Carbon emission monitoring and management system and method

Abstract

The invention discloses a carbon emission monitoring and management system and method. The system comprises a carbon emission monitoring basic database construction module and a carbon emission monitoring and management platform. The carbon emission monitoring basic database construction module is used for integrating the carbon emission data of a plurality of data sources and constructing a carbon emission monitoring basic database at the levels of regions, enterprises and industries; the carbon emission monitoring and management platform is used for analyzing the carbon emission trend from the angles of an industrial chain, spatial evolution and time evolution according to the carbon emission data in the carbon emission monitoring basic database, drawing a carbon emission data evolution analysis map based on the industrial chain, and analyzing the carbon emission data evolution analysis map based on the industrial chain. And providing carbon emission data query, carbon emission data visualization and data editing services. According to the scheme, the problem that carbon emission data are scattered and fragmented is solved, a large amount of carbon emission data are integrated and analyzed, and an efficient informatization analysis means is provided for strategy formulation and optimization.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a carbon emission monitoring and management system and method. Background Art

[0002] my country has adopted a series of measures, such as fixed on-grid electricity prices, renewable energy quotas and carbon emission trading mechanisms, to promote low-carbon transformation. Other key industries such as electricity, petrochemicals and steel account for more than 90% of my country's carbon emissions, among which the power industry is the largest carbon emission industry. In the process of promoting low-carbon transformation of key industries, carbon emission monitoring is an important means, which will enable researchers to better understand how factors such as policy implementation, economic changes, energy prices, holidays and weather affect carbon dioxide emissions. However, there is currently no regional / industry quasi-real-time carbon emission database for my country and a carbon emission monitoring and management system based on it.

[0003] Faced with the current problem of scattered and fragmented carbon emission data in my country, how to integrate and analyze large amounts of carbon emission data is a technical problem that needs to be solved urgently. Summary of the invention

[0004] Based on the above problems, the present application provides a carbon emission monitoring and management system and method, which aims to solve the problem of scattered and fragmented carbon emission data, integrate and analyze a large amount of carbon emission data, and provide efficient information analysis means for strategy formulation and optimization.

[0005] The embodiments of the present application disclose the following technical solutions:

[0006] In a first aspect, the present application provides a carbon emission monitoring and management system, the system comprising: a carbon emission monitoring basic database construction module and a carbon emission monitoring and management platform;

[0007] The carbon emission monitoring basic database construction module is used to integrate carbon emission data from multiple data sources to build a carbon emission monitoring basic database at the regional, enterprise and industry levels; the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution database and the power plant database;

[0008] The carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw a carbon emission data evolution analysis map based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services.

[0009] In an optional implementation, the carbon emission monitoring and management platform is specifically used to:

[0010] The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

[0011] In an optional implementation, the system further includes: an upload module;

[0012] The upload module is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and record the operations on the data table in the system in the form of logs on the blockchain.

[0013] In an optional implementation, the carbon emission monitoring and management platform includes: a data query module, a data visualization module and a data editing module;

[0014] The data query module is used to retrieve carbon emission data according to region, industry or time conditions;

[0015] The data visualization module is used to intuitively display carbon emission data in various forms; the various forms include charts and maps;

[0016] The data editing module is used to edit and proofread the carbon emission data of the carbon emission monitoring and management platform.

[0017] In an optional implementation, the system further includes: a carbon emission data preprocessing module;

[0018] The carbon emission data preprocessing module is used to clean, organize and calculate the carbon emission data from multiple data sources before integrating the carbon emission data from multiple data sources according to regions, enterprises and industries.

[0019] In an optional implementation, the system is applied to national carbon market scenario analysis and simulation, renewable energy green certificate trading simulation, or text analysis of climate change awareness.

[0020] The second aspect of the present application provides a carbon emission monitoring and management method, which is applied to the carbon emission monitoring and management system provided in the first aspect. The method comprises:

[0021] Through the carbon emission monitoring basic database construction module, the carbon emission data from multiple data sources are integrated to build a carbon emission monitoring basic database at the regional, enterprise and industry levels; the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution database and the power plant database;

[0022] Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, a carbon emission data evolution analysis map based on the industrial chain is drawn, and carbon emission data query, carbon emission data visualization and data editing services are provided.

[0023] In an optional implementation, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn, including:

[0024] The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

[0025] In an optional implementation, the method further includes:

[0026] The blockchain technology is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and the operations on the data tables in the system are recorded in the form of logs on the blockchain.

[0027] In an optional implementation, the carbon emission monitoring and management platform analyzes the carbon emission trend from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draws an evolution analysis map of carbon emission data based on the industrial chain, and provides carbon emission data query, carbon emission data visualization and data editing services, including:

[0028] The carbon emission data query retrieves carbon emission data according to region, industry or time conditions;

[0029] The carbon emission data visualization intuitively displays the carbon emission data in various forms; the various forms include charts and maps;

[0030] The data editing service edits and proofreads the carbon emission data of the carbon emission monitoring and management platform.

[0031] Compared with the prior art, this application has the following beneficial effects:

[0032] The carbon emission monitoring and management system proposed in this application includes: a carbon emission monitoring basic database and a carbon emission monitoring and management platform. The carbon emission monitoring basic database integrates carbon emission data from multiple data sources according to regions, enterprises and industries. The carbon emission monitoring and management platform analyzes carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draws an evolution analysis map of carbon emission data based on the industrial chain, and provides carbon emission data query, carbon emission data visualization and data management services. The carbon emission monitoring and management system and method proposed in this application solves the current problem of scattered and fragmented carbon emission data, and provides efficient information analysis means for formulating specific emission reduction paths and strategies, flexibly using market regulation mechanisms, breaking energy and environmental constraints, and achieving a win-win situation of improving economic quality and efficiency and green and low-carbon development. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 A structural diagram of a carbon emission monitoring and management system provided in an embodiment of the present application;

[0035] Figure 2 A data query interface diagram of an energy balance sheet provided in an embodiment of the present application;

[0036] Figure 3 An interface diagram for editing power plant information provided in an embodiment of the present application;

[0037] Figure 4 A structural diagram of another carbon emission monitoring and management system provided in an embodiment of the present application;

[0038] Figure 5 A flowchart of a carbon emission monitoring and management method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] As described above, there is currently no quasi-real-time carbon emission database for my country's regions / industries, nor a carbon emission monitoring and management system based on it. Faced with the problem of scattered and fragmented carbon emission data in my country, how to integrate and analyze a large amount of carbon emission data is a technical problem that needs to be solved urgently.

[0040] In view of the above problems, the inventors have proposed a carbon emission monitoring and management system and method after research, the system comprising: a carbon emission monitoring basic database construction module and a carbon emission monitoring and management platform; the carbon emission monitoring basic database construction module is used to integrate carbon emission data from multiple data sources to construct carbon emission monitoring basic databases at the regional, enterprise and industry levels; the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution discharge database and the power plant database; the carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw a carbon emission data evolution analysis map based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services.

[0041] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] See also Figure 1 , which is a structural schematic diagram of a carbon emission monitoring and management system provided by an embodiment of the present application. Figure 1 As shown, the system includes: a carbon emission monitoring basic database construction module and a carbon emission monitoring and management platform.

[0043] The carbon emission monitoring basic database construction module is used to integrate carbon emission data from multiple data sources to construct a carbon emission monitoring basic database at the regional, enterprise and industry levels.

[0044] Among them, the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution discharge database and the power plant database.

[0045] The national prefecture-level city statistical yearbooks for the past 20 years have calculated the carbon emission levels at the prefecture-level city level, which serves as a data source for regional carbon emissions. At the same time, the carbon emission levels at the enterprise and industry levels are calculated using the China Enterprise Pollution Database and the Power Plant Database, which serve as data sources at the enterprise and industry levels. A China thermal power generation carbon emission database has been constructed, covering information such as the total number of power plants, installed capacity, power generation, and carbon dioxide emissions. In addition, it also includes a carbon emission estimation database for other key industries (steel, papermaking, and non-metals), and an estimation of carbon emission data based on AIS shipping.

[0046] The carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw a carbon emission data evolution analysis map based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services.

[0047] The carbon emission monitoring and management platform is specifically used for:

[0048] The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

[0049] Based on the internationally accepted energy emission factor data, the carbon dioxide emission levels of each province in China in each year were calculated by using the Chinese Provincial Statistical Yearbook, Energy Statistical Yearbook, energy balance sheet, and the National Greenhouse Gas Inventory Guidelines issued by the IPCC.

[0050] On this basis, we can analyze the emission level per unit GDP and per capita emission level of each province, so as to compare the differences in emission levels in different regions from both the production and consumption sides, and further analyze the factors affecting the emission level and conduct structural decomposition, so as to explore the driving factors of the rapid increase in carbon emissions on China's production and consumption sides, such as economic scale, industrial structure, etc.

[0051] 85% of China's carbon dioxide emissions come from cities, so cities are considered key areas for implementing strategies to adapt to climate change and reduce carbon dioxide emissions. At the urban emission level, the carbon emission monitoring and management system provided in this embodiment provides city-level carbon dioxide emission level estimates for 182 Chinese cities, broken down into 17 different fossil fuels, 46 socio-economic sectors, and 7 industrial sectors.

[0052] From the perspective of final use, urban emissions are decomposed into production, consumption, capital formation and other aspects. Different cities have different dominant aspects. Through further research on the driving factors of urban carbon emissions, especially how the economic scale, per capita disposable income of urban residents, the proportion of secondary industry and the increase in urbanization rate drive the growth of urban carbon emissions, and the impact of urban carbon emissions in adjacent areas on urban carbon emissions in the local area.

[0053] In addition, this embodiment collects and organizes data from multiple different sources such as the compilation of power industry statistics, the national generator manual, the China Electricity Council thermal power unit energy efficiency level benchmarking competition, the Huaneng / Huadian statistics compilation, and the national pollution permit management information platform to form a China thermal power plant carbon emissions database, with a time span of 1989-2018. Specific data items include:

[0054] 1) The total number of thermal power plants in China, their total power generation, and their total carbon dioxide emissions;

[0055] 2) The geographical distribution of China's thermal power plants;

[0056] 3) Total installed capacity of thermal power, coal-fired power and gas-fired power;

[0057] 4) Carbon dioxide emissions from coal-fired and gas-fired power generation by province;

[0058] 5) Information related to the emission enterprise.

[0059] Integrating carbon emission data from multiple data sources according to regions, enterprises and industries solves the current problem of scattered and fragmented carbon emission data, and provides relevant support for carbon emission information disclosure and the design of carbon emission optimization and control strategies.

[0060] The carbon emission monitoring and management platform includes: a data query module, a data visualization module and a data editing module;

[0061] The data query module is used to retrieve carbon emission data according to region, industry or time conditions;

[0062] The data visualization module is used to intuitively display carbon emission data in various forms; the various forms include charts and maps;

[0063] The data editing module is used to edit and proofread the carbon emission data of the carbon emission monitoring and management platform.

[0064] Figure 2 The data query module of this embodiment is demonstrated by data query of the energy balance sheet. The energy balance sheet is selected through the data query in the left menu, and the filtering conditions such as year are filled in, for example, 2017, to obtain the carbon emission data in the table. The row headings in the table include the amount of energy available for consumption in the region, primary energy production, hydropower, nuclear power, wind power, amount transferred in from other provinces (cities), import amount, amount transferred out from the province (region, city), export amount, inventory increase and decrease, processing and conversion input-output amount, thermal power generation, heating, coal washing and coking. The column headings include total coal, raw coal, washed coal, other washed coal, shaped coal, coal gangue, coke oven gas, blast furnace gas and converter gas, etc. The data units of each column include tons (tonne) and cubic meters (cubic metre).

[0065] The visualization module in this embodiment visualizes the carbon emission data of regions and industries, and can quickly find the carbon emission data of different cities by filtering years such as 2005 and 2012. It can also reflect the carbon emissions of different sectors such as agriculture, services, industrial energy, industrial processes, urban life and rural life, and summarize the carbon emissions of transportation, energy and industry, and calculate the carbon dioxide emissions per unit of gross domestic product (GDP).

[0066] Figure 3 The data editing module function of this embodiment is demonstrated with the enterprise information editing interface, which includes multiple parts such as condition screening, power plant query results, similar power plant results, corresponding power plant data and enterprise organization code entry. In the condition screening part, you can select the province, enter the power plant keywords to query similar power plants, and you can also enter the ID of the specified power plant to load the corresponding power plant and load the power plant information. The power plant query result part can display the ID of the superior power plant and the ID of the subordinate power plant to update the power plant hierarchy. In the enterprise organization code entry part, the detailed information of the enterprise is entered through the input box. The organization code and database ID are entered for loading in the data merger. It also includes the unified social credit code, enterprise name, legal representative, enterprise address, registered capital, establishment date, enterprise website and enterprise business status.

[0067] The system is applied to national carbon market scenario analysis and simulation, renewable energy green certificate trading simulation or text analysis of climate change cognition.

[0068] The national carbon market scenario analysis and simulation evaluates the impact of China's national carbon emissions trading system at the factory level and assesses the potential market size and emission reduction effects of the carbon market under different permit allocation scenarios, which not only helps in strategy formulation but also provides useful evidence for those important market participants.

[0069] The simulation of renewable energy green certificate trading uses micro data for ex ante strategy evaluation and analyzes the strategic interaction between the carbon market and the renewable energy quota market, as well as the capital reallocation effect. This helps to clarify the laws of capital reallocation effects between enterprises and provincial administrative regions participating in the carbon emission trading system and the impact of strategic interactions, thereby providing support for strategy optimization design.

[0070] The text analysis of climate change cognition uses the references in the annual reports of the Intergovernmental Panel on Climate Change (IPCC) as the seed document library, and captures the cited articles of the seed documents from the WOS (Web of Science) database as well as the documents retrieved by WOS using the keyword "climate change" as the document database. After word segmentation and cleaning of the text, the latent Dirichlet allocation (LDA) model is used to determine the topic tags of the article, and the argument structure of the article is judged through supervised opinion recognition and unsupervised opinion extraction.

[0071] The carbon emission monitoring and management system proposed in this embodiment constructs a carbon emission monitoring basic database for integrating carbon emission data from multiple data sources according to regions, enterprises and industries, thereby solving the current problem of scattered and fragmented carbon emission data. The carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw an evolution analysis map of carbon emission data based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services, thereby providing efficient information analysis means for formulating specific emission reduction paths and strategies, flexibly using market regulation mechanisms, breaking through energy and environmental constraints, and achieving a win-win situation of improving economic quality and efficiency and green and low-carbon development.

[0072] See also Figure 4 , which is a structural diagram of another carbon emission monitoring and management system provided by the embodiment of the present application. In order to further improve the carbon emission monitoring and management system, a carbon emission data preprocessing module and an upload module are added. Figure 4 As shown, the system includes: a carbon emission monitoring basic database construction module, a carbon emission monitoring and management platform, a carbon emission data preprocessing module and an upload module.

[0073] The carbon emission monitoring basic database construction module is used to integrate carbon emission data from multiple data sources to construct a carbon emission monitoring basic database at the regional, enterprise and industry levels.

[0074] Among them, the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution discharge database and the power plant database.

[0075] The carbon emission levels at the prefecture-level city level were calculated using the national prefecture-level city statistical yearbooks for the past 20 years as the data source for regional carbon emissions. At the same time, the carbon emission levels at the enterprise and industry levels were calculated using the China Enterprise Pollution Emission Database and the Power Plant Database as the data source for the enterprise and industry levels.

[0076] The carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw a carbon emission data evolution analysis map based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services.

[0077] The carbon emission monitoring and management platform is specifically used for:

[0078] The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

[0079] From the perspective of time evolution, time series forecasting models such as ARIMA, SARIMA or Prophet can be used to analyze the changing trend of carbon emissions over time and predict future emissions.

[0080] From the perspective of driving factors, through input-output analysis (IOA), an input-output table containing carbon emission information is constructed to track the carbon flow from production to consumption and determine which industries or sectors are the main sources of emissions. The logarithmic mean Dirichlet index method is used to decompose the change in total emissions into multiple contributing factors, such as population growth, economic development, industrial structure adjustment and technological progress, and quantify the specific impact of each factor on the overall change.

[0081] Combined with machine learning, feature selection, predictive modeling, and anomaly detection are performed. Feature selection uses feature selection algorithms in machine learning (such as recursive feature elimination (RFE) and random forest importance scoring) to automatically identify the most important variables or features. Predictive modeling predicts future emission trends based on historical data by training supervised learning models (such as decision trees, random forests, and XGBoost). Anomaly detection can identify possible data errors or emission anomalies caused by special events, helping to discover and solve problems in a timely manner.

[0082] By using visualization tools such as Matplotlib and Seaborn in Python, or ggplot2 in R, we can create intuitive charts and maps. Integrate all the above analysis results to build a multi-dimensional carbon emission evolution analysis map, which should be able to simultaneously display the carbon emission flow in the industrial chain, the spatial distribution of various regions, and the changing trend over time. This comprehensive analysis can not only reveal the temporal and spatial evolution of carbon emissions, but also provide a scientific basis for formulating more accurate and effective emission reduction strategies.

[0083] The upload module is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and record the operations on the data table in the system in the form of logs on the blockchain.

[0084] Exemplarily, the platform application design configuration based on the alliance chain ChainSQL provided in this embodiment is as follows:

[0085] Database layer: MySQL5.5 (user transaction table, data query table, data table).

[0086] Consensus node layer: Alibaba Cloud server (CentOS7 operating system)*4.

[0087] Interface layer: Nodejs interface.

[0088] Application layer: B / S architecture, server: Nodejs / express framework.

[0089] Blockchain technology (such as ChainSQL) is used to achieve distributed storage and sharing of data. It combines the characteristics of blockchain technology and traditional distributed databases. All operations on data tables are recorded in the form of logs on the blockchain, providing database services that cannot be tampered with and can be restored at any time, ensuring the security and non-tamperability of data during transmission and storage.

[0090] Every data operation on the blockchain is recorded as a transaction and is timestamped, making the data fully traceable.

[0091] The blockchain data sharing platform connects data producers and consumers and provides a pricing and licensing framework to promote development; any data uploaded to the chain must pass the data contract formulated by the alliance to ensure data security and compliance, which helps to break down data silos and balance the data of all participants.

[0092] The carbon emission data preprocessing module is used to clean, organize and calculate the carbon emission data from multiple data sources before integrating the carbon emission data from multiple data sources according to regions, enterprises and industries.

[0093] The carbon emission data preprocessing module is used to clean, organize and calculate carbon emission data to ensure the quality and consistency of carbon emission data and handle problems such as missing values ​​and outliers.

[0094] This embodiment provides another carbon emission monitoring and management system, which adds a carbon emission data preprocessing module to ensure the quality and consistency of carbon emission data. On this basis, the carbon emission monitoring basic database construction module integrates carbon emission data from multiple data sources according to regions, enterprises and industries, solving the current problem of scattered and fragmented carbon emission data.

[0095] The carbon emission monitoring and management platform analyzes carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draws a carbon emission data evolution analysis map based on the industrial chain, and provides carbon emission data query, carbon emission data visualization and data editing services. It provides efficient information analysis means for formulating specific emission reduction paths and strategies, flexibly using market regulation mechanisms, breaking through energy and environmental constraints, and achieving a win-win situation of improving economic quality and efficiency and green and low-carbon development.

[0096] Moreover, the carbon emission monitoring and management system provided in this embodiment also adopts blockchain technology to enhance the quality and reliability of carbon emission data and promote the development of a more open and transparent carbon emission management system.

[0097] Based on the carbon emission monitoring and management system in the above-mentioned embodiment, the present application also provides a carbon emission monitoring and management method embodiment, and the carbon emission monitoring and management method embodiment is introduced in detail below.

[0098] See also Figure 5 , which is a flow chart of a carbon emission monitoring and management method provided in an embodiment of the present application. The method is applied to the carbon emission monitoring and management system of the above embodiment. Figure 5 As shown, the method comprises the following steps:

[0099] S501. Integrate the carbon emission data from multiple data sources through the carbon emission monitoring basic database construction module to construct a carbon emission monitoring basic database at the regional, enterprise and industry levels.

[0100] Among them, the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution discharge database and the power plant database.

[0101] In this embodiment, the carbon emission level at the prefecture-level city level in the prefecture-level city statistical yearbooks in China over the past 20 years is calculated as the data source for regional carbon emissions. At the same time, the carbon emission level at the enterprise level and industry level is calculated using the Chinese enterprise pollution database and power plant database, which are used as the data source at the enterprise and industry levels. A Chinese thermal power generation carbon emission database is constructed, covering information such as the total number of power plants, installed capacity, power generation, and carbon dioxide emissions. In addition, it also includes a carbon emission estimation database for other key industries (steel, papermaking, and non-metals), and an estimation of carbon emission data based on AIS shipping.

[0102] S502. Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn to provide carbon emission data query, carbon emission data visualization and data editing services.

[0103] Among them, according to the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn, including:

[0104] The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

[0105] Apply statistical econometric models (such as ARIMA and SARIMA) to analyze the changing trends in time and space, construct input-output tables through input-output analysis, track the carbon flow in the upstream and downstream of the industrial chain, use the logarithmic mean Dirichlet index method to decompose the changes in total emissions, quantify the impact of various driving factors, combine machine learning algorithms (such as random forests and XGBoost) for feature selection, find out the key variables that affect carbon emissions, train supervised learning models to predict future carbon emission trends, identify abnormal emission events, and help take timely measures.

[0106] The method further comprises:

[0107] The blockchain technology is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and the operations on the data tables in the system are recorded in the form of logs on the blockchain.

[0108] This example uses ChainSQL technology, which is a hybrid database system proposed by Onchain (now called Ontology) that attempts to combine the immutability and decentralization of blockchain with the efficient query capabilities of traditional relational databases. In this way, ChainSQL can support more complex data operations and analysis tasks, and enjoy a faster and more convenient data management and query experience while maintaining data security and transparency.

[0109] Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn, providing carbon emission data query, carbon emission data visualization and data editing services, including:

[0110] The carbon emission data query retrieves carbon emission data according to region, industry or time conditions;

[0111] The carbon emission data visualization intuitively displays the carbon emission data in various forms; the various forms include charts and maps;

[0112] The data editing service edits and proofreads the carbon emission data of the carbon emission monitoring and management platform.

[0113] In this embodiment, the carbon emission monitoring and management platform provides a convenient data query function, which allows users to quickly retrieve carbon emission data according to conditions such as region, industry, and time. Carbon emission data visualization intuitively displays carbon emission data in the form of charts, maps, etc., and creates interactive dashboards (such as using Plotly Dash, Tableau) so that users can intuitively explore data. To help users better understand the trends and rules behind the data, administrators can edit and proofread the carbon emission data of the carbon emission monitoring and management platform one by one through the data editing service to ensure the accuracy and completeness of the data.

[0114] The carbon emission monitoring and management method provided in this embodiment integrates the carbon emission data from multiple data sources according to regions, enterprises and industries through the carbon emission monitoring basic database construction module, thereby solving the current problem of scattered and fragmented carbon emission data. Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn. Carbon emission data query, carbon emission data visualization and data editing services are provided, thereby providing efficient information analysis means for formulating specific emission reduction paths and strategies, flexibly using market regulation mechanisms, breaking energy and environmental constraints, and achieving a win-win situation of improving economic quality and efficiency and green and low-carbon development.

[0115] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. The system embodiments described above are merely schematic, in which the units described as separate components may or may not be physically separated, and the components indicated as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0116] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A carbon emission monitoring and management system, characterized in that: The system includes: a carbon emission monitoring basic database construction module and a carbon emission monitoring and management platform; The carbon emission monitoring basic database construction module is used to integrate carbon emission data from multiple data sources to build a carbon emission monitoring basic database at the regional, enterprise and industry levels; the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution database and the power plant database; The carbon emission monitoring and management platform is used to analyze carbon emission trends from the perspectives of industrial chain, spatial evolution and temporal evolution based on the carbon emission data in the carbon emission monitoring basic database, draw a carbon emission data evolution analysis map based on the industrial chain, and provide carbon emission data query, carbon emission data visualization and data editing services.

2. The system according to claim 1, characterized in that The carbon emission monitoring and management platform is specifically used for: The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

3. The system according to claim 1, characterized in that The system further comprises: an upload module; The upload module is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and record the operations on the data table in the system in the form of logs on the blockchain.

4. The system according to claim 1, characterized in that The carbon emission monitoring and management platform includes: a data query module, a data visualization module and a data editing module; The data query module is used to retrieve carbon emission data according to region, industry or time conditions; The data visualization module is used to intuitively display carbon emission data in various forms; the various forms include charts and maps; The data editing module is used to edit and proofread the carbon emission data of the carbon emission monitoring and management platform.

5. The system according to claim 1, characterized in that The system also includes: a carbon emission data preprocessing module; The carbon emission data preprocessing module is used to clean, organize and calculate the carbon emission data from multiple data sources before integrating the carbon emission data from multiple data sources according to regions, enterprises and industries.

6. The system according to claim 1, characterized in that The system is applied to national carbon market scenario analysis and simulation, renewable energy green certificate trading simulation or text analysis of climate change cognition.

7. A carbon emission monitoring and management method, characterized in that: The method is applied to the carbon emission monitoring and management system according to claim 1; The method comprises: Through the carbon emission monitoring basic database construction module, the carbon emission data from multiple data sources are integrated to build a carbon emission monitoring basic database at the regional, enterprise and industry levels; the multiple data sources include the national prefecture-level city statistical yearbook database, the national enterprise pollution database and the power plant database; Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, a carbon emission data evolution analysis map based on the industrial chain is drawn, and carbon emission data query, carbon emission data visualization and data editing services are provided.

8. The method according to claim 7, characterized in that Based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn, including: The statistical econometric model of spatiotemporal trend analysis, input-output analysis and logarithmic mean Dirichlet index method are used, and combined with machine learning, the spatiotemporal characteristics, driving factors and emission sources of the carbon emission data in the carbon emission monitoring basic database are deconstructed, and the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and an evolution analysis map of carbon emission data based on the industrial chain is drawn.

9. The method according to claim 7, characterized in that: The method further comprises: The blockchain technology is used to upload the carbon emission data in the carbon emission monitoring basic database to the blockchain, and the operations on the data tables in the system are recorded in the form of logs on the blockchain.

10. The method according to claim 7, characterized in that Through the carbon emission monitoring and management platform, based on the carbon emission data in the carbon emission monitoring basic database, the carbon emission trend is analyzed from the perspectives of industrial chain, spatial evolution and temporal evolution, and a carbon emission data evolution analysis map based on the industrial chain is drawn, providing carbon emission data query, carbon emission data visualization and data editing services, including: The carbon emission data query retrieves carbon emission data according to region, industry or time conditions; The carbon emission data visualization intuitively displays the carbon emission data in various forms; the various forms include charts and maps; The data editing service edits and proofreads the carbon emission data of the carbon emission monitoring and management platform.

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