1043 results about "Co2 concentration" patented technology

The invention relates to the technical field of pepper breeding regulation and control, and discloses a pepper breeding isolation shed control system based on the Internet of Things. The system comprises an environment data acquisition module, a user behavior analysis module, an isolation shed partition module, a dynamic baseline generation module, an abnormal interaction detection module, a root node decision module and a recommendation chain construction module. The environment data acquisition module acquires temperature, humidity, illumination intensity and carbon dioxide concentration data in the greenhouse in real time; the user behavior analysis module analyzes a user historical regulation and control instruction; the isolation shed partition module divides regulation and control sub-regions according to environmental differences; a dynamic baseline generation module generates a dynamic environment parameter baseline for each sub-region; the abnormal interaction detection module identifies abnormal environment fluctuation and instructions; a root node decision module screens a root node area with most significant fluctuation; the recommendation chain construction module constructs a multi-level regulation and control recommendation chain. According to the system, the accuracy and intelligence of environment regulation and control of the isolation shed are improved, and the pepper breeding requirement is met.

The invention relates to a method for constructing a high-resolution atmosphere carbon dioxide concentration data set based on XGBoost-BO, and belongs to the technical field of environment monitoring and artificial intelligence modeling. The method comprises the following steps: preprocessing OCO-2 satellite data and multi-source auxiliary data, and fusing the preprocessed OCO-2 satellite data and multi-source auxiliary data to obtain a new data set; a Bayesian optimization method is adopted to search for an optimal hyper-parameter, a target function is optimized through second-order Taylor expansion, a regular term is introduced to control the complexity of the model, and ten-fold cross validation is used to evaluate the performance of the model; quantizing the contribution degree of each feature to model prediction through a tree SHAP method, and analyzing global feature importance ranking and feature contribution distribution of individual samples; and performing model verification by using the test set and the site actual measurement data. According to the method, the problems that an existing model-based reconstruction method is insufficient in interpretation and prone to falling into local optimum are solved, and the temporal-spatial resolution of CO2 concentration monitoring can be improved.

The invention discloses an ecological restoration area carbon sink increment real-time prediction method and system based on artificial intelligence, and the method comprises the following steps: multi-source data collection: obtaining a monthly vegetation coverage image through a satellite remote sensing platform, collecting the sensor data of soil temperature and humidity, air CO2 concentration and the like through a laid ground sensor network, and carrying out the real-time prediction of the carbon sink increment of an ecological restoration area; adopting an unmanned aerial vehicle laser radar to obtain vegetation canopy point cloud data according to a preset period, and collecting biomass actual measurement data of a restoration area in a historical preset age limit; preprocessing data, performing radiometric calibration, atmospheric correction and cutting splicing on a monthly vegetation coverage image acquired by a satellite remote sensing platform, and extracting a vegetation coverage and vegetation index time sequence; denoising, ground point separation and single tree canopy segmentation are carried out on vegetation canopy point cloud data acquired by the unmanned aerial vehicle laser radar, and the height and crown breadth of single plant vegetation are calculated. According to the invention, carbon sink increment prediction can be realized more accurately.

The invention discloses an online analysis system based on hydrogen and methane expiration monitoring, and belongs to the technical field of respiration monitoring. Comprising a zero calibration module used for obtaining a first collection environment background carbon dioxide concentration; the original signal acquisition module is used for acquiring an expiration sample; the data processing module is used for processing the original signal data stream; the signal processing module is used for outputting the filtered concentration signal; the signal compensation module is used for obtaining the compensated hydrogen and methane concentration; the secondary zero calibration module is used for acquiring a reference carbon dioxide zero point; the baseline correction module is used for carrying out baseline correction; and the model building module is used for outputting trend judgment. By means of the online hydrogen and methane expiration analysis system, the technical effect that high-concentration precision is still kept under the expiration volume fluctuation and sensor nonlinear conditions is achieved, and the problem of measurement deviation caused by volume change, nonlinear response and carbon dioxide zero drift in the prior art is solved.

A system may include a flow valve coupled to a gas inlet of a landfill gas system and a pump coupled to the flow valve and configured to draw gas from the landfill gas system via the gas inlet. The system may further include an oxygen sensor comprising at least one laser configured to detect oxygen concentration in the gas, a carbon dioxide sensor comprising at least one infrared light source configured to detect carbon dioxide concentration in the gas, and / or one or more chemical sensors configured to sense concentrations of a respective one or more chemicals in the gas. A microprocessor may determine sensed data including at least the oxygen concentration, the carbon dioxide concentration, concentrations of the one or more chemicals, the static pressure, the atmospheric pressure, and / or a differential pressure, and communicate the sensed data to a mobile control device.

The invention discloses a cordyceps sinensis intelligent bionic cultivation control system and method based on the Internet of Things, and the method comprises the steps: collecting the temperature and humidity, gas concentration, illumination intensity and larva behavior data of a cordyceps sinensis matrix through a sensor network, and carrying out the fusion through an edge calculation gateway, and generating a dynamic environment map; constructing a plateau ecological digital twinborn model based on the dynamic environment map in combination with historical meteorological data and a host-strain interaction rule, and generating a staged control time sequence; based on a staged control time sequence, temperature and humidity coupling compensation is carried out through a feedforward-feedback composite algorithm, and actuator linkage is adjusted through fuzzy PID; aI vision is used for identifying a larva infection window period and accurate spraying is carried out, and hypha infection is monitored in combination with a near infrared spectrum to dynamically adjust the CO2 concentration; and constructing an LSTM (Long Short Term Memory) model to predict the growth risk in combination with a dynamic environment map and insect body monitoring data, and actively intervening in an abnormal environment. According to the invention, high-precision, dynamic and intelligent regulation and control of the growth environment of cordyceps sinensis are realized.

The invention discloses a capture method for self-adaptive carbon dioxide concentration regulation and control, and belongs to the technical field of gas separation and capture. The method comprises the following steps: monitoring carbon dioxide concentration in real time through a gas sensor; dynamically adjusting adsorption parameters according to the concentration change, wherein the adsorption parameters comprise three working states including a low-flux adsorption mode, a self-adaptive adjustment mode and an enhanced capture mode; when the concentration is low, the airflow speed is reduced to 0.1-0.5 m / s; when the concentration is medium, the airflow speed is dynamically adjusted and the temperature of the adsorption bed is controlled through a PID controller; when the concentration is high, measures such as pressure increasing, temperature reducing or high-capacity adsorbent switching are taken; in the desorption stage, carbon dioxide is released in a variable-temperature or variable-pressure mode. The method solves the problems that an existing carbon dioxide capture system is low in energy efficiency due to fixed parameter control and cannot automatically adjust the adsorption rate under the concentration fluctuation working condition, the operation parameters can be automatically optimized according to the environment concentration change, and the capture efficiency and the energy utilization rate are remarkably improved.

The invention relates to the technical field of mine environmental protection, and discloses a gravel aggregate mine carbon emission real-time monitoring and metering method, which comprises the following steps: S1, multi-source sensing, including mining blasting monitoring, ore transportation monitoring and aggregate processing monitoring; s2, edge calculation, including data preprocessing, dynamic compensation calculation and local storage and communication; in the dynamic compensation calculation, the CO2 concentration is output and corrected in real time through a dynamic compensation algorithm, and the dynamic compensation algorithm comprises particulate matter dust drop, temperature and humidity deviation and vibration compensation; and S3, cloud platform processing is carried out, block chain evidence storage, carbon sink deduction calculation and early warning control are carried out, and the carbon sink deduction calculation is vegetation carbon sink absorption amount calculation deduction and waste rock recycling carbon emission reduction calculation deduction according to satellite data. The edge calculation layer adopts a dynamic compensation algorithm, temperature and humidity, vibration and particulate matter compensation items are fused in real time, and the hysteresis bottleneck of accounting is solved; a satellite-ground fusion deduction mechanism is adopted to construct a judicial-level trusted data chain.

The invention discloses a soil microorganism carbon utilization efficiency determination method, and relates to the technical field of carbon utilization efficiency determination, and the method comprises soil sample pre-culture, multi-source 18O isotope gradient labeling, dynamic gas monitoring, microorganism respiration rate dynamic correction, and microorganism growth rate and carbon utilization efficiency acquisition. By labeling multi-source isotopes and quantifying contributions of different oxygen sources to microorganism DNA synthesis, underestimation of the carbon utilization efficiency caused by a traditional single labeling method is avoided, the problem of limitation existing in the current soil microorganism carbon utilization efficiency determination process is solved, the inhibition effect of too high local concentration on microorganism metabolism is reduced through gradient labeling, and the accuracy of soil microorganism carbon utilization efficiency determination is improved. The method has the advantages that marking uniformity is improved, multiple groups of soil samples are arranged, real-time change of microbial respiration is captured by means of dynamic monitoring, influence of isotope fractionation on carbon dioxide concentration calculation is eliminated, instantaneous errors of traditional static measurement are avoided, and accuracy of analysis results is improved to a certain extent.

The invention provides a warehousing wheat mildew early warning system and method based on a multi-parameter sensor, relates to the technical field of wheat mildew early warning, and realizes real-time monitoring and early warning of warehousing wheat mildew by combining the multi-parameter sensor and a gas detection technology. The system can identify the carbon dioxide concentration change during wheat storage, position a mildew risk area, and improve the identification precision and the processing efficiency. And the system can predict the change of the internal temperature and humidity by utilizing a relation model of the environment and the internal parameters, so that the perspectiveness and the adaptability of mildew risk judgment are improved. A comprehensive risk coefficient is generated on the basis of carbon dioxide concentration change and internal temperature and humidity change prediction, the storage environment can be comprehensively monitored and predicted through the multi-dimensional evaluation mechanism, reliable data support is provided for managers, and comprehensive risk prediction and coping strategies are provided; and the intelligent level and foresight of warehouse management are enhanced, so that the loss caused by wheat mildew is reduced.

The invention relates to a medical device for evaluating physiological parameters of a respiratory system, and the device comprises a sampling device which is used for collecting detected exhaled gas after a rising inflection point of carbon dioxide; the gas sensor comprises a nitric oxide sensor and a carbon dioxide sensor; the processor is used for receiving the gas signal generated by the gas sensor; the processor is configured to establish a linear expression for calculating a risk parameter R according to the detected carbon dioxide concentration and nitric oxide concentration; the linear expression of the risk parameter R is shown in the specification; wherein the parameter is set as a constant; the parameter is nitric oxide concentration; the parameter is carbon dioxide concentration; and the parameter is a nitric oxide dynamic change rate function. Compared with the prior art, the method provided by the invention provides a more comprehensive evaluation capability for airway inflammation and abnormal ventilation.

The invention provides a concrete carbon sequestration process parameter optimization method, and belongs to the technical field of concrete carbon sequestration. Chemical component data and real-time parameters are input into a carbonization parameter intelligent regulation and control model to obtain regulation values of carbon dioxide concentration, reaction temperature, reaction pressure and water content, and a carbonization reactor is dynamically regulated and controlled; when the carbonization depth is greater than 20mm and the carbon sequestration amount reaches more than 80% of a theoretical maximum value, completing carbonization treatment and recording a process optimization result, and training an intelligent regulation and control model through a parameter regularization framework based on adaptive weight attenuation so that the intelligent regulation and control model can output an optimal parameter adjustment value according to the chemical component difference of the raw material and the real-time change of the carbonization process; the technical problem that the carbon sequestration efficiency is unstable due to the fact that waste concrete carbon sequestration process parameters cannot be dynamically optimized and adjusted according to the chemical component difference of raw materials and the real-time change of the carbonization process is solved.

Embodiments include a method of diagnosing gastroparesis or suspected gastroparesis, the method comprising: obtaining data representing a time series of readings from gas sensing apparatus housed within a ingestible capsule device orally ingested by a subjected; processing the readings to detect one or more gastroparesis indicator spikes in the CO2 concentration with respect to time; based on the detected one or more gastroparesis indicator spikes in the CO2 concentration with respect to time, diagnosing gastroparesis or suspected gastroparesis.

The utility model relates to the technical field of mineralizing bacteria equipment, in particular to an oil reservoir CO2 mineralizing bacteria activity continuous monitoring device which comprises an incubator filled with a culture medium for culturing mineralizing bacteria. The air outlet end of the air supply assembly is located on the lower side in the incubator; the carbon dioxide concentration monitoring assembly is mounted at the upper end part of the incubator; the strain concentration monitoring assembly is mounted on the side wall of the incubator and is communicated with the incubator; the control assembly is electrically connected with the air supply assembly, the carbon dioxide concentration monitoring assembly and the strain concentration monitoring assembly. The activity of mineralized bacteria can be rapidly and continuously monitored, and the monitoring efficiency is improved.

The invention belongs to the technical field of smart buildings, and relates to a green energy-saving building energy consumption real-time monitoring and intelligent optimization system and method based on the Internet of Things, and the system comprises a sensing layer which comprises an environment sensor group which collects the temperature, humidity, illumination intensity and CO2 concentration; the non-intrusive electric energy monitoring module measures equipment current through a Rogowski coil, and the precision is + / -0.5%; the equipment state acquisition terminal is used for acquiring the frequency of an HVAC compressor and the state of a lighting switch; the network layer comprises a multi-protocol edge gateway which supports the conversion from ZigBee / LoRa / Modbus to an MQTT protocol; the block chain evidence storage module is used for generating an SHA-256 hash value for the energy consumption data and uploading the SHA-256 hash value to the chain; the platform layer comprises a digital twin engine which is used for generating an energy consumption three-dimensional thermodynamic diagram based on a BIM model; the optimization control core is composed of an LSTM load prediction unit and an NSGA-II multi-objective optimization unit. The energy efficiency leap of 12-18% comprehensive energy saving (far exceeding the average level of 5-8% in the industry) is realized through a technical chain of'accurate perception-intelligent decision-making-closed-loop control '.

The invention relates to the technical field of granary monitoring, and discloses a granary storage environment adaptive supervision system and a control method.The system comprises an environment monitoring module, an intelligent analysis module, a supervision execution module and a cloud learning platform. Comprising temperature, humidity, carbon dioxide concentration and pest activity data, data preprocessing and feature extraction processing are carried out, accuracy and feature effectiveness of environment data are guaranteed, meanwhile, a granary environment original data set is generated in time through real-time transmission and preliminary verification, monitoring comprehensiveness and reliability are guaranteed, and a granary environment monitoring system is established. A high-quality data basis is provided for environment state evaluation; by comparing the granary environment characteristic data with the preset environment safety threshold value, the comprehensive environment state index is generated, and the safety state, the early warning state and the dangerous state are divided, so that the system can intelligently identify the environment abnormity level.

The invention relates to the related technical field of carbon dioxide detection, in particular to a carbon dioxide leakage detection device which comprises a gas chamber, an infrared light source, an optical filter and a detector. A first-stage connecting lug plate and a second-stage connecting lug plate are integrally formed at ports of the front shell and the rear shell respectively, the first-stage connecting lug plate and the second-stage connecting lug plate are positioned and connected through a first-stage bolt and a first-stage nut, and a mounting bracket is fixedly mounted on the back surface of the gas chamber; external air is pumped into the gas chamber through the air pump, then infrared light is emitted through the infrared light source, carbon dioxide in the gas can absorb infrared light of a specific wave band in the infrared light, then the infrared light irradiates the detection end of the detector through the light filter, the detector detects and analyzes the infrared light, and the infrared light is detected and analyzed through the infrared light source. Therefore, the concentration of carbon dioxide in the air is monitored in real time, and personal safety is effectively guaranteed.

The invention discloses an off-line carbonate cluster isotope sample preparation system and preparation method, the system adopts a main controller and a plurality of sub-controllers to work cooperatively, parameters such as temperature, pressure, gas flow direction and the like are accurately controlled, and the stability and repeatability of sample preparation are ensured; an SPR gas sensor and a fluorescent gas sensor are arranged, CO2 concentration and pressure changes are monitored in real time, accurate data support is provided for a main control machine, and dynamic adjustment and optimization are achieved; a multi-stage cold trap design is adopted, and liquid nitrogen and a methanol-liquid nitrogen mixture are combined for cooling, so that impurity gas is effectively separated, and high purity of final CO2 gas is ensured; the system adopts a modular design, is simple and convenient to operate, is easy to maintain and upgrade, and has good expansibility and universality.

The invention provides a crude helium storage and recycling system for a cryogenic helium extraction process and a recycling control method, and relates to the technical field of helium production. The crude helium storage and recycling system for the cryogenic helium extraction process comprises a membrane separation device, a permeable gas supercharging device, a pressure swing adsorption device, a low-temperature adsorption device, a first storage tank group, an unloading device, a second storage tank group, a first detection unit, a second detection unit, a first recycling loop, a second recycling loop, a third recycling loop and a control device. According to the technical scheme, the first detection unit is arranged to monitor the concentration of methane and carbon dioxide in the crude helium at the outlet of the pressure swing adsorption device, high-concentration impurities can be effectively prevented from entering the low-temperature adsorption device, the problem of equipment freezing and blocking caused by condensation is avoided, the crude helium recycling path is dynamically adjusted, and the recycling efficiency of the crude helium is improved. And the gas meeting the standard is sent to the next stage for treatment, so that the helium quality and the production efficiency can be improved in the cryogenic helium extraction process.

The invention relates to the technical field of low-temperature methanol washing, in particular to an energy-saving low-temperature methanol washing process which comprises the steps of acid gas removal of raw material gas in an absorption tower, desorption and regeneration of a rich solution after the acid gas is absorbed, and cyclic utilization of a methanol solution. Through functional differentiation of a sulfur-containing semi-barren solution and a sulfur-free semi-barren solution, the circulation amount of lean methanol is reduced compared with that of a traditional process, the load and steam consumption of a thermal regeneration tower are directly reduced, the sulfur-containing semi-barren solution selectively absorbs H2S in a desulfurization section, 50-60% of CO2 is removed, the load of a decarburization section is reduced, the total number of tower plates of an absorption tower is reduced, and the equipment investment is reduced; the desulfurization section is divided into two or three sections and is provided with a cooler, the temperature of each section is strictly controlled to be-50 DEG C to-60 DEG C, efficiency reduction caused by heat absorption and release is avoided, and the decarburization section adopts barren liquor and sulfur-free semi-barren liquor combined absorption, so that the concentration of CO2 in purified gas is stabilized below 20ppm, and the requirements of high-end processes such as synthesis ammonia and coal hydrogen production on gas purity are met.

The invention belongs to the field of agricultural pest detection, and particularly relates to an underground grub pest detection system and method based on deep learning multi-mode. Firstly, in an area suspected to have underground grub pests, the activity of underground grubs is enhanced in a targeted manner by arranging a specific stimulation module. After the grub activity is enhanced, sound signals and carbon dioxide concentration changes generated by the grub activity are captured by using a data acquisition module, preprocessing and feature extraction are performed, and analysis and processing are performed in combination with a deep learning model, so that the existence condition, the number and the underground rough distribution position of underground grubs are accurately judged. According to the scheme, by actively enhancing the activity of grubs and combining the multi-mode detection and deep learning technology, the accuracy and reliability of detection are effectively improved, insect pests can be warned in advance, an efficient and accurate solution is provided for underground pest prevention and control in agricultural production, the prevention and control efficiency is improved, the prevention and control cost is reduced, and the negative influence on the environment is reduced.

The invention provides a method, a device and equipment for determining greenhouse environment parameters, and belongs to the technical field of computer information processing. The greenhouse environment parameter determination method comprises the following steps: acquiring real-time data of temperature, humidity, illumination and carbon dioxide concentration of a greenhouse; processing real-time data of temperature, humidity, illumination and carbon dioxide concentration to obtain greenhouse environment parameters; inputting the greenhouse environment parameters into a greenhouse environment control model for processing to obtain greenhouse control parameters; the greenhouse environment control model processes the input vector through a control function to obtain an intermediate result, and the intermediate result is linearly weighted to obtain greenhouse control parameters; the greenhouse control parameters are used for controlling the operation state of the greenhouse environment regulation and control equipment. According to the technical scheme, the greenhouse environment parameters are monitored in real time, the regulation and control equipment is controlled to act in time, the regulation accuracy of the greenhouse temperature and humidity is improved, and the greenhouse environment control effect is improved.

The invention relates to the technical field of carbon dioxide recovery, in particular to efficient carbon dioxide recycling equipment based on a beer production process, which is used for realizing the following steps: acquiring local time lag between adjacent preset positions in a target absorption tower, obtaining the carbon dioxide concentration of different preset positions in the target absorption tower in the current observation time period; determining a concentration relative change index between every two adjacent preset positions; predicting an outlet concentration prediction value corresponding to the next overall time lag; adjusting the power of a pump in the target absorption tower; if the current power adjustment value is smaller than or equal to the preset standard power value, the current spraying redundancy degree is determined, and the opening degree of the spraying valve is adjusted based on the current spraying redundancy degree. By analyzing the carbon dioxide concentration in the current observation time period, self-adaptive adjustment of the pump power and the opening degree of the spraying valve is achieved, and therefore the overall efficiency of carbon dioxide recovery is improved.

The invention discloses a physical constraint-based multi-mode indoor carbon dioxide concentration prediction method, which comprises the following steps of: acquiring time sequence environment data of indoor carbon dioxide concentration, temperature and humidity, and obtaining indoor panoramic image data; performing time sequence feature extraction on the time sequence environment data, and extracting image high-level visual features through a pre-trained image model; in the multi-modal fusion process, a conflict decoupling gating fusion network is introduced to detect and suppress multi-modal time conflicts between static visual information and dynamic environment parameter changes, and contribution weights of an environment modal and a visual modal are dynamically adjusted through a self-adaptive gating mechanism; a time-delay perception cross-modal attention network is introduced to predict and model a physical delay characteristic between a visual event and an environmental parameter response, and cross-modal causal alignment is realized through lag distribution prediction and a weighting mechanism; and inputting the multi-modal features after conflict decoupling and time-lag alignment into a prediction network, and outputting a future indoor carbon dioxide concentration prediction result.

The invention discloses a mouse space experiment cabin, and relates to the technical field of space cabins, the mouse space experiment cabin comprises a mouse living cabin, the mouse living cabin is internally provided with a closed living space, and the living space is used for accommodating a mouse; the sensor assembly is fixedly arranged in the mouse living cabin and can detect temperature, humidity, air pressure and gas component data in the living space; the gas regulation and control assembly is communicated with a living space in the mouse living cabin through a pipeline provided with a valve, and can respectively introduce a set amount of oxygen and air into the mouse living cabin and purify and circulate waste gas in the mouse living cabin; the thermal control device is arranged in the mouse living cabin and can control the temperature in the mouse living cabin; the electric control device can receive data of the sensor assembly and control the working states of the gas regulation and control assembly and the thermal control device according to the data. Key environment parameters such as the temperature, the humidity, the oxygen concentration and the carbon dioxide concentration of the experiment module can be accurately regulated and controlled.

The invention provides a fixed emission source CO2 monitoring method based on an adaptive compensation model. The fixed emission source CO2 monitoring method comprises the following steps: step S1, acquiring mixed gas of various CO2 concentrations; s2, collecting temperature data and humidity data of each mixed gas; s3, establishing a correction coefficient regression model corresponding to each CO2 concentration, and homogenizing each correction coefficient regression model to obtain a first correction coefficient; or controlling the infrared flue gas analyzer to establish a correction coefficient linear model corresponding to each CO2 concentration based on the temperature data and the humidity data, and homogenizing each correction coefficient linear model to obtain a second correction coefficient; and S4, acquiring a first CO2 monitoring value monitored by the electrochemical flue gas analyzer at the current moment or a second CO2 monitoring value monitored by the electrochemical flue gas analyzer, and combining the first correction coefficient or the second correction coefficient to obtain a corresponding CO2 monitoring accurate value. The method has the beneficial effect that the accuracy of CO2 flow monitoring can be improved.

The invention relates to the technical field of building equipment design, discloses a residence-based fresh air system generation method, device and equipment and a storage medium, and is used for improving the design efficiency of a fresh air system. The residence-based fresh air system generation method comprises the steps that house type information of a residence is acquired, wherein the house type information comprises actual room layout, house type area information, room clear height, room function distribution and resident number information; on the basis of the house type information, the fresh air volume is calculated through a ventilation frequency method and a carbon dioxide concentration method, and the larger value in calculation results is selected as the target fresh air volume; determining a starting position and a final position of the fresh air system according to the house type information; grid division is performed on the actual room layout based on the starting point position and the ending point position, and a target path is generated; and generating a target fresh air system according to the target path and the target fresh air volume.

To provide a curing method for concrete pavement for proactively promoting carbonation (neutralization) at a construction site for concrete pavement used in road pavement.SOLUTION: A curing method for concrete pavement (1) includes a process for performing carbonation curing from a bottom surface (1A) of the concrete pavement (1). The carbonation curing process includes the following steps: supplying carbon dioxide gas (CO2 gas) to a construction site; measuring the CO2 concentration; and controlling the CO2 concentration (e.g., maintained within an appropriate range of 0.5% to 80%) of the CO2 gas supplied in the supply step on the basis of the CO2 concentration measured in the measuring step. Preferably, the process includes measuring the temperature and / or humidity of the atmosphere at the construction site and controlling the temperature and / or humidity of the supplied CO2 gas on the basis of the measurement results.SELECTED DRAWING: Figure 1

The invention relates to the technical field of edible mushroom planting, and discloses a culture method of agaricus bisporus. The culture method comprises the following steps: 1) a composting stage: inoculating an agaricus bisporus strain on a culture material for composting fermentation; 2) a soil covering stage: forming a soil covering layer by soil covering, performing first-time water supplementing and mycelium stimulation, and performing second-time water supplementing and complex mycelium culture; and 3) a cooling stage: promoting fruiting by controlling an air temperature reduction program and a CO2 concentration reduction program. By controlling the air temperature and the CO2 concentration reduction program in the fruiting management stage, large mushrooms and small mushrooms appear at the same time, are well-proportioned in height and grow in a layered mode, sufficient growth space is provided for growth of agaricus bisporus, artificial bud thinning treatment is not needed in the later period, the labor cost is reduced, and the agaricus bisporus yield is improved. Meanwhile, the yield of the agaricus bisporus is improved.

The invention discloses a metal organic framework film with a Turing structure as well as a preparation method and application of the metal organic framework film. According to the membrane material, a polymer hollow fiber membrane is used as a supporting layer, a metal organic framework Turing structure layer with periodic wrinkle patterns grows on the surface in situ, and a gas diffusion path is optimized by regulating and controlling the wrinkle degree and the surface appearance; the membrane material shows excellent performance in CO2 / N2 and CO2 / CH4 separation, the CO2 permeation flux can reach 1100 GPU, the CO2 / N2 and CO2 / CH4 selectivity can reach 60, and due to a special diffusion channel, the membrane material has a remarkable separation effect under the condition of low CO2 concentration; the preparation process is simple, is suitable for industrial grade gas separation, and provides a new strategy for efficient carbon capture and utilization.