Constructional engineering carbon emission metering method based on full life cycle

Abstract

The invention discloses a constructional engineering carbon emission metering method based on a full life cycle, and aims to solve the problems of incomplete carbon source coverage, low precision, insufficient efficiency and limited application value in existing metering. According to the core scheme, the method comprises the following steps: S1, instantiating an L0-L3 four-stage carbon source tree, and covering five stages of a full life cycle; s2, realizing multi-source data fusion through BIM automatic extraction, API association with an external database and graphical manual supplementation; s3, matching dynamic factors based on context perception, and hierarchically summarizing emission; and S4, generating a multi-dimensional visual chart and a structured decision report. And a real-time updating module, a data conflict processing module, a carbon emission prediction module, a multi-authority management module, a data tracing module, a reference comparison module, an emission reduction quantitative evaluation module and a multi-standard adaptation module are preferably configured. According to the invention, carbon source full coverage, high data precision and high acquisition efficiency are realized, prospective management and control and multi-scene adaptation are supported, a scientific basis is provided for building low-carbon decision making, and the practicability is high.

Description

Technical Field

[0001] This invention relates to the field of carbon emission treatment technology, and in particular to a method for measuring carbon emissions from building engineering based on the entire life cycle. Background Technology

[0002] Accurately measuring the carbon emissions of a building project throughout its entire life cycle (including building material production, transportation, construction, use, demolition, and waste disposal) is a crucial prerequisite for developing effective emission reduction strategies and promoting the green and low-carbon transformation of the construction industry. Life Cycle Assessment (LCA) is a universal environmental impact assessment framework, but how to apply it accurately and efficiently in building engineering practice still faces challenges.

[0003] Existing methods for measuring carbon emissions from construction projects have the following main drawbacks: The measurement framework is unsystematic and contains omissions: most methods only focus on the energy consumption during the building's operation phase, or calculate the carbon emissions of a few major building materials in a piecemeal manner. There is a lack of a systematic framework to ensure coverage of all aspects (such as building material transportation, construction technology, demolition and recycling, etc.), resulting in one-sided measurement results that cannot support a comprehensive carbon footprint analysis.

[0004] Poor model accuracy and adaptability: Existing econometric models mostly use static, average carbon emission factors, failing to fully consider the dynamic impact of project-specific factors (such as building structure type, construction technology, regional differences, and material transportation distance) on the calculation results. The models lack parameter adjustment capabilities, resulting in insufficient accuracy when applied to different projects.

[0005] The existing methods suffer from poor practicality and low efficiency: they rely heavily on manual data collection and processing from numerous design drawings and bill of quantities reports, a cumbersome and error-prone process that makes rapid comparison and analysis of multiple solutions difficult. Furthermore, the entire methodology lacks deep integration with information technology tools (such as BIM), resulting in low automation and hindering its practical application in engineering decision-making. Summary of the Invention

[0006] The present invention aims to solve at least one of the technical problems existing in the prior art or related art.

[0007] Therefore, the purpose of this invention is to provide a carbon emission measurement method for building engineering based on the whole life cycle. By using a carbon source structure tree model, the complex carbon emission sources are systematized and hierarchized, which fundamentally solves the problems of existing methods relying on experience and being prone to omissions.

[0008] To achieve the above objectives, the present invention provides a method for measuring carbon emissions from building construction projects based on the entire life cycle, comprising the following steps: S1: Project initialization and carbon source tree instantiation. Based on the type of the building project, a pre-set carbon source structure tree template is invoked to generate a hierarchical carbon source tree instance specific to the project. The carbon source structure tree includes, from top to bottom: Root node L0: Carbon emissions from building construction projects; Level 1 Node L1: Five stages of the entire life cycle, namely A1-A3 building material production and transportation stage, A4-A5 construction stage, B1-B7 building operation stage, C1-C4 building demolition stage, and D waste treatment and recycling potential stage; Level 2 (L2): Specific activity categories formed by refining each Level 1 node; Level 3 leaf node L3: corresponds to a specific carbon emission activity or material consumption; each leaf node has predefined standardized data attributes, including activity name, unit of measurement, data collection method and factor code; S2: Multi-source data fusion and intelligent parameter acquisition, which fills the leaf node data of the carbon source tree instance through a multi-path parallel approach, specifically including: S2.1 Automatic extraction of BIM data based on rule engine: Import BIM model in IFC format, use pre-stored mapping rules to identify component types and material properties in BIM model, automatically extract corresponding data and map to the corresponding leaf nodes of carbon source tree; S2.2 External database association based on API interface: Query data such as energy consumption of construction machinery through the API interface of the equipment database, and populate the query results into the corresponding nodes of the carbon source tree; S2.3 Graphical Interactive Interface Manual Supplement: Through a graphical form integrating map services, users are guided to input dynamic parameters, including transportation distance and regional power grid carbon emission factor; S3: Context-aware carbon emission calculation and aggregation: Traverse all leaf nodes of the carbon source tree, match accurate carbon emission factors from the dynamic factor database according to node type and context information, calculate the carbon emission of each leaf node using the formula node carbon emission = activity amount × matched carbon emission factor, and then aggregate to the root node in a bottom-up order to obtain the total carbon emission of the building project throughout its entire life cycle. S4: Multidimensional results visualization and decision support report generation visualization charts, including automatically generated pie charts of carbon emission composition throughout the entire life cycle, bar charts of carbon emission hotspot analysis, and radar charts comparing multiple design schemes. At the same time, a structured decision support report is generated that includes calculation basis, data source, carbon emission details, carbon hotspot analysis, and emission reduction optimization suggestions.

[0009] In the above technical solution, preferably, the dynamic factor database is configured with a real-time update module; the real-time update module automatically synchronizes carbon emission factor data periodically through an authoritative data source, and the synchronization frequency can be configured as weekly, monthly or quarterly according to project needs; the real-time update module is linked with the dynamic factor matching process in step S3 to ensure that the matched carbon emission factors are the latest valid data.

[0010] In any of the above technical solutions, preferably, the rule engine in step S2.1 has a built-in intelligent BIM data conflict processing submodule; when there are numerical differences in the same type of data extracted from multiple IFC files, the intelligent BIM data conflict processing submodule calculates the confidence level based on the data source credibility weight, file version timeliness and data integrity, and automatically selects the data with the highest confidence level to fill the corresponding node of the carbon source tree; if the confidence level difference between different data is lower than a preset threshold, the user is prompted to manually confirm through a graphical interface.

[0011] In any of the above technical solutions, preferably, the D node of the carbon source structure tree is associated with a dynamic calculation sub-model for the efficiency of the dismantling and recycling stage; the dynamic calculation sub-model for the efficiency of the dismantling and recycling stage is set with three dynamic parameter input ports: recycling process type, waste classification qualification rate, and recycled material utilization rate. The carbon emission reduction potential of the recycling stage is calculated by the formula: carbon emission reduction of the recycling stage = total waste × recycled material conversion rate × corresponding material production carbon emission factor × recycling efficiency coefficient. The calculation results are synchronized to the hierarchical summary process in step S3.

[0012] In any of the above technical solutions, preferably, step S3 further includes a machine learning-driven carbon emission prediction sub-step; the carbon emission prediction sub-step trains a gradient boosting model based on the full life cycle carbon emission data of similar historical projects, inputs the carbon emission data of the completed stages of the current project and project characteristic parameters, the project characteristic parameters including building structure type, regional information, and construction technology, and outputs the carbon emission prediction value of the subsequent uncompleted stages; the carbon emission prediction value and the actual calculated value of the corresponding stage are compared and displayed in the visualization chart in step S4.

[0013] In any of the above technical solutions, preferably, a multi-user permission hierarchical management module is also included; the multi-user permission hierarchical management module divides user roles into designers, construction personnel, operation and maintenance personnel, and system administrators; among them, designers only have the right to import BIM data and query carbon emissions of design schemes, construction personnel can supplement dynamic data during the construction phase and view the carbon emission analysis results during the construction phase, operation and maintenance personnel have the right to update energy consumption data during the building operation phase, and system administrators have the right to modify data throughout the entire process, configure permissions, and audit logs; the multi-user permission hierarchical management module forms an access control association with the data acquisition stage in step S2 and the report generation stage in step S4.

[0014] In any of the above technical solutions, preferably, the multi-source data acquisition process in step S2 synchronously constructs a full-process data traceability chain; the data traceability chain records key information for each leaf node's populated data, including the BIM file version number, API interface call address and timestamp, manually entered personnel ID and input time, and data modification log; the relevant data of the data traceability chain can be exported through the report generation module in step S4 as the audit basis for carbon emission measurement results.

[0015] In any of the above technical solutions, preferably, the visualization module in step S4 integrates a cross-project carbon emission benchmark comparison submodule; the cross-project carbon emission benchmark comparison submodule has a built-in industry carbon emission benchmark database of building projects of the same type and scale, calculates the difference between the total carbon emissions of the current project and the carbon emission ratio of each stage and the benchmark value, displays the deviation range through a bar chart, and automatically identifies stages with deviations exceeding ±15% as key emission reduction analysis objects; the industry carbon emission benchmark database supports classification and filtering by region, building use, and construction year.

[0016] In any of the above technical solutions, preferably, the decision support report generation module in step S4 is associated with a quantitative evaluation sub-model for emission reduction measures; the quantitative evaluation sub-model for emission reduction measures has a built-in carbon emission reduction coefficient library for four types of emission reduction measures: low-carbon building material substitution, energy-saving equipment replacement, construction process optimization, and renewable energy utilization; after the user selects the target emission reduction measure, the system automatically calculates the theoretical emission reduction and emission reduction cost-benefit ratio based on the current carbon emission data of the project; the calculation results are included in the structured decision support report in the form of an appendix, and support the comparison of emission reduction effects of multiple emission reduction measure combinations.

[0017] In any of the above technical solutions, preferably, the carbon source tree structure is configured with a multi-standard adaptation and conversion module; the multi-standard adaptation and conversion module supports automatic adaptation to three mainstream carbon emission measurement standards: GB / T51366-2019, EN15978, and ISO21931. By adjusting the division of primary node stages, the definition of leaf node data attributes, and the carbon emission factor matching rules, it can realize the switching of carbon emission measurement under different standards and can simultaneously generate independent structured decision support reports for the corresponding standards; the multi-standard adaptation and conversion module is linked with the carbon source tree instantiation process in step S1, the factor matching process in step S3, and the report generation process in step S4.

[0018] Compared with existing technologies, the advantages of the carbon emission measurement method for building engineering based on the entire life cycle provided by this invention are as follows: 1. Structured Model, Eliminating Omissions: The "Carbon Source Structure Tree" model systematizes and hierarchizes complex carbon emission sources, fundamentally solving the problems of existing methods relying on experience and being prone to omissions.

[0019] Automated data collection, significantly increased efficiency: Through multi-source data fusion technology combining "BIM rule engine + API interface + graphical interface", a leap from tedious manual quantity calculation to intelligent automatic filling has been achieved, greatly improving the efficiency and accuracy of data collection.

[0020] Accurate calculations and reliable results: The context-aware dynamic factor matching mechanism enables carbon emission calculations to truly reflect the specific conditions of the project, moving from "macro-level estimation" to "micro-level precision," significantly improving the scientific validity and credibility of the results.

[0021] Visualized analysis for efficient decision-making: Multi-dimensional visualization charts and automatically generated decision support reports transform complex carbon emission data into intuitive insights, greatly enhancing the practical value of this method in assisting green building design, construction, and operation and maintenance decisions. Attached Figure Description

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 A schematic diagram of the carbon source structure tree model involved in an embodiment of the present invention is shown; Figure 2 An overall flowchart of the method involved in the embodiments of the present invention is shown; Figure 3 A schematic diagram illustrating the data extraction of the BIM rule engine involved in an embodiment of the present invention is shown. Detailed Implementation

[0023] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0024] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0025] like Figures 1 to 3 As shown, a building carbon emission measurement method based on the entire life cycle of a building project according to an embodiment of the present invention includes the following steps: S1: Project initialization and carbon source tree instantiation. Based on the type of the building project, a pre-set carbon source structure tree template is invoked to generate a hierarchical carbon source tree instance specific to the project. The carbon source structure tree includes, from top to bottom: Root node L0: Carbon emissions from building construction projects; Level 1 Node L1: Five stages of the entire life cycle, namely A1-A3 building material production and transportation stage, A4-A5 construction stage, B1-B7 building operation stage, C1-C4 building demolition stage, and D waste treatment and recycling potential stage; Level 2 (L2): Specific activity categories formed by refining each Level 1 node; Level 3 leaf node L3: corresponds to a specific carbon emission activity or material consumption; each leaf node has predefined standardized data attributes, including activity name, unit of measurement, data collection method and factor code; S2: Multi-source data fusion and intelligent parameter acquisition, which fills the leaf node data of the carbon source tree instance through a multi-path parallel approach, specifically including: S2.1 Automatic extraction of BIM data based on rule engine: Import BIM model in IFC format, use pre-stored mapping rules to identify component types and material properties in BIM model, automatically extract corresponding data and map to the corresponding leaf nodes of carbon source tree; S2.2 External database association based on API interface: Query data such as energy consumption of construction machinery through the API interface of the equipment database, and populate the query results into the corresponding nodes of the carbon source tree; S2.3 Graphical Interactive Interface Manual Supplement: Through a graphical form integrating map services, users are guided to input dynamic parameters, including transportation distance and regional power grid carbon emission factor; S3: Context-aware carbon emission calculation and aggregation: Traverse all leaf nodes of the carbon source tree, match accurate carbon emission factors from the dynamic factor database according to node type and context information, calculate the carbon emission of each leaf node using the formula node carbon emission = activity amount × matched carbon emission factor, and then aggregate to the root node in a bottom-up order to obtain the total carbon emission of the building project throughout its entire life cycle. S4: Multidimensional results visualization and decision support report generation visualization charts, including automatically generated pie charts of carbon emission composition throughout the entire life cycle, bar charts of carbon emission hotspot analysis, and radar charts comparing multiple design schemes. At the same time, a structured decision support report is generated that includes calculation basis, data source, carbon emission details, carbon hotspot analysis, and emission reduction optimization suggestions.

[0026] In this embodiment, by constructing a four-level hierarchical carbon source tree (L0-L3) and supporting rapid instantiation for different types of projects, it achieves comprehensive coverage and standardized measurement of carbon sources across the five stages of the building's entire lifecycle, while also taking into account the personalized needs of projects and data traceability. Relying on a multi-path parallel acquisition method that combines automatic BIM data extraction, external database API association, and graphical manual supplementation, it effectively reduces reliance on manual labor and data errors, improves the efficiency, timeliness, and adaptability of data acquisition, and ensures that the data source is verifiable. By leveraging context-aware dynamic factor matching and standardized calculation models, the limitations of traditional fixed factor application are overcome, significantly improving the accuracy of carbon emission measurement and enabling dynamic adaptation to policy and regional differences. By automatically generating various types of visual charts and structured decision support reports that include carbon hotspot analysis and emission reduction recommendations, a closed loop from simple measurement to decision support is achieved. This effectively solves the core problems of existing methods, such as incomplete carbon source coverage, low data collection efficiency, insufficient calculation accuracy, and limited application value of results. It can be widely applied to the entire life cycle carbon emission measurement and carbon management of various building projects, providing a scientific basis for low-carbon design, construction optimization, and emission reduction retrofitting, and helping the construction industry achieve its carbon emission reduction targets. In the above embodiments, preferably, the dynamic factor database is configured with a real-time update module; the real-time update module automatically synchronizes carbon emission factor data periodically through authoritative data sources, and the synchronization frequency can be configured as weekly, monthly or quarterly according to project needs; the real-time update module is linked with the dynamic factor matching process in step S3 to ensure that the matched carbon emission factors are the latest valid data.

[0027] In this embodiment, the real-time update module of the dynamic factor database configuration realizes the dynamic iteration of carbon emission factors through regular automatic synchronization with authoritative data sources and a configurable synchronization frequency design. This effectively solves the technical problems of traditional factor databases being outdated and unable to adapt to changes in policy standards and regional carbon emission levels. At the same time, the linkage mechanism between this module and the S3 dynamic factor matching process ensures that the factors called during the calculation process are always the latest valid data, significantly improving the timeliness and accuracy of the full life cycle carbon emission measurement results and ensuring that the measurement results comply with current industry standards and policy requirements.

[0028] In any of the above embodiments, preferably, the rule engine in step S2.1 has a built-in intelligent BIM data conflict processing submodule; when there are numerical differences in the same type of data extracted from multiple IFC files, the intelligent BIM data conflict processing submodule calculates the confidence level based on the data source credibility weight, file version timeliness and data integrity, and automatically selects the data with the highest confidence level to fill the corresponding node of the carbon source tree; if the confidence level difference between different data is lower than a preset threshold, the user is prompted to manually confirm through a graphical interface.

[0029] In this embodiment, the BIM data conflict intelligent processing submodule built into the rules engine realizes automated identification and screening of data conflicts from the same source in multiple IFC files through a confidence calculation model based on three dimensions: data source credibility weight, document version timeliness, and data integrity. This effectively avoids the subjective errors and efficiency losses of manual judgment of data conflicts. The manual confirmation prompt mechanism when the confidence difference is lower than the threshold takes into account both the efficiency of automated processing and the need for manual decision-making in special scenarios, ensuring that the data filled into the carbon source tree node has optimal credibility, providing a high-quality data foundation for subsequent carbon emission calculations, and further improving the reliability of measurement results.

[0030] In any of the above embodiments, preferably, the D node of the carbon source structure tree is associated with a dynamic calculation sub-model for the efficiency of the dismantling and recycling stage; the dynamic calculation sub-model for the efficiency of the dismantling and recycling stage is set with three dynamic parameter input ports: recycling process type, waste classification qualification rate, and recycled material utilization rate. The carbon emission reduction potential of the recycling stage is calculated by the formula: carbon emission reduction of the recycling stage = total waste × recycled material conversion rate × corresponding material production carbon emission factor × recycling efficiency coefficient. The calculation results are synchronized to the hierarchical summary process in step S3.

[0031] In this embodiment, the dynamic calculation sub-model for the efficiency of the demolition and recycling stages, associated with node D of the carbon source structure tree, constructs a scientifically quantifiable calculation model for the carbon emission reduction potential of the recycling stage by inputting three core dynamic parameters: recycling process type, waste classification qualification rate, and recycled material utilization rate. This breaks through the limitations of traditional measurement methods that "emphasize carbon emission accounting and neglect emission reduction potential assessment" in the demolition and recycling stages. The calculation results of this sub-model are synchronized to the S3 level aggregation process, realizing the integrated accounting of "total carbon emissions - emission reduction potential value," making the carbon emission measurement results of the entire building life cycle more comprehensive, and providing accurate data support for the formulation of low-carbon solutions in the project's demolition and recycling stages.

[0032] In any of the above embodiments, preferably, step S3 further includes a machine learning-driven carbon emission prediction sub-step; the carbon emission prediction sub-step trains a gradient boosting model based on the full life cycle carbon emission data of similar historical projects, inputs the carbon emission data of the completed stages of the current project and project characteristic parameters, the project characteristic parameters including building structure type, regional information, and construction technology, and outputs the carbon emission prediction value of the subsequent uncompleted stages; the carbon emission prediction value and the actual calculated value of the corresponding stage are compared and displayed in the visualization chart in step S4.

[0033] In this embodiment, the newly added machine learning-driven carbon emission prediction sub-step in S3, based on the training of the gradient boosting model and historical data of similar projects, combined with the data and feature parameters of the completed stages of the current project, achieves accurate prediction of carbon emissions for the uncompleted stages. The comparison and display of the predicted and actual calculated values ​​in the visualization chart in S4 constructs a closed-loop management mechanism of "real-time measurement - prediction and early warning - deviation analysis". This effectively solves the pain point of traditional measurement methods, which can only retrospectively calculate the completed stages and cannot predict the risk of carbon emission overruns in advance. It helps project managers adjust low-carbon strategies in a timely manner at all stages of the entire life cycle and achieve forward-looking management of carbon emissions.

[0034] In any of the above embodiments, preferably, a multi-user permission hierarchical management module is also included; the multi-user permission hierarchical management module divides user roles into designers, construction personnel, operation and maintenance personnel, and system administrators; among them, designers only have the permission to import BIM data and query carbon emissions of design schemes, construction personnel can supplement dynamic data during the construction phase and view carbon emission analysis results during the construction phase, operation and maintenance personnel have the permission to update energy consumption data during the building operation phase, and system administrators have the permission to modify data throughout the entire process, configure permissions, and audit logs; the multi-user permission hierarchical management module forms an access control association with the data acquisition stage in step S2 and the report generation stage in step S4.

[0035] In this embodiment, the multi-user permission hierarchical management module achieves full-process access control for data collection, querying, and modification operations by finely dividing permissions for designers, construction personnel, maintenance personnel, and system administrators. The design of linking the permissions of different roles with the S2 data collection stage and the S4 report generation stage ensures the professionalism and relevance of data entry at each stage (e.g., construction personnel only supplement data for the construction stage) and avoids unauthorized personnel from misoperating the data. At the same time, the system administrator's log auditing permission enables full traceability of operational behavior, improving the security and management standardization of carbon emission measurement data, and adapting to the actual scenario of collaborative work among multiple participants in a construction project.

[0036] In any of the above embodiments, preferably, the multi-source data acquisition process in step S2 synchronously constructs a full-process data traceability chain; the data traceability chain records key information for each leaf node's fill data record, including the BIM file version number, API interface call address and timestamp, manually entered personnel ID and input time, and data modification log; the relevant data of the data traceability chain can be exported through the report generation module in step S4 as the audit basis for carbon emission measurement results.

[0037] In this embodiment, the full-process data traceability chain synchronously constructed during the S2 multi-source data acquisition process assigns complete traceability attributes to the data of each leaf node by recording key information such as BIM file version number, API call information, manually entered personnel ID, and modification log. The traceability chain data can be exported through the S4 report generation module, effectively solving the problems of untraceable data sources and difficulty in auditing and verification in traditional carbon emission measurement. This makes the measurement results "verifiable, traceable, and verifiable," meeting the compliance requirements of carbon measurement work and enhancing the credibility of measurement reports.

[0038] In any of the above embodiments, preferably, the visualization module in step S4 integrates a cross-project carbon emission benchmark comparison submodule; the cross-project carbon emission benchmark comparison submodule has a built-in industry carbon emission benchmark database of building projects of the same type and scale, calculates the difference between the total carbon emission of the current project and the carbon emission ratio of each stage and the benchmark value, displays the deviation range through a bar chart, and automatically identifies stages with deviations exceeding ±15% as key emission reduction analysis objects; the industry carbon emission benchmark database supports classification and filtering by region, building use, and construction year.

[0039] In this embodiment, the cross-project carbon emission benchmark comparison submodule integrated into the S4 visualization module realizes automatic difference calculation and visualization of the current project and the industry benchmark through a built-in industry carbon emission benchmark database of similar buildings of the same type and scale. The automatic identification function of deviation exceeding ±15% can quickly locate the gap between the project's carbon emission level and the industry benchmark, which solves the limitations of traditional measurement results that "lack horizontal comparison dimensions and difficulty in identifying key carbon emission reduction links". At the same time, the benchmark database's classification and filtering function by region, use and year improves the relevance of the comparison results and provides a clear direction for the project to formulate differentiated carbon emission reduction strategies.

[0040] In any of the above embodiments, preferably, the decision support report generation module in step S4 is associated with a quantitative evaluation sub-model for emission reduction measures; the quantitative evaluation sub-model for emission reduction measures has a built-in carbon emission reduction coefficient library for four types of emission reduction measures: low-carbon building material substitution, energy-saving equipment replacement, construction process optimization, and renewable energy utilization; after the user selects the target emission reduction measure, the system automatically calculates the theoretical emission reduction and emission reduction cost-benefit ratio based on the current carbon emission data of the project; the calculation results are included in the structured decision support report in the form of an appendix, and support the comparison of emission reduction effects of multiple emission reduction measure combinations.

[0041] In this embodiment, the emission reduction measure quantitative evaluation sub-model associated with the decision support report generation module, through a built-in carbon emission reduction coefficient library of four mainstream emission reduction measures, realizes the automated calculation of the theoretical emission reduction and cost-benefit ratio of emission reduction measures; the effect comparison function of multi-measure combination schemes overcomes the shortcomings of traditional emission reduction recommendations that are "mainly qualitative descriptions and lack quantitative data support"; the calculation results are included in the structured report in the form of appendices, providing project owners with an integrated decision-making basis for "measure selection - effect evaluation - cost accounting", which significantly improves the feasibility and practicality of decision support reports and helps projects efficiently formulate the optimal carbon emission reduction plan.

[0042] In any of the above embodiments, preferably, the carbon source tree structure is configured with a multi-standard adaptation and conversion module; the multi-standard adaptation and conversion module supports automatic adaptation to three mainstream carbon emission measurement standards: GB / T51366-2019, EN15978, and ISO21931. By adjusting the division of primary node stages, the definition of leaf node data attributes, and the carbon emission factor matching rules, it can realize the switching of carbon emission measurement under different standards and can simultaneously generate independent structured decision support reports for the corresponding standards; the multi-standard adaptation and conversion module is linked with the carbon source tree instantiation process in step S1, the factor matching process in step S3, and the report generation process in step S4.

[0043] In this embodiment, the multi-standard adaptation and conversion module configured in the carbon source tree structure supports automatic adaptation to the three major mainstream metrology standards GB / T51366-2019, EN15978, and ISO21931. This enables flexible switching of stage division, data attribute definition, and factor matching rules under different standards, solving the technical bottleneck of traditional metrology methods that can only adapt to a single standard and cannot meet the compliance requirements of multinational projects or multiple standards. The linkage between this module and the S1 carbon source tree instantiation, S3 factor matching, and S4 report generation processes can simultaneously generate independent structured decision support reports under different standards, significantly improving the universality and international adaptability of the method and meeting the carbon emission metrology standards requirements of different regions and different partners.

[0044] Based on the above, Figures 1 to 3 Accordingly, this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the building carbon emission measurement method based on the entire life cycle of any of the above embodiments.

[0045] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0046] Based on the above, Figures 1 to 3 To achieve the above objectives, this application also provides a computer device, including a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the steps of the building carbon emission measurement method based on the entire life cycle of any of the above embodiments.

[0047] Optionally, the computer device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB ports, card reader ports, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Bluetooth interfaces, Wi-Fi interfaces), etc.

[0048] Those skilled in the art will understand that the computer device structure provided in this embodiment does not constitute a limitation on the computer device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0049] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages and stores the hardware and software resources of a computer device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software within the physical device.

[0050] Implementation example: Taking the carbon emission measurement of a green office building as an example.

[0051] Initialization (S1): The system selects the "Office Building" template and instantiates the carbon source tree.

[0052] Data Acquisition (S2): S2.1: Import the BIM model. The rule engine automatically identifies and extracts the concrete volume of 2550m³ and the steel weight of 850 tons in the wall.

[0053] S2.2: When selecting construction machinery, users can choose "SCC1200C crawler crane" from the built-in database, and the system will automatically associate it with a fuel consumption of 45L / shift.

[0054] S2.3: When the user selects the steel supplier (Tangshan, Hebei) and the project location (Guangzhou, Guangdong) on ​​the map interface, the system automatically calculates the road transportation distance as 2200km.

[0055] Calculate (S3): The system matches the steel produced in Tangshan with the "average carbon emission factor of steel production in North China" and the electricity used in Guangzhou with the "carbon emission factor of the Southern Power Grid".

[0056] After calculating node by node, the total carbon emissions C are obtained by summing them up. total =15,800tCO2e.

[0057] Output (S4): The system generates a report and displays a pie chart, revealing that the "Building Materials Production and Transportation" stage accounts for as much as 48%, making it the primary key link in carbon emission reduction.

[0058] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for measuring carbon emissions from building projects based on their entire life cycle, characterized in that, Includes the following steps: S1: Project initialization and carbon source tree instantiation. Based on the type of the building project, the pre-set carbon source structure tree template is called to generate a hierarchical carbon source tree instance specific to the project. The carbon source structure tree, from top to bottom, includes: Root node L0: Carbon emissions from building construction projects; Level 1 Node L1: Five stages of the entire life cycle, namely A1-A3 building material production and transportation stage, A4-A5 construction stage, B1-B7 building operation stage, C1-C4 building demolition stage, and D waste treatment and recycling potential stage; Level 2 (L2): Specific activity categories formed by refining each Level 1 node; Level 3 leaf node L3: corresponds to a specific carbon emission activity or material consumption; each leaf node has predefined standardized data attributes, including activity name, unit of measurement, data collection method and factor code; S2: Multi-source data fusion and intelligent parameter acquisition, which fills the leaf node data of the carbon source tree instance through a multi-path parallel approach, specifically including: S2.1 Automatic extraction of BIM data based on rule engine: Import BIM model in IFC format, use pre-stored mapping rules to identify component types and material properties in BIM model, automatically extract corresponding data and map to the corresponding leaf nodes of carbon source tree; S2.2 External database association based on API interface: Query data such as energy consumption of construction machinery through the API interface of the equipment database, and populate the query results into the corresponding nodes of the carbon source tree; S2.3 Graphical Interactive Interface Manual Supplement: Through a graphical form integrating map services, users are guided to input dynamic parameters, including transportation distance and regional power grid carbon emission factor; S3: Context-aware carbon emission calculation and aggregation: Traverse all leaf nodes of the carbon source tree, match accurate carbon emission factors from the dynamic factor database according to node type and context information, calculate the carbon emission of each leaf node using the formula node carbon emission = activity amount × matched carbon emission factor, and then aggregate to the root node in a bottom-up order to obtain the total carbon emission of the building project throughout its entire life cycle. S4: Multidimensional results visualization and decision support report generation visualization charts, including automatically generated pie charts of carbon emission composition throughout the entire life cycle, bar charts of carbon emission hotspot analysis, and radar charts comparing multiple design schemes. At the same time, a structured decision support report is generated that includes calculation basis, data source, carbon emission details, carbon hotspot analysis, and emission reduction optimization suggestions.

2. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The dynamic factor database is equipped with a real-time update module; the real-time update module automatically synchronizes carbon emission factor data periodically through authoritative data sources, and the synchronization frequency can be configured to weekly, monthly or quarterly according to project needs; the real-time update module is linked with the dynamic factor matching process in step S3 to ensure that the matched carbon emission factors are the latest valid data.

3. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The rule engine in step S2.1 has a built-in intelligent BIM data conflict handling submodule; When there are numerical differences in the same type of data extracted from multiple IFC files, the BIM data conflict intelligent processing submodule calculates the confidence level based on the data source credibility weight, file version timeliness and data integrity, and automatically selects the data with the highest confidence level to fill the corresponding node of the carbon source tree. If the confidence difference between different data is lower than a preset threshold, the user will be prompted to confirm manually through a graphical interface.

4. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The D node of the carbon source structure tree is associated with a dynamic calculation sub-model for the efficiency of the dismantling and recycling stages. The dynamic calculation sub-model for the efficiency of the dismantling and recycling stages is set with three dynamic parameter input ports: recycling process type, waste classification qualification rate, and recycled material utilization rate. The carbon emission reduction potential of the recycling stage is calculated by the formula: carbon emission reduction of the recycling stage = total waste × recycled material conversion rate × corresponding material production carbon emission factor × recycling efficiency coefficient. The calculation results are synchronized to the hierarchical summary process in step S3.

5. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, Step S3 also includes a machine learning-driven carbon emission prediction sub-step; the carbon emission prediction sub-step trains a gradient boosting model based on the full life cycle carbon emission data of similar historical projects, inputs the carbon emission data of the completed stages of the current project and project characteristic parameters, the project characteristic parameters include building structure type, regional information, and construction technology, and outputs the carbon emission prediction value of the subsequent uncompleted stages; the carbon emission prediction value and the actual calculated value of the corresponding stage are compared and displayed in the visualization chart in step S4.

6. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, It also includes a multi-user hierarchical access control module; this module divides user roles into designers, construction personnel, operation and maintenance personnel, and system administrators; among them, designers only have the right to import BIM data and query carbon emissions of design schemes, construction personnel can supplement dynamic data during the construction phase and view carbon emission analysis results during the construction phase, operation and maintenance personnel have the right to update energy consumption data during the building operation phase, and system administrators have the right to modify data throughout the entire process, configure permissions, and audit logs; the multi-user hierarchical access control module is associated with the data acquisition stage in step S2 and the report generation stage in step S4.

7. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, In step S2, the multi-source data acquisition process synchronously constructs a full-process data traceability chain; the data traceability chain records key information for each leaf node's populated data, including the BIM file version number, API interface call address and timestamp, manually entered personnel ID and input time, and data modification log; the relevant data of the data traceability chain can be exported through the report generation module in step S4 as the audit basis for carbon emission measurement results.

8. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The visualization module in step S4 integrates a cross-project carbon emission benchmark comparison sub-module. This sub-module has a built-in industry carbon emission benchmark database for building projects of the same type and scale. It calculates the difference between the total carbon emissions of the current project and the carbon emission ratio of each stage and the benchmark value, displays the deviation range through a bar chart, and automatically identifies stages with deviations exceeding ±15% as key emission reduction analysis targets. The industry carbon emission benchmark database supports classification and filtering by region, building use, and construction year.

9. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The decision support report generation module in step S4 is associated with a quantitative evaluation sub-model for emission reduction measures. This sub-model contains a carbon emission reduction coefficient library for four types of emission reduction measures: low-carbon building material substitution, energy-saving equipment replacement, construction process optimization, and renewable energy utilization. After the user selects a target emission reduction measure, the system automatically calculates the theoretical emission reduction and the emission reduction cost-benefit ratio based on the project's current carbon emission data. The calculation results are included in the structured decision support report in the form of an appendix, and the system supports the comparison of emission reduction effects of multiple emission reduction measure combinations.

10. The method for measuring carbon emissions from building construction based on the entire life cycle as described in claim 1, characterized in that, The carbon source tree structure is configured with a multi-standard adaptation and conversion module. The multi-standard adaptation and conversion module supports automatic adaptation to three mainstream carbon emission measurement standards: GB / T51366-2019, EN15978, and ISO21931. By adjusting the stage division of the first-level nodes, the data attribute definition of the leaf nodes, and the carbon emission factor matching rules, it can realize the switching of carbon emission measurement under different standards and can simultaneously generate independent structured decision support reports for the corresponding standards. The multi-standard adaptation and conversion module is linked with the carbon source tree instantiation process in step S1, the factor matching process in step S3, and the report generation process in step S4.

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