16 results about "Co2 flux" patented technology

The invention relates to a numerical mode simulation method for CO2 flux of high-resolution rice, wheat and corn, which comprises the following steps: calculating a vegetation index and a land surface water index, and carrying out inversion to obtain key vegetation parameters of a land ecosystem; the meteorological data and the topographic data are processed, meteorological field initial and boundary condition files are generated, and CO2 chemical initial and boundary condition files are generated; integrating the gridded artificial source CO2 emission data file; applying the optimized photosynthetic and respiratory action parameters to a photosynthetic and respiratory action calculation formula of the terrestrial ecosystem, and constructing a CO2 flux simulation system of the crop system; outputting the CO2 flux of the rice, the wheat and the corn in the simulation area. The method has the advantages that CO2 flux seasonal change characteristics in the key phenological period in the growth process of rice, wheat and corn are simulated, carbon cycle characteristics in the growth process of crops can be better reflected, and more reliable data support is provided for ecological meteorological research.

The application discloses a high-selectivity high-flux highly-ordered self-assembled mixed-matrix gas separation membrane and a preparation method thereof. The gas separation membrane is prepared from the following steps: taking porous polyacrylonitrile as a base, enhancing surface tension under the protection of a buffer solution by using a silane coupling agent, and in-situ assembling a metal organic framework film by using a surfactant to induce and promote, and modifying the surface by using an ionic liquid. The highly-ordered self-assembled mixed-matrix gas separation membrane synthesized by the application has high orientation, high adsorption and separation performance, and can greatly improve the separation selectivity of CO2 / CH4 and CO2 / N2 under the premise of ensuring the CO2 flux, greatly exceeds the upper limit of 2008 Robertson under the condition of high CO2 permeation rate, and has practical application prospect.

This invention discloses a method and system for differentiating typhoon impacts based on seawater CO2 partial pressure data. The method includes: acquiring marine situation monitoring data during typhoon passage in the target sea area through a multi-source observation platform, constructing a standardized dataset and a climatological background field; using the DBSCAN clustering algorithm to segment water masses, and combining the Man-Whitney U test and correlation analysis to determine the distribution of characteristic typhoon water masses; calculating the seawater CO2 partial pressure anomaly field based on the climatological background field, constructing a typhoon impact index time series, identifying the core impact area, and generating typhoon impact trace paths; subsequently reconstructing seawater CO2 partial pressure grid points, and constructing a spatial map of typhoon impacts; finally, analyzing the spatiotemporal changes in air-sea CO2 flux, assessing carbon sink stability, and generating a typhoon-carbon sink sensitivity zoning map. Using seawater CO2 partial pressure as the core indicator, this method overcomes the limitations of traditional methods and provides reliable technical support for assessing the marine environmental impact of typhoons.

The invention belongs to the technical field of carbon sink estimation, and discloses a global ocean carbon sink estimation method and system considering wave breakage. According to the method, space-time optimization is carried out on empirical coefficients in an air-sea transmission rate model by considering the space-time difference of the marine environment, so that the coefficients used in different sea areas in different seasons are dynamically regulated and controlled, and accurate estimation of large-scale air-sea CO2 flux is realized. According to the method, the empirical coefficient of the air-sea transmission rate model is dynamically adjusted by considering the space-time difference of the marine environment, the influence of wave breaking on the marine carbon sink is quantified based on the dynamic empirical coefficient, the global marine carbon sink is estimated more accurately, and the overall performance of the marine carbon sink is improved. Therefore, a reliable data basis is provided for evaluating the effect of the ocean carbon absorption capacity in slowing down the climate change, and scientific decisions and corresponding measures for coping with the climate change are made in an assisted mode.

The invention relates to the technical field of environmental parameter evolution analysis, in particular to an environmental parameter evolution analysis method based on sparrow search algorithm optimization, which comprises the following steps: recording environmental temperature, CH4 flux and CO2 flux data within a period of time through a flux monitoring system; forming a CH4 / CO2 flux evolution analysis data set by the recorded time, the environment temperature and the CH4 / CO2 flux data; and performing model training, optimization, screening and interpretability analysis on the basis of the CH4 / CO2 flux evolution analysis data set by using a support vector machine (SVM), a random forest (RF) and a neural network (DNN) to obtain a CH4 / CO2 flux evolution analysis model. According to the method, independent evolution analysis models are respectively constructed for CH4 and CO2, evolution laws with different gas fluxes are accurately captured, and parallel training and parameter optimization are performed through three machine learning models with different principles, so that the finally screened optimal model is ensured to have the best generalization ability and stability.

This paper provides a method for diagnosing and analyzing air-sea CO2 fluxes using a physical-biological coupled ocean model. This method achieves high-resolution simulation of the marine ecosystem in the China coastal area (118°E-132°E, 24°N-42°N), accurately simulating the basic structural characteristics of the regional ecosystem, particularly the marine carbon cycle. Based on this, a model post-processing method for air-sea CO2 fluxes has been developed. This automated processing of regional high-resolution physical-ecological coupled ocean simulation data includes the preparation of model input data, evaluation of model results, and visualization. The air-sea CO2 flux diagnostic analysis method is improved by incorporating ocean physical process analysis, analyzing the physical processes that cause changes in the air-sea CO2 flux from a holistic perspective.

The invention relates to the technical field of membrane separation materials, and discloses a composite gas separation membrane as well as a preparation method and application thereof. The composite gas separation membrane comprises a supporting layer, a first functional layer and a second functional layer which are sequentially stacked, wherein the material for forming the first functional layer comprises an amino polymer; the material constituting the second functional layer includes an elastomeric polymer. The composite gas separation membrane comprises a supporting layer, a first functional layer and a second functional layer which are sequentially stacked, the first functional layer and the second functional layer are respectively composed of an amino polymer and an elastomer polymer, every two layers of the separation membrane are firmly combined, the defect rate of the separation membrane can be remarkably reduced, and the composite gas separation membrane can achieve CO2 flux with a high CO2 / N2 separation coefficient, and meanwhile the separation efficiency of the separation membrane is improved. And excellent stability can be maintained in a long-term use process.

The invention relates to the technical field of adsorbents, in particular to a 13X molecular sieve adsorbent and a preparation method thereof. The preparation method comprises the following steps: firstly, performing lanthanum ion replacement treatment on 13X molecular sieve raw powder, then generating an MFI molecular sieve coating layer on the surface of the 13X molecular sieve raw powder, etching by using sodium hydroxide to prepare a mesoporous structure, and then performing hydrophobic modification treatment on the mesoporous structure, so that water molecules are difficult to adsorb by the molecular sieve raw powder and mesoporous surfaces thereof due to a methyl group on the surface, and the molecular sieve raw powder and the mesoporous surfaces are not easy to adsorb; hydrogen bond connection cannot be formed, so that a rapid'adsorption-diffusion 'transfer process cannot be realized in molecular sieve raw powder, the polarity of carbon dioxide is far smaller than that of water molecules, the carbon dioxide cannot be repelled by methyl, and the diffusion of the carbon dioxide in mesopores is far higher than that in micropores due to the existence of the mesopores. Therefore, the carbon dioxide flux in the molecular sieve raw powder is effectively improved, and the carbon dioxide adsorption rate of the molecular sieve raw powder is improved.

This invention relates to a method for estimating soil organic carbon sequestration by crop residue return to the field, comprising: acquiring and processing multi-source data; simulating the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops; extracting the net CO2 flux of MCCs (Mechanical Control Cells) in terrestrial ecosystems; calculating the net assimilated carbon allocation of each component of MCCs during their growth cycle; determining the distribution of biomass carbon in different straw management practices; and calculating the total soil organic carbon sequestration by MCC residue return to the field in all grid units based on the local soil organic carbon conversion rate. The beneficial effects of this invention are: by quantifying the allocation of net assimilated carbon to components such as rhizosphere deposition, crop roots and stubble, collectable straw, and grains, this invention provides crucial support for assessing the carbon cycle and soil organic carbon sequestration potential of farmland ecosystems.

The invention discloses a multi-scale rough structure gas diffusion film and a preparation method thereof. The gas diffusion membrane comprises a supporting layer and a microporous layer, wherein the supporting layer is formed by carrying out fusion molding on polyvinylidene fluoride and NaCl particles of a first size and removing NaCl, and the microporous layer is arranged on the supporting layer and formed by carrying out fusion molding on polyvinylidene fluoride, multi-walled carbon nanotubes and NaCl particles of a second size and removing NaCl. The surface of the gas diffusion film is subjected to solvent heat treatment to form a scaly rough structure, the gas diffusion film has super-hydrophobic performance, the water contact angle is larger than 160 degrees, the rolling angle is smaller than 5 degrees, and the CO2 flux is larger than 1.8 mL * cm <-2 > * min <-1 > * Pa <-1 >. According to the method, a sacrificial template method is combined with solvent heat treatment, the gas diffusion film with multi-scale pore channels and a super-hydrophobic surface is constructed, the gas mass transfer efficiency, the electrolyte infiltration resistance and the long-term operation stability of the gas diffusion film in an electrochemical CO2 reduction reaction are remarkably improved, and the gas diffusion film is suitable for a CO2 electrochemical reduction system under the condition of high current density.

The application relates to the technical field of membrane separation materials, and discloses a separation membrane and a preparation method and application thereof. The separation membrane comprises a support layer, an intermediate layer and a functional layer which are stacked in sequence; the material of the intermediate layer comprises an amino polymer. The separation membrane has high CO2 flux and high CO2 / N2 selectivity.

The invention relates to a soil respiration CO2 flux and delta 13C flux determination method and device, and belongs to the technical field of soil detection.The method comprises the steps that measurement deviation correction is conducted on a gas concentration detection device through standard gas, and the measurement deviation value of the gas concentration detection device is obtained; performing data acquisition on the soil respiration CO2 amount through a gas concentration detection device, and performing data screening on the acquired soil respiration CO2 amount data based on gas chamber exhaust characteristics of the gas concentration detection device to obtain effective acquisition data of the soil respiration CO2 amount in a gas chamber; on the basis of the measurement deviation value of the gas concentration detection device, measurement deviation correction is conducted on effective collection data of the soil respiration CO2 amount in the gas chamber, and the corrected soil respiration CO2 concentration value is obtained; the soil respiration CO2 flux is determined on the basis of the corrected soil respiration CO2 concentration value, and the delta 13C flux is determined on the basis of the 12CO2 flux and the 13CO2 flux in the soil respiration CO2 flux, so that the measurement accuracy of the soil respiration CO2 flux and the delta 13C flux is improved.

The present invention discloses a mesoscale CO2 flux inversion method based on WRF-FLEXPART and WRF-STILT. The method comprises the following steps: first, meteorological data is obtained as input to a WRF model, and the WRF model outputs the meteorological field of the study area; then, CO2 concentration is monitored by monitoring stations, and the CO2 concentration is sorted according to time to obtain an observation sequence; the observation sequence is subjected to outlier removal and window sliding average processing to obtain a CO2 elevated concentration sequence; then, the obtained meteorological field is used as input to the Flexwrf model and the STILT model to obtain a footprint field corresponding to the processed observation sequence; a priori total carbon flux is obtained, and a better posterior total carbon flux is obtained by Bayesian estimation in combination with the footprint field. The method of the present invention does not require manual intervention, that is, the CO2 flux of the surrounding area can be directly solved based on the observation values of the monitoring station, and the method has timeliness and higher inversion accuracy.

The invention discloses a CO2 flux error correction method in a high-humidity environment, and belongs to the field of environment, ecology and signal processing. Comprising the following steps: carrying out synchronous observation through an open-circuit type vorticity related system and a closed-circuit type vorticity related system; respectively acquiring CO2 fluxes measured by the frequency f of the two sets of systems in a preset time period, and comparing the CO2 fluxes of the two sets of systems to obtain a CO2 flux difference value; the two sets of systems calculate covariances according to the pulse quantity of the CO2 signal value intensity and the pulse quantity of the component of the wind speed in the vertical direction, and the covariances of the two sets of systems are compared to obtain the difference value of the covariances; calculating a correction coefficient of the CO2 flux data according to the CO2 flux difference value and the covariance difference value; and correcting the CO2 flux according to the correction coefficient of the CO2 flux data. According to the invention, the data quality of CO2 flux observation of a vortex-related system in a high-humidity environment is greatly improved, and the application range of a vortex-related technology in ocean and inland water environments is expanded.

The invention relates to a method for estimating the organic carbon sequestration amount of crop residue returning soil. The method comprises the following steps: acquiring and processing multi-source data; simulating photosynthesis carbon assimilation quantity of main grain crops and CO2 flux released by respiration; extracting the net CO2 flux of MCCs crop types in the terrestrial ecosystem; calculating the net assimilation carbon distribution amount of each component of the MCCs in the growth cycle; determining distribution conditions of biomass carbon in different straw management practices; according to the local soil organic carbon conversion rate, the total organic carbon sequestration amount of the MCCs residue returning soil of all the grid units is calculated. The method has the beneficial effects that by quantifying the deposition of net assimilation carbon to rhizosphere, crop roots and stubbles, and the distribution amount of components such as straws and grains, key support is provided for carbon circulation of a farmland ecosystem and soil organic carbon sequestration potential evaluation.

The invention relates to the technical field of geological analysis, in particular to an artificial intelligence modeling analysis method for natural gas hydrate real-time monitoring data, which comprises the following steps: establishing a plurality of machine learning models for learning change rules of hydrate monitoring data; optimizing each machine learning model in a test set by using a sparrow search algorithm to obtain a plurality of optimized machine learning models; and performing prediction performance comparison on the multiple optimized machine learning models in the prediction set, and screening out an optimal machine learning model for hydrate monitoring data prediction analysis. According to the method, three machine learning models are built to learn change rules of wellbore data, frozen soil zone thickness, hydrate in-situ formation and decomposition and ecological evolution parameters, hyper-parameters of the machine learning models are optimized by adopting a sparrow optimization algorithm, and formation temperature, pressure distribution, frozen soil zone thickness and ecological evolution parameters are predicted. The CH4 concentration in the water body in the hydrate formation and decomposition process, and the environmental parameters CH4 and CO2 flux.