite hydrogel slow release fertilizer, which comprises biomass charcoal, hydrogel fixed on the pores and surface of the biomass charcoal, and an element fertilizer mixed in the hydrogel, and the hydrogel is prepared from metal cations and alginate. The invention provides a strategy of'in-hole in-situ gelation ', hydrogel is prepared in situ in gaps of the biochar, and the biomass charcoal composite hydrogel slow-release fertilizer is prepared. The biochar and the hydrogel in the slow-release fertilizer are high in bonding strength and mechanical strength, so that the slow-release fertilizer has the slow-release function of the fertilizer and also has the capability of improving soil.

The invention relates to the technical field of environmental science, in particular to a box-type model-based inversion method for methane sulfonic acid particles in marine droplet aerosol, which comprises the following steps of: 1, acquiring satellite remote sensing data, ground observation data and laboratory simulation data, and carrying out data standardization processing; 2, dividing the target sea area into a plurality of sub-areas as independent box bodies; 3, calculating the discharge flux of the marine droplet aerosol based on the dimethyl sulfide concentration and the wind speed, and updating the spatial and temporal distribution of the discharge source; 4, embedding a chemical reaction path for oxidizing dimethyl sulfide on the surface of the aerosol into the box-type model to generate methanesulfonic acid, and introducing the specific surface area of the aerosol to correct the reaction rate; and step 5, outputting spatio-temporal distribution of the concentration of the methane sulfonic acid, and comparing measured data for verification. The accuracy of aerosol source item estimation is improved, the fusion efficiency of multi-source data is improved, and the adaptive capacity of the model in a complex environment is enhanced.

The invention relates to the technical field of carbon emission monitoring and environment perception, and discloses a user-side carbon emission real-time monitoring and tracing system, which comprises a multi-source data integration module, which is used for acquiring microenvironment parameters related to carbon emission in real time; the microenvironment feature analysis module is used for analyzing the feature parameters of the traffic road section through a microenvironment perception algorithm and establishing a microenvironment feature library; the environment relation modeling module is used for constructing a vehicle performance and microenvironment relation model and calculating an environment adjustment coefficient; the dynamic carbon emission calculation module is used for generating a carbon emission estimated value; the abnormal recognition and early warning module is used for recognizing an abnormal emission mode under a specific microenvironment combination and constructing an early warning mechanism; the carbon emission map building module is used for building an urban microenvironment carbon emission influence map; the carbon footprint analysis and report module generates a refined carbon footprint report through a microenvironment factor contribution degree quantitative decomposition algorithm; according to the method, through microenvironment influence decomposition and visual display, a carbon emission result has good interpretability.

The invention discloses a large-scale pig breeding wastewater purification treatment system, and relates to the technical field of wastewater treatment.The large-scale pig breeding wastewater purification treatment system is characterized in that the ion concentration of anaerobic liquid is monitored through a multi-ion sensing array, and a multi-channel feeding system is controlled to synthesize customized struvite compound fertilizer; the AI prediction control unit predicts the optimal medicament dosage and realizes millisecond-level closed-loop regulation; the multi-dimensional synergistic biochemical treatment module comprises an A / O biochemical treatment unit and an electric field enhanced anaerobic ammonia oxidation reactor, the electric field enhanced anaerobic ammonia oxidation reactor applies a direct-current electric field through an electrode pair, and engineering conductive biochar is used as a carrier to accelerate microbial metabolism; the sludge low-temperature pyrolysis self-consistent circulation module is used for pyrolyzing and converting residual sludge into biochar, biofuel and wood vinegar, and the biochar activation treatment unit is used for preparing engineering conductive biochar and forming a substance closed loop through a self-consistent circulation conveying system; and the digital twinning intelligent management and control platform realizes intelligent management and control of the system.

The invention provides a treatment method of ammonia-nitrogen-containing wastewater, and belongs to the technical field of wastewater treatment. The preparation process comprises the following steps: preparing the wastewater treatment agent; preparing an immobilized microbial compound; and treating the ammonia-nitrogen-containing wastewater. According to the immobilized microbial carrier prepared by the invention, a stable dual-network structure and proper pore channels are formed through the synergistic effect of the polyvinyl alcohol, the carboxymethyl chitosan and the polyurethane; secondary cross-linking significantly enhances the stability of the carrier, optimizes internal pore channels, and is beneficial to attachment and proliferation of microorganisms; after the corn straw biochar is modified by Ca / Al, the specific surface area and functional groups are increased, and the physicochemical adsorption of ammonia nitrogen is enhanced. The three are combined, and ammonia nitrogen in wastewater is efficiently removed through synergism of carrier adsorption and microbial metabolism.