267 results about "Metal pollution" patented technology

The invention discloses a composite interference-oriented cultivated land system toughness evaluation and optimization method, and relates to the technical field of cultivated land toughness optimization, and the method comprises the steps: collecting and preprocessing multi-source cultivated land data, constructing a toughness evaluation index system, and calculating the weight of each index; and calculating a comprehensive toughness score based on weight distribution, drawing a time sequence change curve based on the score, and performing region division to generate a toughness distribution diagram. According to the method, the single-factor pollution index, the Nemo comprehensive index and the interaction effect index of heavy metal pollution are combined, the soil pollution condition is accurately quantified through a weighted summation method, a scientific and reliable basis is provided for toughness evaluation, the dynamic toughness distribution diagram is generated in combination with the LSTM model and the GIS technology, the spatio-temporal dynamic characteristics of a cultivated land system under composite interference are revealed, and the method has the advantages of being high in reliability and high in reliability. According to the method, the defects of an existing model in space-time analysis are overcome, differentiated optimization strategies are formulated based on region division and weak region labeling, and the resource allocation efficiency and the pertinence of an optimization scheme are remarkably improved.

The invention discloses a water quality heavy metal pollution detection method and system based on Raman spectrum.The water quality heavy metal pollution detection method comprises the steps that water body Raman scattering light is collected in situ through a miniature optical fiber probe, and a continuous time sequence spectrum signal flow is generated; wavelet transform is combined with self-adaptive threshold setting, and high-frequency noise and effective spectral signals are separated; dynamically strengthening the characteristic peak of the target heavy metal through a frequency domain characteristic screening module, and inhibiting a water molecule interference peak at the same time; generating a cross-domain fusion feature vector; processing the fusion feature vector through a pre-trained heavy metal concentration prediction model, and outputting concentration prediction values of various heavy metals; a confidence score is dynamically calculated based on a deviation between a current predicted value and historical data distribution, and model parameter update and system calibration are automatically triggered. The method has the advantages that through acousto-optic signal cross-domain fusion and closed-loop self-calibration, the target peak is dynamically strengthened while water molecule interference is inhibited, and the real-time performance, the anti-interference performance and the prediction precision of heavy metal detection are improved.

The invention provides a water quality heavy metal pollution detection method and system based on Raman spectrum. The method comprises the following steps: collecting a water sample through a water area to be detected, and scanning the water sample by adopting a Raman spectrometer to generate an original Raman spectrogram; based on the original Raman spectrogram, using a wavelet transform algorithm to perform de-noising processing, reducing background interference, using a principal component analysis technology to extract characteristic peaks, and generating a heavy metal preliminary prediction result; based on the preliminary heavy metal prediction result, constructing a heavy metal concentration prediction model by applying a partial least squares regression algorithm, performing quantitative analysis, evaluating prediction accuracy by adopting a cross validation technology, and generating a heavy metal actual concentration result; and based on the actual heavy metal concentration result, comparing with a water quality safety standard, evaluating a pollution condition, and generating a water quality heavy metal pollution detection report. The technical scheme provided by the invention has high sensitivity, can efficiently denoise and accurately predict, and provides a scientific means for monitoring and treating heavy metal pollution of water.

The invention relates to the technical field of land improvement, in particular to an alginic acid type multifunctional long-acting soil conditioner and a preparation method and application of the alginic acid type multifunctional long-acting soil conditioner. The core particle layer comprises an organic material, nano silicon, calcium magnesium polyphosphate, magnesium hydride, ammonium borate, rhamnose and an adhesive, and the slow release layer comprises clay minerals and alginate; the mass ratio of the clay mineral to the alginate to the organic material to the calcium magnesium polyphosphate to the nano silicon to the magnesium hydride to the ammonium borate to the rhamnose to the binder is controlled within a certain range. The soil conditioner provided by the invention is good in slow release performance, can release effective components durably and slowly, and has multiple effects of improving soil quality, providing nutrition, promoting crop growth, improving resistance and the like; the problems of soil acidification, heavy metal pollution, micro-plastic pollution, pesticide pollution, antibiotic pollution and the like in agricultural production can be effectively solved.

The invention provides a food heavy metal pollution detection system based on plasma emission spectrum analysis, and aims to realize rapid and accurate detection of heavy metal elements in a food sample. The system comprises a sample processing module, an excitation module, a spectrum detection module, a signal processing module, a data analysis module and an output module. The sample processing module converts a food sample into an aerosol or steam state. The spectrum detection module is used for extracting spectrum characteristic information of heavy metal elements. And the signal processing module adopts an AI-driven spectrum denoising algorithm to remove background noise and interference signals. And the data analysis module calculates the concentration of each element based on the characteristic peak intensity and generates heavy metal pollution data. And the output module is used for visually displaying the detection result. According to the method, complex sample pretreatment steps are reduced, the detection efficiency and sensitivity are improved, and the method is suitable for food safety detection scenes and particularly has remarkable advantages in field rapid detection application of agricultural products, drinking water and processed food.

The present application relates to the technical field of heavy-metal pollution remediation, and relates in particular to a soil heavy‐metal accumulation predicting method employing an emission inventory and a receptor model. The method comprises: using atmospheric dust deposition, irrigation water, chemical fertilizers and pesticides as input flux sources of heavy metals to farmland soil, using surface runoff and crops as output fluxes, and constructing an input-output flux inventory of heavy-metal pollutants to clarify a dynamic balance relationship of soil heavy-metal accumulation; and continuously collecting and monitoring of soil samples. The invention provides crucial assistance in determining the transport balance of heavy metals in farmland areas impacted by non-ferrous metal smelting and beneficiation slag sites and in identifying sources of soil heavy-metal pollution, and offers theoretical guidance for subsequent soil heavy-metal remediation and targeted control.

The invention relates to the technical field of mathematical modeling, in particular to a mathematical model modeling method based on data analysis operation processing. The method comprises the following steps: collecting metal pollution data of a target water area by using a multi-parameter water quality sensor array; performing time sequence alignment on the metal pollution data to generate a standardized pollution data set; constructing a metal migration model based on fluid dynamics and chemical adsorption coupling; inputting the standardized pollution data set into the metal migration model for three-dimensional space interpolation calculation, and generating a metal pollutant diffusion cloud picture; pollution source reverse analysis is carried out on the metal pollutant diffusion cloud picture, and a potential pollution source coordinate set and pollution contribution degree sorting are generated. According to the method, by integrating multi-parameter water quality sensor data, fluid dynamics and chemical models and multispectral analysis, the modeling precision of the water pollution diffusion mathematical model is improved.

The invention provides a high-stability in-situ crystallization catalyst as well as a preparation method and application thereof, and belongs to the technical field of oil refining catalysts. The preparation method comprises the following steps: firstly preparing kaolin microspheres, then roasting the kaolin microspheres into high soil balls and partial soil balls, and mixing the high soil balls and partial soil balls with a silicon source, sodium hydroxide, a seed crystal and a silicon-aluminum activator for in-situ crystallization, so that not only is the activation degree of silicon dioxide in kaolin promoted, but also the timely insertion of active silicon species into a NaY zeolite skeleton in the crystallization process is accelerated, and the activity of the NaY zeolite is improved. The high-stability in-situ crystallization catalyst is prepared by carrying out ammonium salt and rare earth exchange, roasting and phosphorus or boron modification treatment on the crystallized microspheres, and has the characteristics of strong heavy oil conversion and metal pollution resistance and high total liquid yield when being used for catalyzing heavy oil cracking.

The invention discloses an unconventional feed quality assessment method and system, and relates to the technical field of unconventional feed quality assessment, and the method comprises the following steps: in a feed high-temperature drying treatment process, establishing a multi-dimensional sensing monitoring baseline, continuously obtaining mercury vapor concentration gradient, moisture evaporation rate and airflow velocity field data in a feed drying environment, and calculating the quality of the feed; forming a time sequence feature set reflecting the dynamic change of mercury vaporization; and constructing a gas-solid interaction analytical model by using the time sequence feature set, and carrying out coupling analysis on the mercury vapor migration trajectory and the temperature distribution and humidity distribution of the feed particle surface to generate a spatial distribution data set representing the spatial distribution feature of the mercury vapor redeposition region. According to the invention, the whole-process monitoring and dynamic regulation and control of mercury vaporization, migration and redeposition in the feed drying process are realized, through multi-dimensional monitoring, amplitude limiting control and high-frequency disturbance, the mercury distribution is balanced, the risk is reduced, the drying safety and the feed quality stability are improved, and the controllable management of heavy metal pollution is effectively realized.

The invention discloses a numerical prediction method and system for heavy metal pollution load evolution in a drainage basin, and belongs to the technical field of drainage basin heavy metal pollution prevention. According to an existing drainage basin pollution prediction scheme, the influence of heavy metal pollution leaching from soil due to rainfall and the influence of atmospheric heavy metal pollution sedimentation are not considered, so that the conversion and transportation processes of heavy metal pollution cannot be accurately simulated. According to the numerical prediction method for heavy metal pollution load evolution in the drainage basin, heavy metal multi-dimensional evolution data is obtained by constructing a heavy metal parameter analysis model, a heavy metal three-dimensional evolution model and a heavy metal coupling prediction model; then the heavy metal multi-dimensional evolution data, weather data and hydrological calculation data are subjected to coupling calculation to obtain an accurate heavy metal pollution prediction value, so that the evolution process of heavy metal pollution between water, land and air can be accurately simulated; and the development trend of the heavy metal pollution load in the drainage basin can be tracked and predicted more comprehensively.

The invention relates to the technical field of ecological environment protection, and discloses a method for accurately selecting heavy metal polluted cultivated land remediation measures based on rhizosphere evaluation. According to the method for accurately selecting the remediation measures of the heavy metal polluted cultivated land based on rhizosphere evaluation, the heavy metal pollution condition in soil and agricultural products and the condition of soil microorganisms under heavy metal stress are comprehensively considered, the heavy metal pollution level of the cultivated land soil is comprehensively evaluated, and the remediation measures of the cultivated land are accurately selected. Proper soil remediation measures are selected by combining the soil pH and the heavy metal content in the irrigation water, so that the heavy metal polluted cultivated land can be accurately remedied, the heavy metal content is reduced, and the quality of agricultural products is guaranteed; compared with large-scale soil remediation, through accurate evaluation, partitioned remediation can be carried out on the cultivated land, the remediation effect is improved, the remediation cost is reduced, normal production of farmers is basically not affected, and remediation and production are carried out at the same time.

A method and system for tracing the source of non-point source heavy metal pollution in a watershed, the method first determines the spatial distribution of soil heavy metal content under various land use types in the watershed, the sediment enrichment ratio and water solubility factor of soil heavy metals, and simulates the spatial and temporal distribution of rainfall runoff and soil erosion sand production, and then calculates the loss of land surface heavy metal pollution, and then combines the migration of heavy metal pollution in the river channel to calculate the loss of non-point source heavy metal pollution in the outflowing river section under various land use types, so as to obtain the contribution ratio of each land use type to the non-point source heavy metal pollution in the watershed, and finally determines the main source of the loss of heavy metal pollution in the watershed according to the contribution ratio. The present invention comprehensively considers the impact of land loss and river migration process on non-point source heavy metal pollution in the watershed, and can realize the accurate calculation of the loss load of non-point source heavy metal pollution at the watershed scale and the rapid and precise identification of pollution sources.

The invention relates to the technical field of soil cadmium remediation, in particular to a soil Cd recognition and remediation method based on mulberry root exudates and microorganisms. According to the method, spatial microscopic image frames of rhizosphere microflora are divided through a community structure, community node increment updating calculation of adjacent time sequences is executed, the transition recombination frequency of the rhizosphere microflora is obtained, and the transition color of the actual concentration content of root exudates is rendered based on a metal pollution level system and the transition recombination frequency. Generating a stress level heat model of the soil cadmium gradient in the target restoration area; and according to the stress level popularity model, carrying out popularity color analysis and identification on the soil cadmium pollution of the target restoration area, and generating a global stress identification result of the soil cadmium. According to the method, rapid identification of cadmium pollution enrichment can be realized by utilizing the synergistic response between mulberry root exudates and rhizosphere microorganisms, and a repair regulation and control plan is made, so that the cadmium pollution degree is reduced, the soil structure and fertility are optimized, and a safer and healthier environment is provided for plant growth.

The invention relates to the technical field of waste catalyst resource utilization, in particular to a waste SCR denitration catalyst based heavy metal adsorbent and a preparation method thereof.The preparation method comprises the following steps that a waste SCR denitration catalyst is placed in a mixed solution of sulfuric acid and organic acid to be subjected to acid leaching treatment, and after filtering and drying treatment, the waste SCR denitration catalyst is obtained; catalyst powder subjected to acid leaching treatment is obtained; mixing the catalyst powder subjected to acid leaching treatment with a mineral material, adding a metal oxide, and carrying out ball milling treatment in a high-energy ball mill; and adding an organic binder into the ball-milled powder, and uniformly mixing to obtain the heavy metal adsorbent. Through the steps of chemical extraction, physical mixing, activity excitation and the like, the waste SCR denitration catalyst is converted into the composite material with the efficient heavy metal ion adsorption capacity, efficient resource utilization of the waste SCR denitration catalyst is achieved, and meanwhile a new solution is provided for water body heavy metal pollution treatment in China.

The invention provides a chitosan-iron nanoparticle leaf surface resistance and control agent as well as a preparation method and application thereof, and belongs to the technical field of reduction of heavy metal pollution of crops. The preparation method comprises the following steps: dissolving chitosan in an organic solvent to obtain a chitosan solution, mixing the chitosan solution with ferrous sulfate, adding a sodium tripolyphosphate solution for crosslinking and stirring to obtain a solution containing precipitates, centrifuging, and collecting the precipitates to obtain the chitosan / ferrous sulfate composite material. The TPP and amino groups of the chitosan form ionic crosslinking through triphosphate groups, and Fe < 2 + > is successfully loaded on the surfaces of the chitosan nanoparticles. By complexing chitosan and Fe < 2 + >, the crystallinity of the material is reduced, and the adsorption activity of the amorphous structure is enhanced. Pot experiments show that by spraying the chitosan-iron nanoparticle leaf surface resistance and control agent on leaf surfaces, heavy metals of crops can be remarkably reduced, the antioxidant enzyme activity of plant tissues is improved, active oxygen is effectively removed, oxidative damage is relieved, and therefore plant growth is promoted, and the toxic effect of heavy metal stress on the crops is relieved.

The invention discloses a method for assessing the ecological risk of heavy metal polluted soil, which belongs to the technical field of pollution assessment, and specifically comprises: dividing a polluted area to be tested into a plurality of grids, collecting indicators in the soil at each grid intersection, and calculating the pollution risk score of each grid intersection; performing interpolation data fitting in the grids by a radial basis function interpolation method, and generating a pollution risk score map contour map; selecting the contour line with the largest value in the contour line map, marking it as the initial contour line, and determining the starting connection point, sequentially searching for the end connection point with the longest distance from the starting connection point of the current contour line in the next level contour line, connecting all the connection lines, marking the obtained line segment set as a heavy metal pollution path, and taking corresponding heavy metal pollution control measures according to the distribution of soil pH value, soil ventilation and soil water content in the pollution path; the invention realizes clear identification of serious pollution areas and diffusion trends.

The invention relates to the technical field of heavy metal pollution treatment, and particularly discloses a biochar material and method for adsorbing heavy metals in wormcast. The biochar material for adsorbing the heavy metals in the wormcast adopts waste green tea residues as a raw material, and after being soaked in a phosphoric acid solution with the mass concentration of 38-42%, the biochar material is subjected to heat treatment at the temperature of 540-560 DEG C to obtain P-BC powder. The P-BC powder is soaked in a metal salt solution with the total metal ion concentration being 0.8-1.2 mol / L, and under the action of a precipitator, the LDH-coated P-BC material is obtained. The LDH-coated P-BC material is mixed with a ferric chloride hexahydrate solution and a NaBH4 aqueous solution for reaction to obtain the biochar material for adsorbing the heavy metals in the wormcast, so that the fixing and stabilizing effects of the biochar material on the heavy metals in the wormcast are improved.

The invention provides a water environment heavy metal pollution measuring method based on electrochemical analysis. The method comprises the following steps: constructing a linear coefficient comparison set and a constant term comparison set of peak current and concentration of heavy metal ions on a certain stripping volt-ampere peak potential by aiming at different samples in a water environment detected sample set of a certain heavy metal; and then, by constructing a water environment similar sample set of the to-be-measured sample for heavy metal pollution measurement, the measurement concentration of the to-be-measured sample about the heavy metal ions is given. According to the technical scheme provided by the invention, the to-be-detected water environment sample is matched according to the data of a certain heavy metal ion of the detected water environment sample in the past, so that the adaptability of rapidly detecting the heavy metal ions of different water environment samples through the electrochemical detection device is enhanced.

The invention discloses an assessment system for children liver damage caused by atmospheric heavy metal pollution, relates to the technical field of environmental health management, and aims to solve the technical problems that risk assessment is distorted and early warning of liver damage risks cannot be supported due to single-dimensional estimation of an existing assessment system. The data acquisition module is used for acquiring child activity track data, atmospheric heavy metal concentration data, child dynamic physiological parameter data, ground medium heavy metal data and child growth and development stage information; the data processing layer is used for preprocessing the data acquired by the data acquisition layer, the preprocessing comprises privacy desensitization processing, multi-source data format unification and abnormal value intelligent elimination, and the privacy desensitization processing adopts a mode of original data local retention and feature parameter cloud transmission. The method has the advantages of realizing three-dimensional accurate quantification of the children atmosphere heavy metal pollution liver injury risk, generating personalized intervention suggestions and forming an optimized closed loop.

The invention relates to the technical field of particulate matter source analysis, and discloses a refined source analysis method and system.The method comprises the steps that a plurality of pollution sources and dust falling particulate matter sampling points are determined according to soil pollution distribution of a target area and an atmospheric pollution source survey result, by collecting single particle mass spectrum data of pollution sources, sampling points and receptors, constructing a mass spectrum library and combining an ART-2a algorithm and a deep learning model, the heavy metal pollution contribution proportion is accurately analyzed and traced to specific discharge ports of enterprises, and the problem that specific pollution enterprises and working sections cannot be positioned in the prior art is solved. According to the method, a pollution source and an environment receptor are sampled and analyzed by utilizing a single-particle mass spectrometry technology aiming at atmospheric dust fall particles in soil, and the heavy metal in the atmospheric dust fall particles in the soil is finely traced to specific enterprises and working sections by analyzing the heavy metal, so that a fine technical support is provided for soil heavy metal pollution management and control.

The invention discloses a soil heavy metal pollution detection and remediation hardware system based on isotopic tracing, which relates to the technical field of soil and comprises an isotopic tracing module, a heavy metal detection module, a remediation execution module, a real-time monitoring module, an intelligent regulation and control module and a data storage and transmission module, the data storage and transmission module is connected with the isotope tracing module, the heavy metal detection module, the repair execution module, the real-time monitoring module and the intelligent regulation and control module, and transmits data to a remote monitoring center in a wired or wireless communication mode, so that further data analysis and remote control are carried out; through multi-source data fusion and intelligent algorithm optimization, precise positioning, dynamic monitoring and efficient repairing of heavy metal pollution are achieved, the isotope tracing technology can position a pollution source and predict a diffusion path, and the plant and microorganism synergistic repairing efficiency is improved; the system is suitable for industrial pollution sites, farmlands and other scenes, and has remarkable environmental and economic benefits.

The invention provides a heavy metal contaminated soil remediation material, and belongs to the technical field of soil remediation. According to the method, the silicon-magnesium modified sunflower straw biochar and the organic fertilizer (chicken manure) are used for synergistically repairing the chromium and lead heavy metal contaminated soil, the adsorption performance of the modified biochar and the biological absorption effect of the organic fertilizer are used for jointly reducing the absorption of spinach to the heavy metal chromium and lead, meanwhile, the physical and chemical properties of the soil are improved, and the nutrient activity of the soil is remarkably improved. Results show that the effective cation exchange capacity, organic matters and available phosphorus of the soil are improved by synergistic remediation of the modified biochar and the organic fertilizer, the pH value of the soil is reduced (averagely reduced by 0.48), the combined application effect of the modified biochar and the organic fertilizer is more obvious, and the absorption of chromium and lead by the spinach is averagely reduced by 26.04% and 18.22% respectively. The invention provides an effective and practical way for reducing the composite toxicity of plants to various metals such as chromium, lead and the like.

The invention discloses a method for evaluating heavy metal pollution risk in high geological background soil by using biological indexes, and belongs to the field of microbiology and environmental science. The method comprises the following steps: firstly, screening by adopting propionium bromide azide to obtain active microorganisms in soil, extracting DNA of the active microorganisms, carrying out gene high-throughput sequencing on the extracted DNA, screening obtained common microorganisms, and establishing a relationship between relative abundance of the common microorganisms and heavy metals; the heavy metal pollution risk of the soil can be judged according to the relative abundance of the microorganisms in the later period. The method provided by the invention not only improves the microbiological analysis accuracy of the heavy metal contaminated soil with the high geological background, but also provides a new method for heavy metal pollution risk assessment of the heavy metal contaminated soil.

The invention relates to the technical field of pollution risk assessment, and provides an AI-based karst region soil-underground water cooperative pollution assessment system. According to the system, multi-source soil and underground water heavy metal time sequence monitoring data are fused, cross-medium collaborative characterization characteristics are constructed, an enhanced time sequence modeling method with a parameter efficient adaptation capability is introduced, and a composite dynamic loss function oriented to non-stationary pollution evolution characteristics is designed; and collaborative prediction and uncertainty description of the heavy metal pollution states of the soil and the underground water are realized. Furthermore, a prediction result is combined with spatial gridding analysis, a collaborative pollution risk index and a risk zoning result are constructed, technical conversion from pollution evolution modeling to spatial risk assessment and early warning output is realized, and reliable technical support is provided for dynamic early warning, graded prevention and control and environment management decision of heavy metal pollution in the karst region.

The utility model discloses a composite core mold which comprises a lining layer, a metal reinforcing layer and an outer covering layer which are sequentially connected from inside to outside, the axial length of the metal reinforcing layer is smaller than the axial length of the lining layer and the axial length of the outer covering layer, sealing layers are arranged on the two axial end faces of the metal reinforcing layer respectively, and the inner surfaces of the sealing layers are connected with the outer surface of the lining layer. The outer surface of the sealing layer is connected with the inner surface of the outer covering layer, and the metal reinforcing layer continuously stretches across the heavy load bearing area. The metal reinforcing layer with low cost and high bending modulus is additionally arranged between the two fiber layers, so that compared with a traditional pure fiber core mold, the core mold has the advantages that the bending modulus is higher, the cost is low, the bearing limit is larger, the weight is lighter under the condition of the same bearing performance, and the core mold is easier to transport; meanwhile, the sealing layer is arranged to prevent dissimilar metal pollution, and the winding quality of foil products is guaranteed; by ensuring the roundness of the metal reinforcing layer, the processing efficiency of the outer covering layer is improved, and the process difficulty is reduced.

The invention provides a high-activity in-situ crystallization catalyst as well as a preparation method and application thereof, and belongs to the technical field of oil refining catalysts. The preparation method comprises the following steps: firstly, carrying out alkali treatment on kaolin, then mixing with kaolin to obtain modified kaolin microspheres, roasting, and then carrying out in-situ crystallization on the modified kaolin microspheres, a silicon source, sodium hydroxide, a seed crystal and a silicon-aluminum activator, so that the activation degree of silicon dioxide in kaolin is promoted, and meanwhile, timely insertion of active silicon species into a NaY zeolite skeleton in the crystallization process is accelerated; the high-activity in-situ crystallization catalyst is prepared by carrying out ammonium salt and rare earth exchange, roasting and phosphorus or boron modification treatment on the crystallized microspheres, and has the characteristics of strong heavy oil conversion and metal pollution resistance and high total liquid yield when catalyzing heavy oil cracking.

The invention relates to the technical field of environmental science and engineering, and discloses a water body sediment heavy metal pollution diagnosis and risk zoning method, which comprises the following steps of: firstly, performing functional zoning and differentiated point distribution sampling based on hydrodynamic topographic features; secondly, carrying out multi-dimensional index detection on the sediment sample to obtain a multi-dimensional data set containing a chemical occurrence form; secondly, combining a positive definite matrix factorization model with bivariate local space autocorrelation analysis, quantitatively analyzing the contribution of the pollution source and verifying the space fate of the pollution source; then, constructing a two-dimensional risk assessment system based on the chemical occurrence form, and calculating a migration release risk index and a bio-availability risk index; and finally, according to source-sink positioning and risk assessment results, a differentiated partition control strategy is generated. According to the invention, through coupling chemical morphology and spatial analysis, the concealment risk that the total amount does not exceed the standard but the bioavailability is high can be accurately identified, and accurate positioning and migration path verification of the composite pollution source are realized.

The invention discloses a method for reducing metal pollution and improving white pixels of an image sensor, and the method at least comprises the steps: providing an ion implanter which comprises a reaction chamber and an ion source reaction chamber; a substrate is provided, the substrate comprises a pixel area, and the substrate is arranged in the reaction chamber; introducing doped gas and diluent gas into the ion source reaction cavity, wherein the doped gas and the diluent gas are dissociated into ions in the ion source reaction cavity; the flow of the diluent gas is greater than that of the doped gas; injecting the ions into the pixel region of the substrate through an ion injection process; wherein the doping gas is halogen-containing gas, and the diluent gas at least comprises inert gas. According to the method, metal pollution can be reduced, and white pixels of the image sensor are reduced.

The invention provides a method for preparing a biological fermentation heavy metal contaminated soil remediation agent by utilizing ardealite and printing and dyeing sludge, and belongs to the technical field of solid waste recycling. The method comprises the following steps: mixing printing and dyeing sludge, ironmaking solid waste and ardealite, uniformly stirring, granulating, carrying out aging treatment, carrying out high-temperature pyrolysis, and grinding to obtain phosphorus printing carbonized powder; mixing the cordyceps sobolifera mycelium extract, the pandanus elliottii leaf extract and the red velvet extract, and uniformly stirring to obtain an extraction mixture; beta-nicotinamide mononucleotide and galactomannan are mixed and stirred uniformly, and a probiotic agent is obtained; mixing a probiotic agent, the extraction mixture and food powder, and uniformly stirring to obtain enlightening mixed powder; and mixing the heuristic mixed powder with the phosphorus-printed carbonized powder, uniformly stirring, and adding primary rhizosphere compound bacteria for fermentation, thereby obtaining the biological film covering heavy metal contaminated soil remediation agent after fermentation is finished. The efficient utilization of the phosphogypsum and the printing and dyeing sludge is realized through reasonable proportioning, pyrolysis carbonization and primary rhizosphere compound bacteria synergistic fermentation.

The invention belongs to the technical field of sewage heavy metal monitoring, and particularly relates to a sewage heavy metal concentration dynamic monitoring method and sensor based on image gray scale, and the monitoring method comprises the following steps: (1) establishing a database and a standard curve of image gray value and heavy metal concentration; (2) shooting a sewage sample image, synchronously collecting a standard color card during shooting, obtaining a sample-color card composite image, carrying out image recognition, and obtaining a sewage sample image gray value dynamically calibrated by the color card; and (3) substituting the image gray value into a standard curve of the image gray value and the heavy metal concentration or a database, and calculating the heavy metal concentration in the sewage. According to the invention, the cost is low, the heavy metal can be rapidly and dynamically monitored on line in real time by utilizing the image gray difference under different heavy metal concentrations and adopting machine vision correction, and the heavy metal pollution phenomenon can be found in time.