BIM evaluation management method for building carbon emission full life cycle

Abstract

This invention discloses a BIM-based evaluation and management method for the entire lifecycle of building carbon emissions. It acquires basic data from each stage of the building's lifecycle and establishes a dynamic carbon emission factor database. Based on the IFC standard, it expands the physical structure of building components to construct an extended BIM model embedding carbon monitoring sensors and carbon data attributes. Based on this extended BIM model, it integrates dynamic carbon emission factors and achieves accurate calculation of carbon emissions at each stage through a self-inherent dynamic calculation model. Through dynamic sensitivity analysis, it identifies key parameters and formulates emission reduction measures, forming a closed-loop management system of "analysis-optimization-verification." This invention solves the problems of lack of dynamism in carbon emission factors, lack of full-stage automation in the calculation process, and lack of a closed-loop optimization mechanism in existing technologies, significantly improving the accuracy, real-time performance, and optimization effect of building carbon emission calculation.

Description

Technical Field

[0001] This invention relates to the field of green building technology, and in particular to a BIM evaluation and management method for the entire life cycle of building carbon emissions. Background Technology

[0002] Against the backdrop of global efforts to address climate change, the construction industry, as one of the major sources of carbon emissions, accounts for a high proportion of carbon emissions throughout its entire life cycle, and urgently needs precise and dynamic carbon emission management methods.

[0003] In existing technologies, carbon emission measurement methods based on BIM and life cycle assessment (LCA) have been applied, but the following problems still exist: carbon emission factors lack dynamism and regional adaptability; the measurement process has not achieved full-stage automated integration; there is a lack of closed-loop optimization mechanisms based on sensitivity analysis; and carbon data management lacks unified standards, making cross-platform exchange and traceability difficult.

[0004] Therefore, this invention proposes a BIM carbon data management system that integrates IFC standards, IoT monitoring, and a dynamic factor library to achieve closed-loop management of the entire process from data acquisition and calculation to optimization feedback. Summary of the Invention

[0005] This invention provides a BIM-based evaluation and management method for the entire lifecycle of building carbon emissions to overcome the aforementioned technical problems.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows: A BIM-based evaluation and management method for the entire lifecycle of building carbon emissions includes the following steps: S1: Investigate relevant data on building projects throughout the entire building lifecycle and define the spatial and temporal boundaries for carbon emission calculations; The spatial boundary is used to characterize the physical structural components of the building and the configuration system that meets the building's usage; the temporal boundary is used to characterize the time span of each building stage within the entire life cycle, and the building stage includes the construction stage, operation stage, maintenance stage, and demolition stage. S2: Define a carbon emission factor database; the carbon emission factors include, but are not limited to, configuration system energy consumption, human factors, building materials, and machinery shift factors; at the same time, based on empirical values ​​and the actual application results of building projects, adjust the carbon emission factor database to obtain a dynamic carbon emission factor database. S3: Obtain the original IFC dictionary file, and based on the IFC standard, add the building's carbon monitoring sensor space to the original IFC dictionary file according to the building's spatial boundaries; add the pre-set structural elements of different types of carbon monitoring sensor entities to the carbon monitoring sensor space to obtain the physical element system of the building carbon monitoring sensor; add attribute sets to the types of carbon monitoring sensor entities in the physical element system; the attribute set addition is to add sensor data attributes corresponding to the carbon monitoring sensor type to the physical element system, obtain the carbon monitoring sensor type IFC dictionary file, and then form the building carbon monitoring sensor type IFC file based on the carbon monitoring sensor type IFC dictionary file; at the same time, based on the BIM management platform, define carbon calculation data entities for the building carbon monitoring sensor type IFC file and configure the entity attribute set of the carbon calculation data entities to obtain an extended BIM model integrating carbon monitoring sensor entities and carbon calculation data entities; S4: Based on the extended BIM model, a self-emergent dynamic calculation model for building carbon emissions is constructed according to the carbon emission dynamic factor database and time boundaries; the self-emergent dynamic calculation model for building carbon emissions includes a carbon emission calculation model for the construction phase, a carbon emission calculation model for the operation phase, a carbon emission calculation model for the maintenance phase, a carbon emission calculation model for the demolition phase, a carbon emission calculation model per unit area of ​​the building, and a carbon emission calculation model per unit area per year; the calculation results of the self-emergent dynamic calculation model for building carbon emissions are used as the calculation results for the entire life cycle of building carbon emissions; S5: Perform dynamic sensitivity analysis on the calculation results of building carbon emissions throughout the entire life cycle to obtain key parameters affecting building carbon emissions; the key parameters include, but are not limited to, material consumption, machinery consumption, dynamic technology correction coefficient, and stage weight coefficient. Simultaneously, based on the BIM platform, the dynamic range of each key parameter is set, and based on the dynamic range of the change and combined with the self-inherent dynamic calculation model of building carbon emissions, the simulation calculation results of the building carbon emissions throughout the entire life cycle corresponding to the key parameters with different values ​​are simulated and obtained. The sensitivity index is obtained by comparing the degree of impact of the numerical change of each key parameter on the total carbon emissions throughout the building's life cycle. The key parameters whose sensitivity index exceeds the preset threshold are identified as the most sensitive parameters with the greatest impact on carbon emissions. S6: Based on empirical values ​​and sensitivity parameters, formulate emission reduction measures for each building stage to update the entity attribute set of carbon calculation data entities; the emission reduction measures include, but are not limited to, replacing high-carbon building materials, optimizing energy structure, and adjusting maintenance cycles; S7: Apply the emission reduction measures to the extended BIM model, and repeat steps S4 to S6 to recalculate carbon emissions and verify the optimization effect, ultimately forming a closed loop of carbon emission measurement and optimization, thereby realizing BIM evaluation and management of building carbon emissions throughout the entire life cycle.

[0007] Furthermore, step S4 specifically includes the following steps: S41: Load the extended BIM model into the preset BIM management platform; By identifying the carbon calculation data entities in the extended BIM model and reading the calculation parameters in their respective entity attribute sets; and the calculation parameters include, but are not limited to, carbon emission factor association identifiers, labor consumption, material consumption, machine shift consumption, dynamic technology correction coefficients, and stage weight coefficients; S42: Based on the calculation parameters, execute the self-inherent dynamic calculation model of building carbon emissions according to the carbon emission dynamic factor database and the time boundary; the self-inherent dynamic calculation model of building carbon emissions includes a carbon emission calculation model for the construction stage, a carbon emission calculation model for the operation stage, a carbon emission calculation model for the maintenance stage, a carbon emission calculation model for the demolition stage, a carbon emission calculation model for building unit area, and a carbon emission calculation model for annual carbon emissions per unit area. S43: Use the calculation results of the self-inherent dynamic calculation model of building carbon emissions as the calculation results of building carbon emissions throughout the entire life cycle.

[0008] Furthermore, the carbon emission calculation model for the construction phase described in S42 is as follows:

[0009] In the formula: This indicates the annual carbon emissions during the building's construction phase; These represent the consumption of labor, materials, and machine shifts for the k-th construction sub-project, respectively. These represent the carbon emission factors of labor, materials, and machinery shifts for the kth construction sub-project, respectively. This represents the elasticity coefficient of human efficiency; Indicates the material synergistic effect factor; Indicates the mechanical time-sensitive factor; Indicates the duration of a sub-item of work; represents the carbon emission adjustment coefficients for labor, materials, and machinery shifts for the k-th construction sub-project, respectively; n represents the total number of all sub-projects in the construction phase that require separate carbon emission calculations.

[0010] Furthermore, the carbon emission calculation model for the operation phase described in S42 is as follows:

[0011] In the formula: This indicates the annual carbon emissions during the building's operational phase. An energy consumption function representing the changes in electricity, fuel, and renewable resources over time; ω represents the dynamic carbon emission factor related to electricity, fuel, and renewable resources in the energy structure; ω represents the elasticity of renewable energy substitution. Y represents the maximum amount of renewable energy that can be substituted; Y represents the building's service life. These represent the carbon emission adjustment factors for electricity, fuel, and renewable resources, respectively.

[0012] Furthermore, the carbon emission calculation model for the maintenance phase described in S42 is as follows:

[0013] In the formula: This indicates the annual carbon emissions during the building maintenance phase; These represent the carbon emission adjustment factors for labor, materials, and machinery shifts for the kth construction sub-project, respectively. Indicates the area of ​​the maintenance zone; k Indicates the factors affecting the area of ​​the maintenance zone; k This represents the logarithmic correction factor for building materials; Indicates the maintenance cycle; represents the maintenance cycle sensitivity coefficient; m represents the total number of all sub-maintenance tasks in the maintenance phase that require separate calculation of carbon emissions.

[0014] Furthermore, the carbon emission calculation model for the demolition phase described in S42 is as follows:

[0015] In the formula: This indicates the annual carbon emissions during the building demolition phase. Indicates the carbon emission factor of recyclable carbon sources; Indicates the amount of recyclable carbon engineering work; Indicates the demolition efficiency factor; Indicates the area to be demolished; Indicates the material size correction factor; Indicates the mechanical time-sensitive factor; Indicates the machine's operating time; Indicates the gain coefficient of the recycling technology; represents the carbon emission adjustment coefficients for the k-th sub-item (labor, materials, machinery shifts, and recyclable carbon sources), respectively; p represents the total number of all sub-item demolition tasks that require separate carbon emission calculation during the demolition phase.

[0016] Furthermore, the carbon emission calculation model per unit area and the annual carbon emission calculation model per unit area described in S42 are as follows:

[0017]

[0018]

[0019] In the formula: Represents total life-cycle carbon emissions; S represents total building area; γ represents building function adjustment coefficient; δ represents area adjustment coefficient; η represents area scale effect factor; κ represents scale decay coefficient; μ represents area logarithmic correction factor; S0 represents baseline area; C d ε represents carbon emissions per unit area; N represents the building's design service life; ε represents the time adjustment factor; ζ represents the stage time adjustment factor; ν represents the age-related decay factor; λ represents the decay rate; and ξ represents the technology update dynamic factor. Indicates the technology update cycle; C m This indicates the carbon emissions per unit of building area per year. Indicates the first i Carbon emissions at each stage of construction i =1~4; Represents the dynamic technical correction coefficient and ; Indicates the initial correction factor; The 't' represents the rate of technological decay; 't' represents the time variable. Indicates the stage weight coefficient; This represents the nonlinear decay factor; Indicates the rate of decay over time; This represents the logarithmic adjustment factor; Indicates the first i The duration of the construction phase.

[0020] Furthermore, the stage weight coefficient The method for obtaining these values ​​is based on principal component analysis (PCA) to obtain the stage weight coefficients. The specific steps include: S100: Obtain carbon emission data for each stage of the entire life cycle of several historical building projects, forming a data matrix with n samples; S101: Perform Z-score normalization on the data matrix; the expression is as follows:

[0021] In the formula: This represents the average carbon emissions in stage j. This represents the standard deviation of carbon emissions in stage j; Indicates the first i The carbon emissions corresponding to stage j for each construction project; Indicates the Z-score after standardization. i The carbon emissions corresponding to stage j for each construction project; S102: The covariance matrix is ​​calculated based on the data matrix after Z-score standardization:

[0022] In the formula: This represents the data matrix after Z-score normalization; express transpose; Represent the covariance matrix; S103: Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues. With feature vectors ; S104: Based on eigenvalues The variance contribution rate is:

[0023] In the formula: Represents all eigenvalues The sum; Simultaneously, the eigenvalues ​​are sorted in descending order according to the variance contribution rate to obtain the sequence list, and the first two eigenvalues ​​are selected as principal components; at the same time, the eigenvectors corresponding to the principal components are used as the principal component eigenvectors. S105: Based on the eigenvalues ​​of the principal components and the principal component eigenvectors, the principal component loading vectors are obtained as follows:

[0024] In the formula: V represents the principal component eigenvector matrix; Λ represents the eigenvalue diagonal matrix; Represents the principal component loading vector; S106: Summate and normalize the absolute values ​​of the principal component loadings to obtain the stage weight coefficients. for:

[0025] In the formula: This represents an element in the principal component loading vector.

[0026] Beneficial Effects: This invention provides a BIM-based evaluation and management method for the entire lifecycle of building carbon emissions. It acquires basic data from each stage of the building's lifecycle and establishes a dynamic carbon emission factor database. Based on the IFC standard, it expands the physical structure of building components to construct an extended BIM model embedding carbon monitoring sensors and carbon data attributes. Based on this extended BIM model, it integrates dynamic carbon emission factors and achieves accurate calculation of carbon emissions at each stage through a self-inherent dynamic calculation model. Through dynamic sensitivity analysis, it identifies key parameters and formulates emission reduction measures, forming a closed-loop management system of "analysis-optimization-verification." This invention solves the problems of lack of dynamism in carbon emission factors, lack of full-stage automation in the calculation process, and lack of a closed-loop optimization mechanism in existing technologies, significantly improving the accuracy, real-time performance, and optimization effect of building carbon emission calculation. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 The flowchart is for the BIM evaluation and management method of building carbon emissions throughout the entire life cycle of this invention. Figure 2 This is a model entity relationship diagram of the carbon monitoring sensor space in this embodiment; Figure 3 This is the entity relationship diagram of the IFC extended data model in this embodiment. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] This embodiment provides a BIM-based evaluation and management method for the entire lifecycle of building carbon emissions, such as... Figure 1 As shown, the specific steps include: S1: Investigate relevant data of building projects throughout the entire life cycle of a building, and define the spatial and temporal boundaries for carbon emission calculations; the spatial boundary is used to characterize the physical structural components of the building and the configuration system that meets the building's use; the temporal boundary is used to characterize the time span of each building stage within the entire life cycle, and the building stage includes the construction stage, operation stage, maintenance stage, and demolition stage; Specifically, this embodiment utilizes IoT and sensor technologies to collect relevant data about the construction project in real time, clarifying the calculation content and defining the system boundaries, including: S11: Collect relevant data for the building project and clarify the calculation content, including building name, location, climate conditions, and design service life. Utilize IoT and sensor technologies for real-time data acquisition to ensure data accuracy and timeliness; define system boundaries covering the construction, operation, maintenance, and demolition phases throughout the building's entire lifecycle; reduce input errors and ensure data accuracy through pre-set dual entry and verification mechanisms; and establish data monitoring and alarm mechanisms to promptly detect and handle data anomalies and missing data. S12: The calculation content includes emission types, calculation indicators, units, and system boundaries. Greenhouse gases emitted by buildings include carbon dioxide (CO2), methane (CH4), perfluorocarbons (PFCs), nitrous oxide (N2O), hydrofluorocarbons (HFCs), and sulfur hexafluoride (SF6). The amount of these gases emitted is expressed as carbon dioxide (CO2). Therefore, the calculated carbon emissions are not just CO2 emissions, but the sum in the form of greenhouse gas emission equivalents. Clearly define the calculation indicators and corresponding units for each level, using the unit of measurement of carbon dioxide emission equivalent per ton (tCO2eq) to statistically analyze the total carbon emissions generated at each stage of the building's life cycle, expressed as CO2 emission equivalent per unit building area (kgCO2eq / m²). 2 The contribution of a certain part, material, or stage to carbon emissions per unit area is incorporated into the indicator measurement system, using the time period converted to years. The CO2 emission equivalent per unit building area per year for each stage is used as the indicator measurement. 2 •a) As an accounting unit, carbon emissions of different years and different building areas are uniformly measured; the process, node and location for calculating carbon emissions are determined. In this embodiment, the scope of the system boundary is considered from both time and space perspectives: the spatial boundary refers to certain systems that constitute the physical organization of the building or meet the use of the building, such as the reinforced concrete that constitutes the building itself, and related systems that meet the basic functions of the building (such as HVAC system, lighting system, water supply and drainage system, etc.). Other equipment added during the operation of the building is not considered in the carbon emissions of this building; the time boundary refers to the time span of each stage within the entire life cycle.

[0031] S2: Define a carbon emission factor database; the carbon emission factors include, but are not limited to, configuration system energy consumption, human factors, building materials, and machinery shift factors; at the same time, based on empirical values ​​and the actual application results of building projects, adjust the carbon emission factor database to obtain a dynamic carbon emission factor database. Specifically, buildings are divided into stages based on the Life Cycle Assessment (LCA) methodology. A refined database of carbon emission factors is constructed using inventory analysis, and then compared and verified against international standards (such as ISO 14044), including: S21: From the perspective of LCA, the life cycle of a building is divided into four phases: construction phase, operation phase, maintenance phase, and demolition phase; S22: Utilize inventory analysis to construct a refined database of carbon emission factors, covering multiple dimensions such as energy consumption, labor, materials, and machine hours; The refined carbon emission factor database is constructed using Life Cycle Assessment (LCA) as the core methodology and inventory analysis as the specific means. It incorporates the characteristics of the four stages of the building's entire life cycle and completes its construction through five core steps: stage division, factor dimension analysis, data collection and calibration, international standard verification, and dynamic updating. Simultaneously, it covers multiple dimensions of factors such as energy consumption, labor, materials, and machinery usage, ensuring the database's refinement, standardization, and dynamism. The core construction steps of the refined carbon emission factor database are as follows: Based on the LCA method, the four stages of the building life cycle are defined to determine the dimensional boundaries of the database. First, the building life cycle is divided into four stages—construction, operation, maintenance, and demolition—using the LCA method as the primary classification dimension of the database. This ensures accurate matching of factors with the carbon emission scenarios throughout the building process, avoiding missing factors or scenario mismatches. Then, through inventory analysis, the subdivided dimensions of carbon emission factors at each stage are identified: using inventory analysis as the core, the carbon emission sources at each stage are comprehensively broken down, identifying four core subdivided dimensions: energy consumption, labor, materials, and machinery hours. Simultaneously, for stages such as operation and demolition, specific dimensions such as renewable energy and recyclable carbon sources are added, forming a two-dimensional factor system of "stage + subdivided dimensions," achieving refined factor breakdown. Multi-channel data collection ensures data accuracy and industry adaptability: For factors of different dimensions, basic data is collected from multiple channels, including authoritative international databases, national / industry standards, enterprise measured data, and research institution reports, balancing international applicability and regional adaptability. In this embodiment, material and machinery factors reference international lifecycle databases such as Ecoinvent and GaBi, combined with domestic standards such as the "Building Carbon Emission Calculation Standard" (GB / T51366-2019) and the "China Construction Machinery Energy Consumption and Emission Standard." Energy consumption factors in this embodiment adopt energy carbon emission factors published by the National Development and Reform Commission and local power grids, supplemented by renewable energy factors from IPCC reports. For labor and recycling factors in this embodiment, specialized accounting guidelines / research reports from construction industry research institutions (such as the China Academy of Building Research) and international industry associations (such as the International Iron and Steel Institute) are referenced. Simultaneously, the database is compared and verified against international standards to ensure standardization and compatibility: the collected and calibrated factor data is compared and verified with internationally recognized standards such as ISO 14044 (Environmental Management Life Cycle Assessment Requirements and Guidelines) to verify the calculation methods, units, and statistical scope of the factors, ensuring consistency with international standards and solving the problem of cross-platform exchange and traceability of carbon data.

[0032] S23: Establish a dynamic adjustment mechanism to achieve continuous database updates: that is, based on the actual project application results, industry technological progress, energy policy adjustments, and changes in regional energy structure (e.g., increased penetration of renewable energy, upgrade of material production processes), the factors in the database are calibrated and updated in real time to avoid the static defects of factors and ensure the timeliness of carbon emission calculations.

[0033] S3: Obtain the original IFC dictionary file, and based on the IFC standard, add the building's carbon monitoring sensor space to the original IFC dictionary file according to the building's spatial boundaries; add the pre-set structural elements of different types of carbon monitoring sensor entities to the carbon monitoring sensor space to obtain the physical element system of the building carbon monitoring sensor; add attribute sets to the types of carbon monitoring sensor entities in the physical element system; the attribute set addition is to add sensor data attributes corresponding to the carbon monitoring sensor type to the physical element system, obtain the carbon monitoring sensor type IFC dictionary file, and then form the building carbon monitoring sensor type IFC file based on the carbon monitoring sensor type IFC dictionary file; at the same time, based on the BIM management platform, define carbon calculation data entities for the building carbon monitoring sensor type IFC file and configure the entity attribute set of the carbon calculation data entities to obtain an extended BIM model integrating carbon monitoring sensor entities and carbon calculation data entities; In this embodiment, based on the IFC standard, an extended BIM model is constructed that embeds the carbon monitoring sensor entity and the full life cycle carbon data structure, such as... Figures 2 to 3 Specifically, it is shown as follows: S31: Obtain the original IFC dictionary file; S32: Based on the IFC standard, define the carbon monitoring sensor space in the original IFC dictionary; Specifically, under the IFC spatial structure class (IfcSpatialStructuralElement), a new carbon monitoring sensor space class (IfcCarbonSensorSpace) is added as the spatial entity of the building carbon monitoring sensor. The spatial entity enumeration type of the building carbon monitoring sensor (IfcCarbonSensorSpaceTypeEnum) is added through the predefined type attribute definition method (PreDefinedType), thereby deriving the energy consumption monitoring sensor space (IfcEnergyMonitoringSpace), material carbon emission monitoring sensor space (IfcMaterialCarbonSpace), and environmental parameter monitoring sensor space (IfcEnvironmentalParamSpace). S33: Expand the carbon monitoring sensor entity by adding various types of sensor structural elements into the sensor space: Under the general class of physical structural elements in the IFC model (IfcElement), add a building carbon monitoring element (IfcCarbonMonitoringElement) to make it at the same level as the building element entity (IfcBuildingElement). Then, based on IfcCarbonMonitoringElement, expand downward to create an abstract entity of physical elements for building carbon monitoring sensors (IfcCarbonSensorElement) as the parent class of all sensor entities. The IfcCarbonSensorElement derives into the IfcEnergyMonitoringSensor, IfcMaterialCarbonSensor, and IfcEnvironmentalParamSensor, forming the physical element system of building carbon monitoring sensors. Further expansion is based on the IFC standard, using IfcCarbonMonitoringElement as the parent class for manual standardization. Its core is achieved by setting abstract entity attributes, clarifying inheritance relationships, and defining derivation rules. In this embodiment, attribute sets are added to each sensor entity defined in step S33, making it include the various attributes shown in Table 1, forming a building carbon monitoring sensor type IFC dictionary file, and generating a building carbon monitoring sensor type IFC file accordingly. Table 1. Attributes contained in each sensor entity

[0034] S34: In this embodiment, to achieve accurate carbon emission calculation at each stage of construction, while expanding the sensor entity, the data structure required for calculation is directly bound to it, adding a new entity named Carbon Calculation Data Entity (IfcCarbonCalculationData). This entity is associated with the abstract entity of the physical element of the building carbon monitoring sensor (IfcCarbonSensorElement) and its associated building components (IfcBuildingElement) through a set relationship entity (IfcRelAssociates). The Carbon Calculation Data Entity (IfcCarbonCalculationData) is used to provide all the required parameters, intermediate results, and final results for the self-inherent dynamic calculation model of building carbon emissions in step S4. Its specific attribute set definition is shown in Table 2: Table 2. IfcCarbonCalculationData Entity Attribute Set

[0035] S35: In this embodiment, an extended BIM model file (i.e., the building carbon monitoring and calculation integrated IFC file) of the integrated sensor entity and carbon calculation data entity (IfcCarbonCalculationData) is obtained; the structured containers of all input data (consumption, coefficients, factor correlations) and output data required for the stage carbon emission calculation in step S4 have been prepared in the IFC model, laying the data foundation for the subsequent self-inherent dynamic calculation model and closed-loop management of building carbon emissions.

[0036] S4: Based on the extended BIM model, a self-emergent dynamic calculation model for building carbon emissions is constructed according to the carbon emission dynamic factor database and time boundaries; the self-emergent dynamic calculation model for building carbon emissions includes a carbon emission calculation model for the construction phase, a carbon emission calculation model for the operation phase, a carbon emission calculation model for the maintenance phase, a carbon emission calculation model for the demolition phase, a carbon emission calculation model per unit area of ​​the building, and a carbon emission calculation model per unit area per year; the calculation results of the self-emergent dynamic calculation model for building carbon emissions are used as the calculation results for the entire life cycle of building carbon emissions; The specific steps include: S41: Load the extended BIM model into the preset BIM management platform; identify the carbon calculation data entities in the extended BIM model and read the calculation parameters in the corresponding entity attribute set; and the calculation parameters include, but are not limited to, carbon emission factor association identifier, labor consumption, material consumption, machine shift consumption, dynamic technology correction coefficient and stage weight coefficient. In this embodiment, the extended BIM model containing the IfcCarbonCalculationData entity obtained in step S35 is loaded into the BIM management platform, and the following initialization operations are performed: S411: Parse Calculation Data Entities: Automatically identify all IfcCarbonCalculationData entities in the model and read various predefined calculation parameters from their attribute sets; S412: Linking Dynamic Carbon Emission Factor Database: Identifying Emissions through Carbon Emission Factors The FactorReference attribute serves as a data index, allowing for real-time querying and retrieval of the latest carbon emission factor values ​​from the dynamic carbon emission factor database constructed in step S2. S42: Based on the aforementioned calculation parameters, and in conjunction with the carbon emission dynamic factor database and time boundaries, the building carbon emission self-embedded dynamic calculation model is executed, i.e., embedded calculation based on IFC attributes: The calculation engine is triggered within the BIM management platform, directly using the attributes of the IfcCarbonCalculationData entity in the IFC model as input variables to execute the building carbon emission self-embedded dynamic calculation model; the building carbon emission self-embedded dynamic calculation model includes a carbon emission calculation model for the construction phase, a carbon emission calculation model for the operation phase, a carbon emission calculation model for the maintenance phase, a carbon emission calculation model for the demolition phase, a carbon emission calculation model per unit area of ​​the building, and a carbon emission calculation model per unit area per year; Specifically, carbon emissions at each stage of the building are calculated to determine the building's total life-cycle carbon emissions. The calculation engine reads the required attribute values ​​from the associated IfcCarbonCalculationData entity and then executes formula (1), which is the building's total life-cycle carbon emissions calculation model. (1) In the formula: This represents carbon emissions over the entire life cycle; Indicates the first i Carbon emissions at each stage of construction i =1~4 correspond to the construction, operation, maintenance and demolition stages, respectively; This represents the dynamic technology correction factor, which is dynamically updated with technological advancements and policy adjustments. Its calculation formula is as follows: ; This represents the initial correction factor, set according to industry benchmarks. This represents the rate of technological degradation, such as the decrease in carbon emission factors resulting from the increased penetration of renewable energy; t represents the time variable. The stage weight coefficients represent the contribution weights of different stages to total carbon emissions and are determined through expert scoring or principal component analysis (PCA). This represents the nonlinear decay factor, characterizing the exponential decay effect of carbon emissions over time (such as the reduction in carbon emissions due to material aging during maintenance). The time decay rate is represented by regression fitting of historical data; This represents the logarithmic adjustment factor, used to simulate the logarithmic relationship between carbon emissions and time (such as the diminishing marginal carbon emissions effect caused by the extension of building lifespan). Indicates the first i Duration of the construction phase (in years); The calculation results are then directly written to the TotalLifecycleCarbonEmission property.

[0037] In a specific embodiment, the stage weight coefficient The method for obtaining these values ​​is based on principal component analysis (PCA) to obtain the stage weight coefficients. The specific steps include: S100: Obtain carbon emission data for each stage of the entire life cycle of several historical building projects, forming a data matrix with n samples; S101: Perform Z-score normalization on the data matrix; the expression is as follows:

[0038] In the formula: This represents the average carbon emissions in stage j. This represents the standard deviation of carbon emissions in stage j; Indicates the first i The carbon emissions corresponding to stage j for each construction project; Indicates the Z-score after standardization. i The carbon emissions corresponding to stage j for each construction project; S102: The covariance matrix is ​​calculated based on the data matrix after Z-score standardization:

[0039] In the formula: This represents the data matrix after Z-score normalization; express Transpose of; Represent the covariance matrix; S103: Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues. With feature vectors ; S104: Based on eigenvalues The variance contribution rate is:

[0040] In the formula: Represents all eigenvalues The sum; Simultaneously, the eigenvalues ​​are sorted in descending order according to the variance contribution rate to obtain the sequence list, and the first two eigenvalues ​​are selected as principal components; at the same time, the eigenvectors corresponding to the principal components are used as the principal component eigenvectors. S105: Based on the eigenvalues ​​of the principal components and the principal component eigenvectors, the principal component loading vectors are obtained as follows:

[0041] In the formula: V represents the principal component eigenvector matrix; Λ represents the eigenvalue diagonal matrix; Represents the principal component loading vector; S106: Summate and normalize the absolute values ​​of the principal component loadings to obtain the stage weight coefficients. for:

[0042] In the formula: This represents an element in the principal component loading vector.

[0043] For carbon emission calculation during the construction phase, the calculation engine reads the required attribute values ​​from the IfcCarbonCalculationData entity and EmissionFactorReference respectively, and then executes formula (2), which is the carbon emission calculation model for the construction phase: (2) In the formula: This indicates the annual carbon emissions during the building's construction phase; These represent the consumption of labor, materials, and machine shifts for the k-th construction sub-project, respectively. These represent the carbon emission factors of labor, materials, and machinery shifts for the kth construction sub-project, respectively. It represents the elasticity coefficient of labor efficiency, reflecting the nonlinear relationship between labor consumption and carbon emissions (such as the carbon emissions from skilled workers reducing repetitive tasks). This represents the material synergy effect factor, which characterizes the marginal carbon emission increase effect when the amount of material used increases (e.g., the larger the amount of concrete poured, the lower the unit carbon emission due to improved transportation efficiency). This represents the time-sensitive factor of machinery, simulating the non-linear increase in carbon emissions caused by the extension of machinery shift time (such as the decrease in efficiency of continuous machinery operation). Indicates the duration (in days) of a sub-item of work; These represent the carbon emission adjustment factors for labor, materials, and machinery shifts for the k-th construction sub-project, respectively; n represents the total number of all sub-projects in the construction phase that require separate carbon emission calculations; k represents the index. The calculation results are written to StageCarbonEmission [1] Attributes, where index 1 represents the construction phase; During the runtime carbon emission calculation, the calculation engine reads the required attribute values ​​from the IfcCarbonCalculationData entity and EmissionFactorReference respectively, and then executes formula (3). The runtime carbon emission calculation model is as follows: (3) In the formula: This indicates the annual carbon emissions during the building's operational phase. An energy consumption function representing the changes in electricity, fuel, and renewable resources over time; ω represents the dynamic carbon emission factors of electricity, fuel, and renewable resources related to the energy structure; ω represents the renewable energy substitution elasticity, which characterizes the inhibitory effect of the proportion of renewable energy on the carbon emissions of traditional energy. Y represents the maximum substitutable renewable energy capacity (limited by building-integrated photovoltaic area); Y represents the building's operational lifespan. These represent the carbon emission adjustment factors for electricity, fuel, and renewable resources, respectively. Write the numerical integration result into StageCarbonEmission [2] Attributes (index 2 represents the runtime phase); In this embodiment, the carbon emissions generated during the maintenance phase mainly come from the replacement of some materials and construction. The calculation engine reads from the IfcCarbonCalculationData entity and then executes formula (4), which is the carbon emission calculation model for the maintenance phase: (4) In the formula: This indicates the annual carbon emissions during the building maintenance phase; These represent the carbon emission adjustment factors for labor, materials, and machinery shifts for the kth construction sub-project, respectively. Indicates the area of ​​the maintenance zone; k This indicates the influence factor of the maintenance area area. The larger the area, the lower the unit man-made carbon emissions (scale effect). k This represents the logarithmic correction factor for building materials, reflecting the diminishing carbon emission effect when the amount of material used increases (such as emission reduction through bulk purchasing). Indicates the maintenance cycle; This represents the maintenance cycle sensitivity coefficient, where an extended maintenance cycle leads to an increase in mechanical carbon emissions (e.g., due to equipment aging); m represents the total number of all sub-maintenance tasks in the maintenance phase that require separate carbon emission calculations. The calculation results are written to StageCarbonEmission [3] Attributes (index 3 represents the maintenance phase); In this embodiment, the carbon emission sources mainly come from the carbon emissions generated by the human and mechanical processes of demolishing buildings and transporting construction waste. The calculation engine reads from the IfcCarbonCalculationData entity and then executes formula (5), which is the carbon emission calculation model for the demolition stage: (5) In the formula: This indicates the annual carbon emissions during the building demolition phase. Indicates the carbon emission factor of recyclable carbon sources; Indicates the amount of recyclable carbon in a project; Demolition efficiency factor (unit: m) 3-1 This was determined through regression analysis of historical project data; Indicates the demolition area ( When the number of workers increases, the carbon emissions per unit of labor decrease due to the increased efficiency of collaborative work. This represents the material scale correction factor (unitless), which is obtained by fitting a logarithmic relationship (material usage) using material supply chain data. As production increases, unit carbon emissions decrease due to batch processing or transportation optimization. Mechanical time sensitivity factor (unit: days) -1 The energy consumption versus time curve provided by the equipment manufacturer is used to derive the energy consumption versus time curve. Indicates the machine operation time ( When extended, carbon emissions increase exponentially due to equipment aging or decreased efficiency. This represents the recycling technology gain coefficient (unitless), derived from technical reports in the renewable resources industry. represents the carbon emission adjustment coefficients for the k-th sub-item (labor, materials, machinery shifts, and recyclable carbon sources), respectively; p represents the total number of all sub-item demolition tasks that require separate carbon emission calculation during the demolition phase. The calculation results are written to StageCarbonEmission [4] Attributes (index 4 represents the demolition stage); In this embodiment, after completing the full life cycle carbon emission calculation, the carbon emission calculation model per unit area of ​​the building (6) and the annual carbon emission calculation model per unit area (7) are executed: (6) (7) In the formula: The total carbon emissions over the entire life cycle are represented by: S, total building area; γ, building function adjustment coefficient (considering the impact of different building functions on carbon emissions); δ, area adjustment coefficient, used to consider the impact of changes in building area at different stages on carbon emissions; η, area scale effect factor, reflecting the nonlinear impact of building area on unit carbon emissions (when S is small, the scale effect is significant (approaching 0), and unit carbon emissions decrease; when S exceeds the threshold S0, management complexity increases, leading to marginal increases in carbon emissions; typical value: η = 0.2~0.5, derived through regression analysis of historical project data); κ, scale decay coefficient, controlling the rate of scale effect, with units of m. 2μ represents the area logarithmic correction factor, characterizing the long-term impact of changes in building area on carbon emissions. Typical values ​​are μ = 0.1~0.3, and calibration is required based on building function type. S0 represents the baseline area, set with reference to industry standards or project type. C d ε represents carbon emissions per unit area; N represents the building's design life; ε represents the time adjustment factor, used to consider the impact of building life on carbon emissions; ζ represents the stage time adjustment factor, used to consider the impact of different stage time spans on carbon emissions; ν represents the age decay factor, reflecting the nonlinear impact of building life on annual carbon emissions (N approaches 0 as it increases; the correction term 1+ν reflects the increase in maintenance carbon emissions due to equipment aging, with typical values ​​of ν=0.05~0.2 and λ=0.02~0.05 years). 1) λ represents the decay rate; ξ represents the dynamic coefficient of technological renewal, quantifying the long-term inhibitory effect of technological iteration on carbon emissions; Indicates the technology update cycle (e.g., the replacement cycle of renewable energy equipment). =10 years, then ξ=10 / N represents the correction of annual carbon emissions based on the technology update frequency; C m This indicates the carbon emissions per unit of building area per year. Indicates the first i Carbon emissions at each stage of construction i =1~4; Represents the dynamic technical correction coefficient and ; Indicates the initial correction factor; The 't' represents the rate of technological decay; 't' represents the time variable. Indicates the stage weight coefficient; This represents the nonlinear decay factor; Indicates the rate of decay over time; This represents the logarithmic adjustment factor; Indicates the first i The duration of the construction phase; the calculation results are also written to the UnitAreaCarbonEmission property; S43: The calculation results of the building carbon emission self-inherent dynamic calculation model are used as the calculation results for the entire life cycle of building carbon emissions. Simultaneously, after the calculation is completed, the calculation results are directly and automatically written back to the corresponding attribute of the source IfcCarbonCalculationData entity via a pre-built engine. Write stage carbon emissions into StageCarbonEmission; The total carbon emissions throughout the entire life cycle will be included in TotalLifecycleCarbonEmission. Write the carbon emissions per unit area into UnitAreaCarbonEmission; The annual carbon emissions per unit area are recorded in UnitAreaAnnualCarbonEmission; This embodiment also includes S44: Model-driven and dynamic visualization, which is to achieve dynamic control and intuitive display of the model based on the carbon emission results written into the model, including: S441: Model-Driven Optimization: The system presets business rules and automatically drives model changes based on calculation results. For example, when the UnitAreaCarbonEmission of a component exceeds a preset threshold, the system can automatically highlight the component as a warning; if the TotalLifecycleCarbonEmission exceeds the limit, it can trigger automatic adjustment suggestions for key parameters (such as MaterialSynergyFactor) in IfcCarbonCalculationData and start a new round of calculations to verify the optimization effect. S442: Carbon Data Visualization: Utilizing the powerful graphics engine configured in the BIM management platform, the results data (such as StageCarbonEmission) in IfcCarbonCalculationData are mapped onto their associated building components for visualization rendering. For example, the carbon footprint of different components or areas can be intuitively displayed in the 3D model through a color gradient (from green to red), forming a building carbon footprint heatmap, providing decision-makers with the most direct insights; S5: Apply dynamic sensitivity analysis to the calculation results of building carbon emissions throughout their entire life cycle to obtain key parameters affecting building carbon emissions. In this embodiment, the key parameters include, but are not limited to, material consumption, machinery usage, dynamic technical correction coefficients, and stage weighting coefficients. Simultaneously, based on the BIM platform, set the dynamic variation range of each key parameter, and based on this dynamic variation range combined with the self-inherent dynamic calculation model for building carbon emissions, simulate and obtain the simulation calculation results of the building carbon emissions throughout their entire life cycle corresponding to different values ​​of the key parameters. Obtain the sensitivity index by comparing the degree of impact of the numerical changes of each key parameter on the total carbon emissions throughout the building's entire life cycle. Based on the sensitivity index, obtain the key parameters corresponding to the sensitivity index that meet the preset threshold, as the sensitivity parameters with the greatest impact on carbon emissions. Specifically, this includes: S51: Based on the carbon emission calculation results written into the IfcCarbonCalculationData entity in stage S4, extract the key parameters that have a significant impact on carbon emissions, including but not limited to Material Consumption, Machinery Consumption, Dynamic TechCorrection Factor, and StageWeightCoefficient; S52: Set the dynamic variation range of each key parameter (e.g., ±10%, ±20%) in the BIM management platform, and based on IfcCarbon... The formula structure and parameter relationships stored in onCalculationData are used to automatically perform multi-scenario simulation calculations; S53: By comparing the impact of changes in each parameter on the total lifecycle carbon emission, a sensitivity index is calculated, and three sensitivity levels (high, medium, and low) are assigned to identify the key parameters with the greatest impact on carbon emissions; S54: For high-sensitivity parameters, targeted emission reduction measures are formulated based on building type and stage characteristics, such as replacing high-carbon materials, optimizing energy structure, and adjusting maintenance cycles, and these measures are mapped to the corresponding IfcCarbonCalculationData parameter attributes to provide input for subsequent optimization and verification; S6: Based on empirical values ​​and sensitivity parameters, formulate emission reduction measures for the entity attribute sets of entities used to update carbon calculation data entities at each building stage; the emission reduction measures include, but are not limited to, replacing high-carbon building materials, optimizing energy structure, and adjusting maintenance cycles; specifically, based on the key parameters and optimization schemes obtained by sensitivity analysis, directly modify the attribute values ​​of the corresponding IfcCarbonCalculationData entities in the current extended BIM model, for example: updating MaterialConsumption (replacing materials), adjusting DynamicTechCorrectionFactor (adopting new technologies), etc. S7: Apply the emission reduction measures to the extended BIM model and repeat steps S4 to S6 to recalculate carbon emissions and verify the optimization effect, ultimately forming a closed loop for carbon emission measurement and optimization, thereby achieving BIM evaluation and management of building carbon emissions throughout their entire lifecycle. Since all data is in the model, the calculation engine will immediately recalculate based on the updated model data to obtain the optimized carbon emission results, and then write them back to the model. By comparing the result attributes in the old and new versions of IfcCarbonCalculationData in the model, the actual effect of the emission reduction measures can be intuitively evaluated, forming a complete digital closed loop of "analysis-optimization-model update-calculation verification".

[0044] This embodiment uses IoT sensors to collect basic data at each stage of the building's entire lifecycle in real time; establishes a dynamic carbon emission factor database and compares and verifies it with international standards; expands the physical structure of building components based on IFC standards to construct an extended BIM model embedding carbon monitoring sensors and carbon data attributes; integrates carbon emission factors based on the extended BIM model, and achieves accurate calculation of carbon emissions at each stage through a self-inherent dynamic calculation model for building carbon emissions; applies a multi-dimensional quantitative indicator system for unified measurement; and identifies key parameters and formulates emission reduction measures through dynamic sensitivity analysis, forming a closed-loop management system of "analysis-optimization-verification". This invention solves the problems of lack of dynamism in carbon emission factors, lack of full-stage automated integration in the calculation process, and lack of closed-loop optimization mechanisms in existing technologies, significantly improving the accuracy, real-time performance, and optimization effect of building carbon emission calculation.

[0045] In this embodiment, a green certified office building is used as an example to conduct carbon emission calculation and assessment as follows: I. Basic Project Information This case study selects a green-certified office building as the research object. It was designed and constructed in 2024, with a designed reasonable service life (N) of 50 years and a building area (S) of 10,000 m². 2 The entire life cycle of a building is divided into four stages: construction, operation, maintenance, and demolition. Data such as material transportation and machinery energy consumption during the construction stage, air conditioning and lighting energy consumption during the operation stage, and material replacement frequency during the maintenance stage are monitored in real time using IoT sensors. Spatial boundaries: building entity, functional systems, and directly related materials and energy; temporal boundaries: the entire life cycle is divided into construction (2 years), operation (50 years), maintenance (every 5 years), and demolition (1 year).

[0046] Key parameter assumptions: (1) Construction phase: 50,000 kg of concrete, 20,000 kg of steel, and 500 machine shifts; (2) Operation phase: 600,000 kWh of electricity consumption per year, of which photovoltaic power generation accounts for 30% ( =180000kWh / year); (3) Maintenance stage: Replace the external wall insulation material every 5 years, each time consuming 5000kg of material; (4) Demolition stage: 15,000kg of recyclable steel, demolition machinery operation time 30 days.

[0047] II. Establishing a carbon emission factor database Referring to the ISO 14044 standard and combining it with China's "Standard for Calculation of Carbon Emissions from Buildings" (GB / T51366-2019), the key carbon emission factors are obtained, as shown in Table 3 below: Table 3. Carbon Emission Factor Values

[0048] Key dynamic parameter descriptions: 1. Electricity carbon emission factor: F dl (t)=0.8 0.005 t kg CO2eq / kWh (t = time, year), the dynamic logic is that the carbon emission factor decreases by 0.005 kg CO2eq / kWh each year due to the clean power structure (renewable energy penetration rate increases by 1.5%). 2. Calculation basis for the emission reduction factor of recyclable steel: The carbon emission factor of new steel is 1.8 kg CO2eq / kg, the recycling process reduces emissions by 70% (1.8 × 0.7 = 1.26 kg CO2eq / kg), and the net emission reduction after deducting the energy consumption of recycling is -0.3 kg CO2eq / kg.

[0049] Precautions: 1. Simplified processing of machine shifts: For accurate calculations, it is necessary to use itemized fuel consumption (e.g., diesel carbon emission factor of 3.0 kg CO2eq / L) to avoid errors caused by simplified values. 2. Dynamic factor calibration: Time-sensitive parameters (e.g., F) dl (t) This needs to be updated regularly in conjunction with policy documents or energy transition goals. 3. International standard compatibility: If the project needs to comply with the ISO14044 standard, it is recommended to use localized data from international databases (such as Ecoinvent).

[0050] III. Carbon emission calculation process: 1. Carbon emission calculation during the construction phase (C jz) The parameter settings are shown in Table 4: Table 4. Carbon emission parameter settings during the construction phase

[0051] Adjustment factor (μ) k ν k ξ k : 1.0 (No adjustments) According to formula (2): ; Substitute the data: (1) Man-made carbon emissions: (2000 man-days × 0.1 kg CO2 / man-day × 1.0) 1 0.1 =200 0.9 ≈117.5 kg CO2 eq; (2) Carbon emissions from materials (taking concrete as an example): (50000kg × 0.5kg CO2 / kg × 1.0) × (1 0.015ln(50000))=25,000×(1 0.015×10.82)≈25000×0.838=20950kgCO2eq; (3) Carbon emissions from machinery: (500 shifts × 1.0 kg CO2 / shift × 1.0) × e 0.03×30 =500×e 0.9 ≈500 × 2.46 = 1230 kg CO2 eq; (4) Total carbon emissions during the construction phase: C jz =117.5+20,950+1,230=22297.5kgCO2eq; 2. Carbon emission calculation during operation (C yx) The parameter settings are shown in Table 5: Table 5. Carbon emission parameter settings during operation:

[0052] Adjustment coefficients (η(t), θ(t), ι(t): 1.0 (no adjustment) According to formula (3): ; Substitute the data (integrated over 10 years): (1) 0-10 years: Average annual power consumption: 600,000 × e 0.01×5 ≈600000×0.951=570600kWh (taking t=5 years is based on the numerical integration approximation of the midpoint rule:) ); Carbon emission factor for electricity: F dl (5) = 0.8 0.005 × 5 = 0.775 kg CO2 eq / kWh; Photovoltaic substitution volume: X zs (5) = 180000 (5 / 50) = 18000 kWh; Photovoltaic power generation: 180,000 kWh (accounting for 31.5%) Inhibitory factors: ; Carbon emissions from traditional energy sources: 570600×0.775+1000×2.5×0.881≈444417.5kgCO2eq / year; Photovoltaic offsetting amount: 18000 × 0.02 = 360 kg CO2eq / year; 10-year net emissions: (444417.5) 360) × 10 = 4440575 kg CO2 eq; (2) 10-20 years: Average annual power consumption: 600,000 × e 0.01×15 ≈600000 × 0.861 = 516600 kWh; The proportion of photovoltaic power has increased to 35%, and the calculation logic is the same as above.

[0053] Net emissions over 10 years: (516600×0.725+1000×2.5×0.652-1080)×10=3750850kgCO2eq; (3) Total carbon emissions over 50 years of operation: C yx =4440575+3750850+3147825+2624450+2170275≈16133975kgCO2eq; 3. Carbon emissions during the maintenance phase (C wh ) The parameter settings are shown in Table 6: Table 6. Carbon emission parameter settings during maintenance phase

[0054] Adjustment factor (κ) k , λ k π k : 1.0 (No adjustments) According to formula (4): ; Substitute the data: (1) Carbon emissions per maintenance session (assuming a maintenance task k=1): Artificial items: kgCO2eq; Material item: 5000 × 0.5 × 1.0 × (1 0.02×ln(5000))=2,500×(1 0.02×8.517)≈2500;×0.83=2075kgCO2eq; Mechanical item: 50 × 1.0 × 1.0 × (1 + 0.03 × 5) = 50 × 1.15 = 57.5 kg CO2 eq; Total carbon emissions per maintenance cycle: 0.77 + 2075 + 57.5 = 2133.27 kg CO2 eq; (2) Total maintenance carbon emissions over 50 years: C wh =2133.27×10=21332.7kgCO2eq; 4. Carbon emissions during the demolition phase (C cc ) The parameter settings are shown in Table 7: Table 7. Carbon emission parameter settings during the demolition phase

[0055] Adjustment coefficients (ρk, σk, τk, ωk): 1.0 (no adjustment) According to formula (5): ; Substitute the data: (1) Labor item (kgCO2eq): ; (2) Materials: 2000×0.5×1.0×(1 0.015×ln(2000))=1000×(1 0.015 × 7.6) ≈ 886 kg CO2 eq; (3) Mechanical items: 100×1.0×1.0×e 0.03×30 =100×e 0.9 ≈246kgCO2eq; (4) Recovery offset items: 1000×( 0.3)×1.0×(1+0.1×0.6)= 300 × 1.06 = 318 kg CO2 eq; (5) Total carbon emissions from demolition: C cc =0.73+886+246-318=814.73kgCO2eq; 5. Total carbon emissions throughout the building's life cycle (C z ) The parameter settings are shown in Table 8: Table 8. Parameter settings for carbon emissions throughout the building's life cycle

[0056] In this embodiment, the weights of the calculation stage are... β i Principal component analysis (PCA) was chosen, and the PCA analysis steps are as follows: I. Data Preparation Collect carbon emission data for each stage of the entire life cycle of multiple building projects to form a data matrix (n is the sample size (n≥30 is recommended to reduce random error).

[0057] II. Data Standardization Z-score standardization: Standardizes the data in each column (stage) to eliminate differences in units; ; Where: μ j σ represents the mean carbon emissions in stage j; j This represents the standard deviation of carbon emissions in stage j; III. Calculating the covariance matrix Covariance matrix formula: Where X represents the standardized data matrix; IV. Eigenvalue and Eigenvector Decomposition Solving for eigenvalues ​​and eigenvectors: The eigenvalues ​​λ are obtained through the eigenvalue decomposition of the covariance matrix. j With feature vector v j ; V. Determining the number of principal components Variance contribution rate: ; Retain principal components: Select the first two principal components to cover most of the data information.

[0058] VI. Calculation of stage weights β i (1) Principal component loadings: (V is the eigenvector matrix, and Λ is the eigenvalue diagonal matrix) (2) Weight allocation: Summing and normalizing the absolute values ​​of the loads: ; (3) Normalized weights: According to formula (1): ; Phased carbon emission correction calculation: (1) Construction phase (i=1) C1′=22297.5×0.95×0.12×(1+0.1 e 0.02×2 )×(1+0.01 ln(2))=22297.5×0.95×0.12×1.096×1.007≈2805.44kgCO2eq; (3) Operation phase (i=2) C2′=16133975×0.90×0.76×(1+0.2 e 0.01×50)×(1+0.005 ln(50))=16133975×0.90×0.76×1.121×1.020≈12618370.2kgCO2eq; (4) Maintenance phase (i=3) C3′=21332.7×0.98×0.10×(1+0.15 e 0.03×50 )×(1+0.02 ln(50))=21332.7×0.98×0.10×1.033×1.078≈2328.04kgCO2eq; (5) Demolition stage (i=4) C4′=814.73×1.00×0.02×(1+0.05 e 0.05×1 )×(1+0.001 ln(1))=814.73×1.00×0.02×1.048×1≈17.08kgCO2eq; (6) Total carbon emissions over the entire life cycle C z= C1′+C 2+ ′C3′+C4′=2805.44+12618370.2+2328.04+17.08=12623520.8kgCO2eq; 6. Carbon emissions per unit area (C d ) The parameter settings are shown in Table 9: Table 9. Parameter settings for carbon emissions per unit area

[0059] According to formula (6): ; Substitute the data: Cd=(12623520.8 / 10000)×1.0×1.0×[1+0.3×(1-e -0.001×10000 )]×(1+0.2×ln(10000 / 5000)=(12623520.8 / 10000)×1.0×1.0×1.30×1.139≈1869.16kgCO2eq; 7. Annual carbon emissions per unit area (C m ) The parameter settings are shown in Table 10: Table 10. Parameter settings for carbon emissions per unit area:

[0060] According to formula (7): ; Substitute the data: ; 8. Summary: Based on the detailed calculations described above, the following results were obtained in this embodiment: 1. Total carbon emissions throughout the building's life cycle (C z ): 12623520.8 kgCO2eq 2. Carbon emissions per unit area (C d ): 1869.16 kgCOeq / m² 3. Annual carbon emissions per unit area (C m ): 28.44 kg COeq / m² These results reflect the carbon emissions throughout the entire lifecycle of a building, from construction to demolition, providing data support for subsequent optimization and decision-making. Sensitivity analysis is a method used to assess the impact of changes in key parameters on the overall outcome of a project. Through sensitivity analysis, parameters with the greatest impact on carbon emissions can be identified, and targeted optimization measures can be developed. The following is a sensitivity analysis of a small residential building project based on the above assumptions. Based on the calculation process in the case study, key input parameters for the operation phase are selected for sensitivity analysis: 1. Selection of main input parameters: Annual electricity consumption (X) dl (0) and the proportion of photovoltaic power generation (X) zs,max ); 2. Sensitivity analysis method: A one-way sensitivity analysis was used, where only one parameter was changed at a time while keeping other parameters constant, to observe its effect on total carbon emissions (C). z The impact of ) 3. Analysis process and results: (1) Annual electricity consumption (X) dl (0) Original value: 600,000 kWh 20% reduction: 480,000 kWh Carbon emissions during the new operating phase (C yx ): 3552425+2998300+2520075+2080700+1735575=12889075kgCO2eq; New total carbon emissions (C z ): 10085686.64 kg CO2eq Conclusion: Annual electricity consumption has a very significant impact on total carbon emissions. A 20% reduction in annual electricity consumption results in a reduction of 2,537,834.16 kg CO2eq in total carbon emissions.

[0061] (2) Proportion of photovoltaic power generation (X) zs,max ) Original value: 180,000 kWh / year Increase by 20%: 216,000 kWh / year Carbon emissions during the new operating phase (C yx ): 4439855+3748690+3144225+2619410+2163795=16115975kgCO2eq; New total carbon emissions (C z ): 12609443kgCO2eq Conclusion: The proportion of photovoltaic power generation has a significant impact on total carbon emissions. A 20% increase in the proportion of photovoltaic power generation reduces total carbon emissions by 14,077 kg CO2eq.

[0062] 4. Sensitivity analysis results: The annual electricity consumption during the operation phase has the most significant impact on total carbon emissions, with a change rate as high as 8.03%; therefore, optimizing the energy efficiency of buildings and reducing energy consumption are key measures to reduce carbon emissions.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A BIM-based evaluation and management method for the entire lifecycle of building carbon emissions, characterized in that, Specifically, the following steps are included: S1: Investigate relevant data on building projects throughout the entire building lifecycle and define the spatial and temporal boundaries for carbon emission calculations; The spatial boundary is used to characterize the physical structural components of the building and the configuration system that meets the building's usage; the temporal boundary is used to characterize the time span of each building stage within the entire life cycle, and the building stage includes the construction stage, operation stage, maintenance stage, and demolition stage. S2: Define a carbon emission factor database; the carbon emission factors include, but are not limited to, configuration system energy consumption, human factors, building materials, and machinery shift factors; at the same time, based on empirical values ​​and the actual application results of building projects, adjust the carbon emission factor database to obtain a dynamic carbon emission factor database. S3: Obtain the original IFC dictionary file, and based on the IFC standard, add the building's carbon monitoring sensor space to the original IFC dictionary file according to the building's spatial boundaries; add the pre-set structural elements of different types of carbon monitoring sensor entities to the carbon monitoring sensor space to obtain the physical element system of the building carbon monitoring sensor; add attribute sets to the types of carbon monitoring sensor entities in the physical element system; the attribute set addition is to add sensor data attributes corresponding to the carbon monitoring sensor type to the physical element system, obtain the carbon monitoring sensor type IFC dictionary file, and then form the building carbon monitoring sensor type IFC file based on the carbon monitoring sensor type IFC dictionary file; at the same time, based on the BIM management platform, define carbon calculation data entities for the building carbon monitoring sensor type IFC file and configure the entity attribute set of the carbon calculation data entities to obtain an extended BIM model integrating carbon monitoring sensor entities and carbon calculation data entities; S4: Based on the extended BIM model, construct a self-inherent dynamic calculation model for building carbon emissions according to the carbon emission dynamic factor database and time boundary; the self-inherent dynamic calculation model for building carbon emissions includes a carbon emission calculation model for the construction phase, a carbon emission calculation model for the operation phase, a carbon emission calculation model for the maintenance phase, a carbon emission calculation model for the demolition phase, a carbon emission calculation model for building unit area, and a carbon emission calculation model for annual carbon emissions per unit area. The calculation results of the self-inherent dynamic calculation model of building carbon emissions are used as the calculation results of building carbon emissions throughout the entire life cycle. S5: Perform dynamic sensitivity analysis on the calculation results of building carbon emissions throughout the entire life cycle to obtain key parameters affecting building carbon emissions; the key parameters include, but are not limited to, material consumption, machinery consumption, dynamic technology correction coefficient, and stage weight coefficient. Simultaneously, based on the BIM platform, the dynamic range of each key parameter is set, and based on the dynamic range of the change and combined with the self-inherent dynamic calculation model of building carbon emissions, the simulation calculation results of the building carbon emissions throughout the entire life cycle corresponding to the key parameters with different values ​​are simulated and obtained. The sensitivity index is obtained by comparing the degree of impact of the numerical change of each key parameter on the total carbon emissions throughout the building's life cycle. The key parameters whose sensitivity index exceeds the preset threshold are identified as the most sensitive parameters with the greatest impact on carbon emissions. S6: Based on empirical values ​​and sensitivity parameters, formulate emission reduction measures for each building stage to update the entity attribute set of carbon calculation data entities; the emission reduction measures include, but are not limited to, replacing high-carbon building materials, optimizing energy structure, and adjusting maintenance cycles; S7: Apply the emission reduction measures to the extended BIM model, and repeat steps S4 to S6 to recalculate carbon emissions and verify the optimization effect, ultimately forming a closed loop of carbon emission measurement and optimization, thereby realizing BIM evaluation and management of building carbon emissions throughout the entire life cycle.

2. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 1, characterized in that, S4 specifically includes the following steps: S41: Load the extended BIM model into the preset BIM management platform; By identifying the carbon calculation data entities in the extended BIM model and reading the calculation parameters in their respective entity attribute sets; and the calculation parameters include, but are not limited to, carbon emission factor association identifiers, labor consumption, material consumption, machine shift consumption, dynamic technology correction coefficients, and stage weight coefficients; S42: Based on the calculation parameters, execute the self-inherent dynamic calculation model of building carbon emissions according to the carbon emission dynamic factor database and the time boundary; the self-inherent dynamic calculation model of building carbon emissions includes a carbon emission calculation model for the construction stage, a carbon emission calculation model for the operation stage, a carbon emission calculation model for the maintenance stage, a carbon emission calculation model for the demolition stage, a carbon emission calculation model for building unit area, and a carbon emission calculation model for annual carbon emissions per unit area. S43: Use the calculation results of the self-inherent dynamic calculation model of building carbon emissions as the calculation results of building carbon emissions throughout the entire life cycle.

3. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 2, characterized in that, The carbon emission calculation model for the construction phase described in S42 is as follows: In the formula: This indicates the annual carbon emissions during the building's construction phase; These represent the consumption of labor, materials, and machine shifts for the k-th construction sub-project, respectively. These represent the carbon emission factors of labor, materials, and machinery shifts for the kth construction sub-project, respectively. This represents the elasticity coefficient of human efficiency; Indicates the material synergistic effect factor; Indicates the mechanical time-sensitive factor; Indicates the duration of a sub-item of work; represents the carbon emission adjustment coefficients for labor, materials, and machinery shifts for the k-th construction sub-project, respectively; n represents the total number of all sub-projects in the construction phase that require separate carbon emission calculations.

4. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 3, characterized in that, The carbon emission calculation model for the operation phase described in S42 is as follows: In the formula: This indicates the annual carbon emissions during the building's operational phase. An energy consumption function representing the changes in electricity, fuel, and renewable resources over time; ω represents the dynamic carbon emission factor related to electricity, fuel, and renewable resources in the energy structure; ω represents the elasticity of renewable energy substitution. Y represents the maximum amount of renewable energy that can be substituted; Y represents the building's service life. These represent the carbon emission adjustment factors for electricity, fuel, and renewable resources, respectively.

5. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 4, characterized in that, The carbon emission calculation model for the maintenance phase described in S42 is as follows: In the formula: This indicates the annual carbon emissions during the building maintenance phase; These represent the carbon emission adjustment factors for labor, materials, and machinery shifts for the kth construction sub-project, respectively. Indicates the area of ​​the maintenance zone; k Indicates the factors affecting the area of ​​the maintenance zone; k This represents the logarithmic correction factor for building materials; Indicates the maintenance cycle; represents the maintenance cycle sensitivity coefficient; m represents the total number of all sub-maintenance tasks in the maintenance phase that require separate calculation of carbon emissions.

6. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 5, characterized in that, The carbon emission calculation model for the demolition phase described in S42 is as follows: In the formula: This indicates the annual carbon emissions during the building demolition phase. Indicates the carbon emission factor of recyclable carbon sources; Indicates the amount of recyclable carbon engineering work; Indicates the demolition efficiency factor; Indicates the area to be demolished; Indicates the material size correction factor; Indicates the mechanical time-sensitive factor; Indicates the machine's operating time; Indicates the gain coefficient of the recycling technology; represents the carbon emission adjustment coefficients for the k-th sub-item (labor, materials, machinery shifts, and recyclable carbon sources), respectively; p represents the total number of all sub-item demolition tasks that require separate carbon emission calculation during the demolition phase.

7. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 6, characterized in that, The carbon emission calculation models per unit area and per unit area annual carbon emission calculation models described in S42 are as follows: In the formula: Represents total life-cycle carbon emissions; S represents total building area; γ represents building function adjustment coefficient; δ represents area adjustment coefficient; η represents area scale effect factor; κ represents scale decay coefficient; μ represents area logarithmic correction factor; S0 represents baseline area; C d Indicates carbon emissions per unit area; N represents the building's design life; ε represents the time adjustment factor. ζ represents the stage time adjustment coefficient; ν represents the annual decay factor; λ represents the decay rate; ξ represents the technology update dynamic coefficient; Indicates the technology update cycle; C m This indicates the carbon emissions per unit of building area per year. Indicates the first i Carbon emissions at each stage of construction i =1~4; Represents the dynamic technical correction coefficient and ; Indicates the initial correction factor; The 't' represents the rate of technological decay; 't' represents the time variable. Indicates the stage weight coefficient; This represents the nonlinear decay factor; Indicates the rate of decay over time; This represents the logarithmic adjustment factor; Indicates the first i The duration of the construction phase.

8. The BIM evaluation and management method for the entire life cycle of building carbon emissions according to claim 7, characterized in that, The stage weight coefficient The method for obtaining these values ​​is based on principal component analysis (PCA) to obtain the stage weight coefficients. The specific steps include: S100: Obtain carbon emission data for each stage of the entire life cycle of several historical building projects, forming a data matrix with n samples; S101: Perform Z-score normalization on the data matrix; the expression is as follows: In the formula: This represents the average carbon emissions in stage j. This represents the standard deviation of carbon emissions in stage j; Indicates the first i The carbon emissions corresponding to stage j for each construction project; Indicates the Z-score after standardization. i The carbon emissions corresponding to stage j for each construction project; S102: The covariance matrix is ​​calculated based on the data matrix after Z-score standardization: In the formula: This represents the data matrix after Z-score normalization; express transpose; Represent the covariance matrix; S103: Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues. With feature vectors ; S104: Based on eigenvalues The variance contribution rate is: In the formula: Represents all eigenvalues The sum; Simultaneously, the eigenvalues ​​are sorted in descending order according to the variance contribution rate to obtain the sequence list, and the first two eigenvalues ​​are selected as principal components; at the same time, the eigenvectors corresponding to the principal components are used as the principal component eigenvectors. S105: Based on the eigenvalues ​​of the principal components and the principal component eigenvectors, the principal component loading vectors are obtained as follows: In the formula: V represents the principal component eigenvector matrix; Λ represents the eigenvalue diagonal matrix; Represents the principal component loading vector; S106: Summate and normalize the absolute values ​​of the principal component loadings to obtain the stage weight coefficients. for: In the formula: This represents an element in the principal component loading vector.

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