615 results about "Carbon neutrality" patented technology

The invention discloses a vertical large language model training method and system in the carbon neutralization field, and the method comprises the following steps: collecting data of the carbon neutralization field, carrying out the data preprocessing, constructing a carbon neutralization field knowledge base, and updating the carbon neutralization field knowledge base through a dynamic updating mechanism; performing dynamic semantic partitioning and vectorization coding on the text of the carbon neutralization domain knowledge base, and storing the text into a vector database; performing staged fine tuning on the pre-trained large language model based on a low-rank adaptation technology, wherein the fine tuning comprises general instruction fine tuning and carbon neutralization field professional fine tuning; a retrieval enhancement generation mechanism is adopted, knowledge fragments related to user query are retrieved through a vector database, and a large language model is input to generate answers. Compared with the prior art, the method has the advantages that the answer reliability is improved through conflict detection and source tracing, so that the large language model can more accurately adapt to knowledge requirements in the carbon neutralization field.

The invention discloses tempered low-emissivity coated glass, which comprises a tempered glass substrate and a composite metal film layer laminated on the substrate, and is tempered coated glass with three metal silver film layers. After a common glass substrate is plated with a composite metal film layer, toughening treatment is carried out, and after toughening treatment, all the metal film layers reflect, interfere and refract light, so that the glass is light blue in the sun, and the decoration and energy-saving effects are good; the visible light transmittance is high, the outdoor visible light reflectivity is low, the solar energy transmittance is low, and the solar energy reflectivity is high; the prepared hollow glass has better energy-saving effects of light control, heat insulation, heat preservation and the like, enables buildings to be closer to nature, is used for near-zero-energy-consumption buildings, enables the buildings to meet the requirements of the national standard GB55015-2021 General Standard for Energy conservation and Renewable Energy Utilization of Building, and has great contribution and significance on carbon neutralization and carbon peak reaching of the buildings.

The invention discloses a carbon neutralization target-oriented electricity-carbon-green certificate multi-target scheduling optimization method and system, and relates to the technical field of carbon neutralization control, and the method comprises the following steps: obtaining first data of a target energy storage unit, constructing a constraint generation network, and dynamically updating an energy storage operation constraint domain based on a dynamic time warping algorithm; based on the updated operation constraint domain, establishing an electricity-carbon coupling model, extracting a nonlinear mapping relation between an electric energy output behavior and carbon emission intensity, and outputting a dynamic incidence matrix through a multi-dimensional time sequence predictor; constructing a carbon flow distribution topological graph according to the dynamic incidence matrix, and obtaining an optimal carbon flow path through a Dijkstra algorithm; based on the operation constraint domain and the optimal carbon flow path, establishing a multi-subject collaborative decision-making mechanism, solving a multi-target unit equilibrium solution by adopting a distributed alternating direction multiplier method, and generating a global scheduling instruction set; according to the method, a carbon flow topology and dynamic constraint domain cooperation mechanism is constructed, so that efficient solving of a multi-main-body carbon response optimization scheduling problem is realized.

The invention relates to the technical field of sewage plant-oriented carbon neutralization regulation and control scheme design, in particular to a sewage plant-oriented carbon neutralization regulation and control method and a sewage plant-oriented carbon neutralization regulation and control system. The method comprises the steps of collecting water quality, energy consumption and gas emission data in real time through a multi-source sensor, inputting the data into a space-time diagram convolutional network to predict a carbon emission trend after edge computing node cleaning, and dynamically optimizing an aeration rate and a sludge reflux ratio based on a fuzzy PID controller. A whole-process carbon footprint is tracked by adopting a life cycle evaluation method, a multi-target compensation strategy is generated in combination with an improved NSGA-III algorithm, and photovoltaic, biogas and green power resources are scheduled preferentially. A digital twin platform and a block chain evidence storage module are innovatively integrated, the former calibrates model parameters in real time, and the latter generates a non-tampering carbon neutralization voucher. According to the method, the problems of one-sided data, regulation and control lag and insufficient credibility of a traditional method are solved, and minute-level sensing, prediction and offset closed-loop control of carbon emission in the sewage treatment process is realized.

The invention relates to the technical field of power systems, in particular to a carbon neutralization-oriented peak-valley electricity price dynamic excitation mechanism design and user response prediction system, which comprises a data acquisition module, a load characteristic analysis module, a dynamic regulation and control module, a sample evaluation module and an execution module. The system obtains power grid operation, user power consumption behaviors and new energy power generation data through a multi-source data access interface, and realizes partition load optimization and new energy adaptation in combination with a load classification model, a dynamic excitation framework and an energy storage optimization scheduling scheme. The method can accurately predict the user response, optimizes the peak-valley electricity price strategy, improves the new energy consumption capability, and assists the realization of a carbon neutralization target.

The invention discloses a preparation method of tempered low-emissivity coated glass. The preparation method comprises the following steps: sintering a target material, carrying out moisture removal and degassing pretreatment on glass, carrying out coating treatment and tempering treatment, and laminating a composite metal film layer on a tempered glass substrate to prepare the tempered coated glass with three metal silver film layers. According to the method, after a common glass substrate is plated with the composite metal film layers, toughening treatment is carried out, and after toughening treatment, the metal film layers reflect, interfere and refract light, so that the glass is light blue in the sun, and the decoration and energy-saving effects are good; the visible light transmittance is high, the outdoor visible light reflectivity is low, the solar energy transmittance is low, and the solar energy reflectivity is high; the prepared hollow glass has better energy-saving effects of light control, heat insulation, heat preservation and the like, enables buildings to be closer to nature, is used for near-zero-energy-consumption buildings, enables the buildings to meet the requirements of the national standard General Standard for Energy conservation and Renewable Energy Utilization of Building, and has great contribution and significance on carbon neutralization and carbon peak reaching of the buildings.

The invention provides a carbon neutralization evaluation method for an ecological park, and the method comprises the steps: obtaining the basic data of various carbon assets in the ecological park, and the basic data comprises the natural ecological system carbon sink capability and human activity carbon emission intensity data; according to the carbon asset basic data, a time sequence analysis method is adopted to carry out modeling on the change trend of the carbon sink capacity and the carbon emission intensity, and a change trend model is obtained; modeling the spatial distribution of the carbon reserves and the carbon flux by utilizing a geographic information system technology and combining a change trend model to obtain a spatial distribution model; key variables are extracted from the spatial distribution model, and the effects of different factors on the carbon assets are quantified by adopting a multiple regression analysis method; acquiring carbon asset monitoring data, evaluating data quality, and if an abnormal value exists, performing correction by adopting a data cleaning algorithm; and according to the corrected carbon asset data, adopting a random forest model to predict the carbon sink capacity and the carbon emission intensity, and generating a dynamic evaluation result.

The invention provides a carbon neutralization path dynamic planning method and system based on carbon asset matching, and the method comprises the following steps: obtaining multi-source carbon asset data in an enterprise, a park or a region, and carrying out the preprocessing of the multi-source carbon asset data; the carbon asset value is dynamically evaluated by constructing the time-varying value evaluation model and comprehensively considering the change of factors such as policies, markets and technologies along with time, and meanwhile, various carbon assets are managed in a classified manner by constructing the four-dimensional asset matrix, so that the carbon asset management efficiency and benefit are remarkably improved; through supply side geographical matching and demand side time sequence matching, carbon asset supply and demand are accurately connected from space and time dimensions, cost and loss are reduced, an improved Bellman equation is applied, decision weight is dynamically adjusted under triple constraint conditions, carbon asset transaction and emission reduction measures are scientifically coordinated, and the utilization efficiency of carbon assets is improved; by constructing a reinforcement learning model, path planning is continuously optimized, and the scheme is ensured to be able to land and adapt to changes.

The invention discloses a shipping industry carbon emission prediction method based on fusion of multi-scale feature extraction and time sequence dependence analysis, and belongs to the field of carbon emission prediction and time sequence analysis. The method comprises the steps that historical shipping carbon emission data are acquired and preprocessed; performing multi-scale decomposition on the preprocessed data by adopting a complete ensemble empirical mode decomposition adaptive noise technology, generating n intrinsic mode functions and a residual sequence, inputting the n intrinsic mode functions and the residual sequence into a Transform model, obtaining data features of the intrinsic mode functions, inputting the data features into an LSTM model, and obtaining predicted n intrinsic mode functions and n residual sequences; and superposing all prediction results, carrying out smoothing processing to obtain a final carbon emission prediction result, and then obtaining a trained Transform model and a trained LSTM model to predict the carbon emission of the shipping industry. The method is suitable for practical application scenes such as shipping carbon emission supervision, carbon emission reduction policy evaluation and carbon neutralization path planning.

The invention relates to the technical field of cloud computing and data center energy efficiency optimization, and discloses a carbon neutralization-oriented cloud data center energy efficiency optimization method, which comprises the following steps of: 1, acquiring server computing load, power consumption, cooling state and carbon emission data of a data center based on a distributed sensor network; step 2, constructing an energy efficiency mathematical model of the data center based on a deep learning model of AI training; 3, training a task scheduling and cooling system optimization strategy based on a reinforcement learning agent; 4, analyzing the real-time carbon emission condition of the data center by using an AI prediction algorithm; 5, based on the carbon emission trend predicted by AI, triggering an intelligent carbon compensation strategy in combination with the real-time energy consumption condition of the data center; and step 6, dynamically adjusting task scheduling, a cooling control strategy and a carbon compensation scheme by adopting an AI adaptive learning method based on data feedback. And dynamic scheduling of calculation tasks of the data center is realized through a reinforcement learning agent trained by AI.

The invention relates to the technical field of carbon neutralization, and provides a carbon emission monitoring method and system based on agricultural carbon neutralization. The carbon emission monitoring method based on agricultural carbon neutralization comprises the following steps: constructing a multi-dimensional database based on carbon emission based on agricultural planting data of a current area, and determining dynamic characteristics of carbon emission; according to the carbon emission dynamic characteristics, constructing a dynamic analysis model, and determining a carbon neutralization efficiency index set; according to the carbon neutralization efficiency index set, a carbon emission thermodynamic diagram of the current area is constructed, the carbon emission thermodynamic diagram generates a key sensitive factor sorting sequence which is transformed in real time based on the carbon neutralization time-space evolution trend, and the color depth of the thermodynamic diagram is adjusted based on the key sensitive factor sorting sequence. According to the application, through multi-dimensional data fusion, dynamic coupling of respiration source analysis and metabolic entropy change, based on sensitive factor sorting and thermodynamic diagram rendering rules, meteorological sudden change response and edge calculation are combined, a monitoring result is displayed in real time through a thermodynamic diagram, and the carbon emission condition is determined.

The invention discloses an LCA-based fabricated building carbon neutralization analysis management system, and particularly relates to the field of analysis management, and the system comprises a data collection module, a life cycle analysis module, a carbon emission calculation module, a carbon neutralization strategy generation module, a visual display module, and a user feedback and optimization module. According to the invention, through integration of an Internet of Things sensor, a BIM model and a block chain technology, full life cycle links are automatically collected; the system quantifies the environmental influence of each stage by using a dynamic LCA model, calculates the carbon emission in real time, and generates a carbon neutralization strategy based on a multi-objective optimization algorithm, including renewable energy application and carbon compensation measures; through a visual tool and dynamic simulation, the system visually displays an analysis result and a strategy effect, and supports user interaction and parameter adjustment; a user feedback mechanism is combined with a reinforcement learning algorithm, system parameters and strategies are dynamically optimized, a'feedback-optimization-re-feedback 'closed loop is formed, and analysis precision and strategy feasibility are improved.

The invention provides an urban carbon neutralization path analysis system and an analysis method thereof. The urban carbon neutralization path analysis system comprises a data acquisition module, a data arrangement module, a region division module, a carbon balance calculation module, a path setting module, a path analysis module and a result output module, according to the invention, through regular rasterization region division, fine modeling of the city space is realized; the carbon sequestration capacity is dynamically estimated by combining multiple types of carbon sources and multiple types of vegetation carbon sequestration factors with an NDVI time sequence index, so that a carbon-oxygen balance calculation result has time sensitivity and spatial resolution; meanwhile, the path analysis module supports a user to set various energy structures, traffic modes and greenbelt lifting parameter combinations to form a multi-path parallel simulation matrix, the selection space of path decision is effectively expanded, the system can realize comparable carbon neutralization evolution analysis according to regions and time periods, and the effects of improving the analysis precision and enhancing the path deduction capability are achieved.

The invention relates to the technical field of carbon neutralization, and discloses a full-life-cycle carbon neutralization system and method for an intelligent networked electric vehicle. The system comprises a full-life-cycle carbon emission system which is used for calculating carbon emission of a vehicle in five stages of material supply, part and whole vehicle manufacturing, charging use, scrap recovery and intelligent network connection cloud service full-life cycle; the ecological system engineering BECNU negative carbon emission system is used for providing globally acknowledged carbon removal certification carbon sink credit (CRCF); the intelligent network connection system is used for deducting and neutralizing carbon emission in the boundary of the system; and the vehicle-mounted carbon neutralization intelligent instrument is used for carrying out digital intelligent network connection recording, metering accounting, authentication and carbon label neutralization identification on carbon footprint emission and removal information.

The invention discloses a building material mine carbon emission metering traceability method, which realizes full-chain accurate metering and credible traceability of carbon emission through multi-process division, multi-source sensing data acquisition, dynamic model correction and block chain traceability technologies. The method comprises the following steps: refining a building material mine production process into five main procedures of mining, raw material processing, calcining / sintering, finished product preparation and transportation, and deploying a multi-source sensor group to collect raw material quality, particle size distribution, energy consumption and waste gas emission data in real time; constructing a multi-layer carbon emission calculation model, and dynamically correcting emission factors in combination with a material balance method, life cycle evaluation (LCA) and a machine learning algorithm; determining a carbon emission distribution coefficient based on the product output proportion and the process contribution degree, and generating a block chain carbon footprint label; coupling a mine restoration carbon sink evaluation and deduction mechanism, and outputting a dynamic net carbon accounting report; and an abnormal emission early warning mechanism is integrated. According to the method, the accuracy of carbon emission metering is remarkably improved, and technical support is provided for building material mine carbon neutralization.

The invention relates to the technical field of environment management, in particular to a carbon neutralization management method and system based on digital asset circulation, and the method comprises the following steps: screening associated data of energy consumption and carbon emission based on carbon emission data, energy consumption, a total production value and an industrial production value, and eliminating abnormal values and redundant information. According to the invention, through combination of trend weight and time sequence fitting, the influence range of trend change is determined, the prediction capability of dynamic association of energy consumption and carbon emission is effectively enhanced, and through analysis of quota distribution records and time span parameters, quota adjustment in a transaction path is optimized, the quota distribution efficiency and flexibility are improved, and the prediction efficiency of the dynamic association of energy consumption and carbon emission is improved. Supply and demand fluctuation analysis is combined with quota price and distribution adjustment, a supply and demand matching mechanism is dynamically optimized, distribution accuracy and response efficiency are improved, fluctuation intervals and risk association weights are dynamically calculated, real-time assessment and regulation of risk changes are realized, and adverse effects of risk accumulation on carbon transaction management are reduced.

The invention discloses an urban carbon emission peak prediction method, and particularly relates to the technical field of carbon emission prediction. A carbon emission data set with high time resolution is constructed, and first K influence factors with the highest contribution degree to a carbon emission peak value are screened based on an adaptive weight attribution mechanism, including extraction of heating system response time and energy scheduling hysteresis characteristics, construction of a carbon emission peak value prediction model, and when a prediction value exceeds a set threshold value, calculation of the carbon emission peak value prediction model is carried out. The method comprises the following steps: automatically adjusting the influence weight of a key factor, calculating a peak confidence interval on a test set, evaluating and optimizing the model performance, finally deploying an optimized model to an urban carbon emission monitoring system, and dynamically updating in combination with a real-time data stream to ensure the accuracy and stability of prediction; according to the method, the accuracy of urban carbon emission peak prediction is remarkably improved, the capability of responding to sudden energy demand increase in extreme weather is enhanced, and scientific support is provided for carbon neutralization policies, energy regulation and control and environment management.

The invention discloses a kiln temperature monitoring method based on coupling simulation and Kalman filtering, which belongs to the technical field of kiln temperature monitoring, and comprises the following steps of: simulating temperature field distribution in a kiln through simulation software, and fusing a simulation result and actual measurement data by using a Kalman filtering technology to obtain a simulation result; therefore, a more accurate temperature monitoring result is obtained. The method can effectively improve the accuracy and real-time performance of monitoring, optimize the heat energy utilization efficiency of the kiln, reduce energy consumption and carbon emission, and provide technical support for achieving the carbon neutralization target in industrial production.

The invention belongs to the field of carbon sequestration, and particularly relates to a carbon sequestration dynamic estimation method for summarizing multi-village carbon emission data, which comprises the following steps: step 1, collecting multi-village carbon emission source data and carbon confluence data with annual time as a period, and numbering the carbon emission source data and the carbon confluence data after the accounting range and boundary are determined according to village levels; the method comprises the following steps: counting carbon emission and carbon sink data of multiple villages in a historical period, acquiring a carbon balance correlation coefficient related to the carbon emission and carbon sink data by virtue of a carbon emission estimation model and a carbon sink dynamic estimation model, and confirming a carbon sink dynamic variable by virtue of the carbon balance correlation coefficient when carbon emission is increased in rural construction. According to the method, the area and space related to carbon sequestration are dynamically adjusted in the country, positive correlation of a carbon sequestration dynamic variable and a carbon emission dynamic variable is ensured, and a corresponding strategy and scheme are proposed based on the carbon sequestration dynamic variable, so that the requirements of carbon peak reaching and carbon neutralization are met when the country is constructed.

The invention relates to the technical field of carbon emission calculation, in particular to an enterprise carbon emission calculation evaluation method and system and a storage medium. The method comprises the following steps: collecting boundary material inflow information and material outflow information of an enterprise production system to obtain material flow data; establishing a material balance equation based on the material flow data, and tracking a flow path of carbon elements through the material balance equation to obtain a carbon element balance table; and according to preset standard state thermodynamic parameters and chemical reaction equations, performing combustion condition and stoichiometric unit fuel combustion on the carbon element balance table to generate carbon emission, and obtaining direct carbon emission data. According to the method, direct and indirect carbon emission and carbon sink contribution are integrated, the total carbon emission of the enterprise is dynamically summarized and counteracted, net carbon emission data are generated, and a quantitative basis is provided for a carbon neutralization target of the enterprise.

According to the low-concentration flue gas CO2 absorbent screening method, system, equipment and medium disclosed by the embodiment of the invention, the RF for feature screening and the XGBoost for performance prediction are combined to construct a high-precision physical property prediction model, so that the dependence on experimental data is reduced; by introducing an NSGA-II algorithm of an adaptive constraint processing mechanism, weights of key features are dynamically adjusted, a global optimal solution is ensured, the accuracy of the model is effectively improved, and industrial requirements are met. Finally, the low-concentration flue gas CO2 absorbent formula which is excellent in performance and economical and feasible is screened out, an efficient absorbent design scheme is provided for industrial application, the efficiency and economical efficiency of the CO2 capturing process are improved, the industrialization process of the CO2 capturing technology is promoted, and powerful technical support is provided for achieving the purposes of carbon emission reduction and carbon neutralization.

The invention relates to the technical field of carbon neutralization of networked tramcars, and discloses an intelligent instrument system for carbon neutralization of networked tramcars based on a BECNU international negative carbon emission neutralization standard, and the system comprises a hardware terminal module which comprises three forms of integrated intelligent terminals, namely a handheld intelligent instrument terminal, a vehicle-mounted intelligent instrument terminal and a station pile intelligent instrument terminal; the intelligent control module comprises a special operating system and an intelligent chip; the software system module comprises the following seven subsystems: an intelligent instrument cloud service subsystem; an intelligent driving management subsystem; a smart energy management subsystem; a carbon cycle management subsystem; an ecological value management subsystem; a road intelligent traffic subsystem; according to the system, the carbon footprint full-life-cycle management of the networked electric vehicle based on the BECNU international negative carbon emission neutralization standard is realized.

The invention discloses a carbon neutralization target setting and tracking system based on big data and an artificial intelligence technology, and relates to the technical field of carbon neutralization. The system comprises a plurality of key modules, a data acquisition module widely collects multi-source data of energy, industry, traffic, building, weather and the like, a satellite remote sensing data acquisition technology is introduced, and the carbon emission condition is comprehensively reflected; the data preprocessing module adopts a transfer learning technology to improve the processing efficiency; the big data storage module is combined with a block chain technology to guarantee data credibility; a reinforcement learning mechanism is integrated into a target setting sub-module of the artificial intelligence analysis module, a knowledge graph technology is introduced into a tracking analysis sub-module, and a carbon neutralization target is accurately set and tracked; the visual display module provides immersive experience by applying VR and A technologies; and the decision support module gives comprehensive decision suggestions in combination with a simulated annealing algorithm and a multi-objective decision theory. The system can scientifically set targets, accurately track the progress and intelligently assist in decision making, and provides powerful technical support for carbon neutralization.

The invention provides a college campus planning and design multi-objective optimization method based on cGAN and NSGA-II, and the method specifically comprises the steps: obtaining a large number of existing different campus planning and design related data, and carrying out the correlation of the data with corresponding carbon emission and incremental cost data, and forming a model data set; inputting the model data set into a pre-constructed cGAN model for training, and optimizing an initial campus planning and design scheme output by the cGAN model through an NSGA-II algorithm; and performing optimization adjustment and scheme visual display on the cGAN model based on the target campus planning design. The college campus carbon emission level and incremental cost collaborative optimization model constructed by the invention provides scientific decision support for an architect to fully consider the balance between the carbon emission reduction performance and the economic benefit in a scheme stage, and is helpful to further realize a campus carbon neutralization construction plan.

The invention relates to the technical field of carbon resource management, in particular to a carbon emission management system for a building energy carbon supervision platform, which comprises a carbon emission statistics module, a carbon emission calculation and evaluation module and a carbon planning module, the carbon emission statistics module comprises a carbon emission factor management sub-module, a real-time data sub-module, a historical data sub-module and a system data sub-module, the carbon emission calculation and evaluation module comprises a carbon emission calculation sub-module and a carbon emission reduction benefit analysis sub-module, and the carbon planning module comprises a carbon neutralization calculation sub-module and a dual-carbon process analysis sub-module. The invention provides a carbon emission management system suitable for a building energy and carbon supervision platform, which can connect the computational statistics, analysis and evaluation and planning and expectation processes of building carbon emission to form a complete building carbon emission management system, and on the basis of the basic data and functions of the energy and carbon supervision platform, according to the actual project requirements, the energy and carbon supervision platform can be used for energy and carbon supervision. And a comprehensive and clear carbon emission management service is provided for the user.

The invention belongs to the technical field of carbon neutralization, and discloses an organic solid waste pyrolysis gasification tar hydrocarbon co-production quality-divided utilization method, which comprises the following steps of: firstly, dividing tar generated in an organic solid waste pyrolysis gasification process into light tar, medium tar and heavy tar according to boiling range difference through in-situ thermal-state quality division; the light tar is subjected to catalytic steam reforming to obtain hydrogen-rich synthesis gas, the medium tar is subjected to steam reforming to obtain synthesis gas and semicoke generated by condensation polymerization, and the semicoke and the heavy tar are subjected to steam activation to obtain synthesis gas and porous carbon; and carrying out water-gas shift, CO2 capture and pressure swing adsorption purification treatment on the obtained synthesis gas to obtain battery-grade hydrogen. According to the method, the tar is converted into high-value porous carbon and high-purity hydrogen step by step through stage treatment and quality-divided utilization of the tar, so that the problems of rapid deactivation of a catalyst, waste of high-temperature energy and the like in the tar treatment process are effectively solved, and resource utilization of the tar is realized.

The invention relates to the technical field of building energy consumption analysis, and discloses a building energy consumption and carbon neutralization analysis system based on big data analysis, which comprises an acquisition unit, an analysis unit, a calculation unit, a deficit unit, a judgment unit and a carbon neutralization management unit, and is used for generating a carbon neutralization management instruction of a target object according to a carbon neutralization urgency index, performance degradation of a target object along with increase of service life is captured, an analysis unit combines real-time carbon emission data of a power grid, generates a dynamic carbon track slope and reflects a carbon emission change trend in real time, a calculation unit performs segment processing on operation duration based on big data, and a complete-cycle carbon track vector is constructed. A healthy deficit degree and a stepped urgency index are generated through big data analysis of the deficit unit and the judgment unit, and finally a management instruction is output by the management unit, so that the problem of insufficient tracking of full-life-cycle energy consumption attenuation and carbon emission increment of a target object by traditional analysis is effectively solved, and the accuracy of long-term carbon neutralization planning is greatly improved.

The invention discloses a device and a method for in-situ determination and reduction of greenhouse gas emission in a nitrogen and phosphorus removal process of an AOA process, and belongs to the field of sewage treatment and carbon neutralization. The device comprises a gas collection type continuous flow AOA reactor, an accurate aeration system, a gas collection system, a microelectrode system and the like. According to the device, a greenhouse gas in-situ monitoring system and a regulation and control system are integrated, the emission condition of greenhouse gases (CO2, CH4 and N2O) in the operation process of the AOA technology can be monitored in real time, then parameters such as dissolved oxygen and the sludge reflux ratio are automatically adjusted, the operation conditions are optimized, and emission of the greenhouse gases is effectively reduced. The method is also combined with a biological enhancement technology, and the ecological niche of the microbial community is adjusted by adding anaerobic ammonia oxidation filler, so that the nitrogen and phosphorus removal efficiency of the AOA process is further improved, and meanwhile, the generation of greenhouse gases is reduced. The device can comprehensively monitor the greenhouse gas in the AOA process, and provides technical support for greenhouse gas research in the biological sewage treatment process.

Disclosed herein are systems and embodiments for improving energy efficiency of a chemical separations plant through heat integration. Heat integration may provide heating loops between distillation columns and / or integrated electric heating components configured to supply heat to reboilers in the chemical separations plant. Heat integration may use heat from an associated chemical synthesis plant configured to carry out an exothermic reaction (e.g., production of methanol from CO2 and H2). Such integrated process designs allow for the use of “low-grade” heat, thereby improving energy efficiency. Furthermore, such integrated process designs allow for electrification of exemplary chemical separations plants, replacing the use of steam as a heating medium with more energy efficient and carbon-emission neutral, electrical methods.

The invention discloses a system and a method for supercritical CO2 in-situ pyrolysis of wide-depth-range oil-rich coal, an injection well, a first horizontal well, a second horizontal well and a production well are respectively arranged in shallow-layer oil-rich coal and deep-layer oil-rich coal, a temperature monitor is supplemented, supercritical CO2 is injected to realize in-situ pyrolysis of the oil-rich coal, and the in-situ pyrolysis of the oil-rich coal is realized. The pyrolysis products are subjected to grading treatment, meanwhile, different land parcels are operated in a combined mode, waste heat of the previous land parcel is used for the pyrolysis reaction of the next land parcel, CO2 is a heat carrying medium, and then part of CO2 is sealed in the previous land parcel. In the whole process, in-situ pyrolysis of the oil-rich coal seam in different burial depths and thickness ranges is achieved, heat in the pyrolysis process is fully utilized, heat waste is avoided, and the mining utilization rate of the oil-rich coal is increased through the promoting effect of supercritical CO2 on heat and mass transfer; and meanwhile, the strategic goals of CO2 emission reduction and carbon neutralization promotion are achieved.