Multi-dimensional building construction carbon quota calculation method, device, equipment and medium

Abstract

The application relates to the technical field of carbon quota calculation, and discloses a multi-dimensional building construction carbon quota calculation method, device, equipment and medium, which comprises the following steps: decomposing a single construction project into a plurality of construction sub-projects, extracting key construction factors of the construction sub-projects that affect carbon emission, and dividing the key construction factors into fixed factors and adjustable factors; combining the influence law of the key construction factors on carbon emission, and constructing a carbon quota calculation model corresponding to each construction sub-project; fixing the parameters of all the fixed factors, changing the parameters of the adjustable factors, and calculating the carbon quota of each construction sub-project one by one through the carbon quota calculation model; accumulating the carbon quotas of all the construction sub-projects to obtain the total carbon quota of the single construction project; and optimizing the parameters of the adjustable factors to obtain the optimal carbon quota calculation result of the single construction project. The application solves the technical problems in the prior art, such as coarse calculation granularity, non-type parameters, lack of actual measurement and quantitative modeling, and inability to rely on the approved quota limit to optimize parameters.

Description

Technical Field

[0001] This application relates to the field of carbon quota calculation technology in building construction scenarios, specifically a multi-dimensional method, device, equipment and medium for calculating carbon quotas in building construction. Background Technology

[0002] Currently, the carbon quota allocation calculation in the construction industry generally adopts quota accounting models such as the output value coefficient method, the building area quota method, and the historical emission base method. These models directly determine project carbon quotas based on fixed industry benchmark coefficients, which has many technical drawbacks in practical application and results in poor universality of the calculation system. Specifically, existing schemes have a coarse division of accounting units, lack a hierarchical breakdown of project processes, and fail to classify and manage various carbon emission impact parameters according to construction constraints. Fixed and adjustable parameters are mixed, which is not conducive to targeted quota optimization. Furthermore, traditional quota coefficients are based on experience and are difficult to combine with actual project measurement data to build a quantitative model of parameters and carbon emissions, leading to significant discrepancies between the calculation results and actual on-site conditions. In addition, conventional calculations only calculate quota values ​​in one direction, without considering the approved quota upper limit for the project to optimize construction parameters. This easily leads to calculated quotas exceeding the approved limit, making it difficult to output compliant and optimal quota calculation data. Summary of the Invention

[0003] The purpose of this application is to provide a multi-dimensional method, device, equipment and medium for calculating carbon quotas in building construction, so as to solve the technical problems in the prior art, such as coarse calculation granularity, lack of parameter classification, lack of actual measurement and quantitative modeling, and inability to optimize parameters based on approved quota limits.

[0004] To achieve the above objectives, this application provides a multi-dimensional method for calculating carbon emission allowances in building construction, including: The single construction project is broken down into several construction sub-projects. The key construction factors affecting carbon emissions of each construction sub-project are extracted. Based on the preset construction implementation constraints, the key construction factors are divided into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan. Based on the impact of key construction factors on carbon emissions, a carbon quota calculation model is constructed for each construction sub-project. The carbon quota calculation model uses the key construction factors of the construction sub-project as input parameters and outputs the corresponding carbon quota of the construction sub-project. With all fixed factors kept constant, the parameters of adjustable factors are changed, and the carbon allowances for each construction sub-project are calculated one by one using the carbon allowance calculation model. The total carbon allowance for a single construction project is obtained by summing the carbon allowances of all construction sub-projects. The parameters of the adjustable factors are optimized using the maximum approved carbon allowance for a single construction project as a constraint, and the optimal carbon allowance calculation result for a single construction project is obtained.

[0005] As a preferred option, during the process of optimizing the parameters of the adjustable factors, the construction and renovation costs generated by parameter adjustments and the market revenue corresponding to the surplus carbon quotas are statistically analyzed simultaneously. The optimal combination of adjustable factor parameters is determined by maximizing the net revenue of a single construction project after deducting the construction and renovation costs.

[0006] As a preferred approach, the key construction factors of the corresponding construction sub-projects are updated using the optimal combination of adjustable factor parameters. All the updated key construction factors are then substituted into the carbon quota calculation model to recalculate the carbon quotas of each construction sub-project and the total carbon quota of the individual construction project. After the second verification is completed, the final carbon quota calculation data is output.

[0007] As a preferred approach, the optimal carbon allowance calculation results of all individual construction projects are summarized, and the actual carbon allowance consumption status of each individual construction project is monitored according to a preset fixed period. The carbon allowance surplus status and the carbon allowance deficit status are distinguished, and a dynamic carbon allowance ledger for the entire project is established.

[0008] As a preferred option, retrieve the dynamic ledger of carbon quotas for all projects in the region, calculate the input cost required for projects with shortfalls to make up their quotas based on their own key construction factors, and the quota revenue after making up their quotas; when the required input cost is greater than the quota revenue, allocate the surplus carbon quotas of surplus projects to supplement projects with shortfalls; when the required input cost is less than or equal to the quota revenue, projects with shortfalls adjust their own key construction factors to make up their quotas themselves.

[0009] Preferably, the construction of the carbon quota calculation model corresponding to each construction sub-project includes: Collect measured parameters of key construction factors and corresponding measured carbon emission data for construction sub-projects, and fit the variation patterns between key construction factors and carbon emissions; determine the fixed conversion relationship between carbon emissions and carbon quotas based on the current project carbon quota accounting specifications; and integrate the variation patterns and fixed conversion relationships to generate a carbon quota calculation model.

[0010] As a preferred approach, the first-order and second-order variation characteristics of the influence of adjustable factors on carbon emissions are extracted; the control priority of each adjustable factor is determined based on the first-order variation characteristics; the parameter adjustment critical value of the adjustable factor is limited based on the second-order variation characteristics; and the actual adjustable parameter range of the adjustable factor is limited by combining the control priority and the parameter adjustment critical value.

[0011] To achieve the above objectives, this application also provides a multi-dimensional building construction carbon quota calculation device, which applies the multi-dimensional building construction carbon quota calculation method described above, including: The construction analysis module is used to break down a single construction project into several construction sub-projects, extract the key construction factors that affect carbon emissions from each construction sub-project, and classify the key construction factors into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan based on preset construction implementation constraints. The model building module is used to combine the impact of various key construction factors on carbon emissions to build a carbon quota calculation model for each construction sub-project. The carbon quota calculation model takes the key construction factors of the construction sub-project as input parameters and outputs the corresponding carbon quota of the construction sub-project. The calculation and optimization module is used to keep all fixed factors unchanged, change the parameters of adjustable factors, and calculate the carbon quota of each construction sub-project one by one through the carbon quota calculation model. The total carbon quota of a single construction project is obtained by summing the carbon quotas of all construction sub-projects. The parameters of the adjustable factors are optimized with the maximum approved carbon quota of a single construction project as a constraint to obtain the optimal carbon quota calculation result of a single construction project.

[0012] To achieve the above objectives, this application also provides a multi-dimensional carbon quota calculation device for building construction, including at least one processor, at least one memory, and a data bus; The processor and the memory communicate with each other via the data bus; The memory stores program instructions that can be executed by the processor, which calls the program instructions to execute the multi-dimensional building construction carbon quota calculation method as described above.

[0013] To achieve the above objectives, this application also provides a medium on which a computer program is stored, which, when executed by a processor, implements the multi-dimensional carbon quota calculation method for building construction as described above.

[0014] Beneficial Effects: The multi-dimensional carbon emission calculation method, device, equipment, and medium for building construction proposed in this application overcome the shortcomings of existing methods such as extensive fixed-quota calculation, fixed quota ratios, and passive external purchase of carbon emission allowances for shortfalls by combining multiple layers of coordination, including detailed calculation of key construction factors, selection of the best economic option from multiple schemes, secondary verification of calculation results, establishment of a dynamic quota ledger for the entire enterprise, and differentiated allocation of internal carbon emission allowances based on cost-benefit differentiation. It can accurately calculate the carbon emissions of individual projects, optimize processes from the source of construction to reduce the probability of excessive emissions, and rely on the ledger to coordinate the surplus and shortage of quotas for the entire enterprise, thus revitalizing idle internal quota resources. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application 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 only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the multi-dimensional carbon quota calculation method for building construction provided in this application embodiment; Figure 2The structural block diagram of the multi-dimensional building construction carbon quota calculation device provided in this embodiment is shown in the figure. In the figure: 10, construction analysis module; 20, model building module; 30, calculation and optimization module.

[0017] The implementation, functional features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0019] In this document, the term "comprising" is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0020] Carbon quotas refer to the amount of carbon dioxide that regulatory authorities approve and allow companies to legally emit within a certain period. For construction companies, they are a core compliance resource for annual carbon emission compliance and carbon asset management. For individual construction projects, they serve as the basis for quantifying and controlling construction carbon emissions and determining the carbon quotas used for the project. Currently, carbon quotas in the construction industry are generally calculated using fixed quotas based on output value and building area, which is the mainstream solution in the industry. This model uses the complete individual construction project as a unified accounting unit, directly determining the overall quota based on officially published fixed conversion factors. The allocation process is simple and can meet the basic needs of companies to quickly complete the internal allocation of carbon quotas.

[0021] However, the above calculation model has significant drawbacks: First, the calculation unit is not broken down into individual construction sub-projects, resulting in coarse-grained calculations that make it difficult to accurately distinguish the carbon emission contributions of different construction stages. Second, various carbon emission influencing factors are calculated together without distinguishing between fixed parameters that cannot be changed and adjustable parameters that can be adjusted according to construction constraints, making it difficult to optimize all parameters simultaneously. Third, the quota coefficients rely on industry experience for calibration, lacking support from actual project conditions and emission data, making it impossible to build a quantitative calculation model for construction factors and carbon quotas, resulting in high deviations between the calculated values ​​and actual emissions on site. Fourth, the calculation only calculates the quota in a forward direction, without using the maximum carbon quota approved for the project as a constraint for reverse optimization, making it easy for the calculation results to exceed the approved limit and failing to output the optimal compliant quota.

[0022] To overcome the aforementioned shortcomings, this embodiment discloses a carbon quota calculation technology based on multi-dimensional factor-level decomposition of building construction items. In summary, this embodiment constructs a multi-dimensional system by decomposing projects and combining them with binary factor classification. Based on this multi-dimensional system, it models according to measured patterns and optimizes responses to building construction characteristics within quota constraints, thereby achieving calculations that closely match on-site working conditions and significantly improve optimization iteration efficiency. This solves the technical problems of existing technologies, such as coarse calculation granularity, lack of parameter classification, lack of measured quantitative modeling, and inability to optimize parameters based on approved quota limits.

[0023] Reference Figure 1 , Figure 1 The flowchart of the multi-dimensional carbon quota calculation method for building construction provided in this embodiment is shown.

[0024] like Figure 1 As shown, in a first aspect, this embodiment discloses a multi-dimensional method for calculating carbon allowances in building construction, including: S10: Break down a single construction project into several sub-projects, extract the key construction factors that affect carbon emissions from each sub-project, and based on the preset construction implementation constraints, divide the key construction factors into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan.

[0025] In summary, S10 of this embodiment completes the splitting of accounting units and factor classification. In specific applications of this embodiment, S10 can be implemented in conjunction with existing technologies. For example, the existing technologies can, but are not limited to, using an eight-dimensional relational knowledge graph to break down and cut individual construction projects layer by layer according to construction procedures and work blocks, thereby obtaining construction sub-projects and corresponding construction factors. The eight-dimensional relational knowledge graph is a database designed for carbon emission analysis of building construction in the prior art.

[0026] The key construction factors affecting carbon emissions for each construction sub-project in this embodiment will now be explained.

[0027] In practice, after a construction company obtains its annual carbon allowance, it typically allocates internal allowances roughly based on macro-level quota indicators such as the output value and building area of ​​each individual construction project. A pattern emerges from this process: carbon emission values ​​and carbon allowances have a direct conversion relationship. Therefore, accurate carbon emission value analysis can provide a data foundation for carbon allowance calculation. However, combined with the aforementioned carbon emission analysis based on an eight-dimensional relational knowledge graph, this process involves a large amount of complex and redundant data, and the cost of full data screening is high. This situation contradicts the actual needs of carbon allowance calculation to efficiently screen core influencing parameters and simplify calculation dimensions. Therefore, this embodiment proposes an extraction design for key construction factors. In a specific example, this extraction can be achieved through relational graph label filtering combined with carbon emission contribution weight ranking. Thus, this embodiment provides key construction factors, defining core input parameters for subsequent factor classification and allowance modeling.

[0028] The division of fixed factors and adjustable factors in this embodiment will now be explained.

[0029] Construction factors, simply put, are various construction-related parameters that can influence carbon emissions during the construction phase. As mentioned earlier, key construction factors are the core parameters selected from all construction factors that have a significant impact on carbon emissions. Construction factors possess two attributes: those constrained by rigid construction conditions and those that can be flexibly adjusted through construction plan optimization. Similarly, key construction factors also possess two attributes: parameters that cannot be changed and parameters that can be optimized. Based on the different characteristics of fixed and adjustable parameters, this embodiment classifies factors into fixed and adjustable factors. This aims to eliminate ineffective optimization variables and focus quota optimization calculations only on adjustable factors, reducing the workload of accounting. In a specific example, the material parameters corresponding to the site boundary and design floor height are classified as fixed factors, while the parameters related to machinery selection and building material ratios are classified as adjustable factors. Therefore, this embodiment achieves parameter classification and control through the division of fixed and adjustable factors, laying a classification foundation for subsequent accurate modeling and quota optimization.

[0030] Thus, S10 of this embodiment completes project breakdown, key construction factor screening, and binary attribute division. In the implementation of carbon quota calculation, traditional quotas lack a parameter-based quantitative correlation model and rely solely on empirical coefficients for calculation, resulting in distorted results. Therefore, S20 was designed in this embodiment.

[0031] S20: Combining the impact patterns of key construction factors on carbon emissions, construct carbon quota calculation models for each construction sub-project. The carbon quota calculation models use the key construction factors of the construction sub-projects as input parameters and output the corresponding carbon quotas for the construction sub-projects.

[0032] In summary, S20 of this embodiment completes the construction of the sub-item calculation model, specifically the carbon quota calculation model. In the specific application of this embodiment, the carbon quota calculation model can adopt existing neural network model architectures, such as the BP neural network model, to achieve nonlinear relationship fitting of multi-dimensional key construction factors, accurately map the dynamic impact of construction factor fluctuations on carbon emissions and carbon quotas, and improve the accuracy and versatility of quota calculation under complex construction conditions.

[0033] The carbon quota calculation model of this embodiment will now be described in detail.

[0034] Specifically, construct carbon quota calculation models for each construction sub-project, including: Collect measured parameters of key construction factors and corresponding measured carbon emission data for construction sub-projects, and fit the variation pattern between key construction factors and carbon emissions.

[0035] Specifically, the key construction factors of a construction sub-project can be measured parameters such as fuel consumption of construction machinery, electricity consumption on site, and the amount of main materials used. The corresponding measured carbon emission data are the sub-item carbon dioxide emissions obtained from on-site verification and record-keeping by a third-party organization. This embodiment uses a dataset of multiple historical measured samples to fit the changing patterns between key construction factors and carbon emissions. For example, iterative training of the sample data is performed using a BP neural network, and after convergence, the correlation curve between the factors and emissions is obtained.

[0036] The fixed conversion relationship between carbon emissions and carbon quotas is determined based on the current project carbon quota accounting standards.

[0037] Combining the aforementioned fixed quota calculation methods such as output value and building area, and the database for carbon emission analysis in construction, represented by an eight-dimensional relational knowledge graph, the fixed conversion relationship in this embodiment can be, but is not limited to, a quantitative conversion formula formed by superimposing regional working condition correction coefficients on the officially released benchmark carbon emission coefficient for the construction industry. It should be noted that this conversion relationship complies with relevant domestic regulations on carbon accounting in construction, differs from traditional unified quotas for the entire project, and is adapted to the itemized conversion needs of various construction sub-projects.

[0038] A carbon quota calculation model is generated by integrating the changing patterns and fixed conversion relationships.

[0039] In the specific application of this embodiment, integrating the variation law and the fixed conversion relationship specifically involves deeply coupling the nonlinear correlation law between the factors obtained by training the BP neural network and carbon emissions with the compliant carbon emissions and quota quantification conversion relationship. Combining the nonlinear fitting and computing capabilities of the BP neural network, a carbon quota calculation model for refined sub-item carbon quota quantification and accounting is generated. This completes the calculation for the subdivided construction operation scenario with various key construction factor parameters of the construction sub-project as input and the accurate carbon quota value of the corresponding construction sub-project as output.

[0040] Based on S20, this embodiment realizes the quantitative modeling of key construction factors and carbon quotas for each construction sub-project, solving the problems of crude traditional quota calculation and poor adaptability to working conditions. In response to the actual project needs to combine officially approved quota limits and dynamically optimize construction parameters to obtain the optimal compliant quota, this embodiment provides S30, which aims to iteratively optimize parameters under quota constraints and output the optimal compliant carbon quota for a single construction project.

[0041] S30: Keep all fixed factors unchanged, change the parameters of adjustable factors and calculate the carbon quota of each construction sub-project one by one through the carbon quota calculation model, and sum up the carbon quota of all construction sub-projects to obtain the total carbon quota of a single construction project; use the maximum approved carbon quota of a single construction project as a constraint to optimize the parameters of adjustable factors and obtain the optimal carbon quota calculation result of a single construction project.

[0042] In summary, S30 of this embodiment achieves the technical effect of calculating the initial quota of a single unit and optimizing the quota to determine the optimal quota of a single unit.

[0043] Specifically, for calculating the initial carbon allowance for a single project, this embodiment locks all unchangeable fixed factor parameters and only performs multi-set parameter traversal calculations on adjustable factors that can be adjusted in the construction plan. Based on the established sub-project carbon allowance calculation model, the allowance calculation for each subdivided construction stage is completed one by one. Finally, the initial total carbon allowance for the single construction project is obtained by summing the individual items. For example, fixed factor parameters such as site conditions and structural design remain unchanged, while only adjustable factor parameters such as equipment shifts and building material losses are adjusted. The allowance values ​​for each construction sub-project under different construction conditions are calculated in batches, and the initial total allowance for the single construction project is obtained after summarizing. It should be noted that the technical principle of obtaining the initial total carbon allowance of a single construction project by summarizing the items in this embodiment is that the boundaries of the work processes of each construction sub-project are clear, the work content is independent of each other, and the carbon emissions generated by them do not have a coupling and overlapping relationship. This conforms to the basic principle of carbon accounting for construction items. By calculating the items independently and summarizing them step by step, the actual situation of the carbon allowance of the whole project can be truly restored, effectively avoiding the defects of coarse granularity and untraceable error in the traditional overall accounting model.

[0044] To optimize the carbon allowance for individual projects, the maximum carbon allowance approved by the competent authority is used as the upper limit. Within a reasonable range of adjustable factors, parameter combinations are iteratively optimized. The allowances for each sub-project and the total project amount are continuously recalculated until the total project allowance is converged within the approved limit. From this, the optimal parameter combination that balances construction feasibility is selected, and the final optimal carbon allowance result is output. In a simple example, if the initial calculated total exceeds the approved allowance limit, priority is given to optimizing high-carbon-emission adjustable parameters such as the selection of construction machinery and the proportion of main materials. This compresses the overall carbon allowance without altering fixed conditions such as the site and main structure, ensuring the calculation result is compliant and under control. This optimization logic differs from the traditional one-time quota setting method. It relies on parameter fine-tuning to achieve dynamic quota correction, satisfying both compliance control requirements and adapting to on-site construction conditions.

[0045] In the specific application of this embodiment, in order to further narrow the parameter optimization range, reduce invalid iterative calculations, and improve quota optimization efficiency, this embodiment also performs fine-grained constraint processing on the adjustable range of the adjustable factor. The constraint process is as follows: Specifically, the first-order and second-order variation characteristics of the impact of adjustable factors on carbon emissions are extracted; the control priority of each adjustable factor is determined based on the first-order variation characteristics; the parameter adjustment critical value of the adjustable factor is limited based on the second-order variation characteristics; and the actual adjustable parameter range of the adjustable factor is limited by combining the control priority and the parameter adjustment critical value.

[0046] Specifically, the first-order change characteristics are derived from the correlation between parameter adjustments and carbon emission changes, summarizing the carbon emission sensitivity of each factor. The second-order change characteristics are derived from the optimization upper limit characteristics of each factor, summarizing the carbon control performance after continuous parameter adjustments. In practice, adjustable factors belonging to key construction factors are distributed among various construction sub-projects under a single construction project. The optimization order and adjustment boundaries are determined based on the differences in sensitivity and optimization upper limits, thereby prioritizing the optimization of parameters with greater potential and eliminating parameter ranges with no practical optimization value, thus simplifying the overall optimization workload. For example, parameters such as fuel consumption of construction machinery and electricity consumption during construction can significantly reduce carbon emissions with small adjustments, exhibiting high sensitivity and thus being prioritized for control. After various parameters are adjusted to a certain limit, further modifications are unlikely to reduce carbon emissions further. This critical point is used as the parameter boundary to avoid redundant calculations caused by exceeding the limit. It needs further explanation that: A single construction project may contain multiple sub-projects. When adjusting adjustable factors, the core objective is to achieve the total carbon quota for the entire project. Adjustments to the adjustable parameters of each sub-project are optimized sequentially according to a preset control priority. No adjustment of any factor should exceed its own critical limit, taking into account the implementation requirements of each sub-project's construction process. This prevents a single sub-project's unilateral carbon reduction from hindering the normal construction of other processes, thus achieving optimal adjustment of adjustable factors within the single construction project. The preset control priority can be determined based on the carbon emission sensitivity of each adjustable factor extracted earlier. Higher sensitivity and more significant carbon reduction effects under the same parameter changes correspond to a higher control priority. In a simple example, pile foundation construction and main structure pouring are two separate sub-projects. Fuel consumption is a high-priority adjustable factor. Priority is given to reducing fuel consumption of pile foundation equipment. Once this factor reaches its adjustment threshold, the power consumption parameters for the main structure construction are then optimized. After overall adjustment, the single construction project meets the quota requirements, and both processes can be implemented normally.

[0047] Thus, based on the refined constraint processing of the adjustable range of the adjustable factor, this embodiment achieves a highly efficient quota optimization effect that reduces the range of invalid trial calculations and compresses the calculation time when iteratively optimizing the adjustable factor under quota constraints, which is different from the existing technology.

[0048] Building upon the requirement of carbon quota compliance, this embodiment further introduces an economic benefit screening dimension to refine the parameter selection logic. Specifically, during the optimization of adjustable factor parameters, the construction and renovation costs incurred from parameter adjustments and the market returns corresponding to surplus carbon quotas are simultaneously statistically analyzed. The optimal combination of adjustable factor parameters is determined by maximizing the net return of a single construction project after deducting construction and renovation costs.

[0049] The principle of introducing an economic benefit screening dimension to improve parameter selection in this embodiment will now be explained.

[0050] Existing technologies use the fact that the total carbon allowance of a single construction project does not exceed the approved limit as the sole criterion for parameter optimization. As long as the total allowance calculated by the parameter combination meets the compliance requirements, it is considered a feasible solution. As seen from the optimization examples of pile foundation construction and main structure pouring mentioned above, simple carbon control optimization can achieve the allowance standard by replacing low-fuel-consumption construction machinery and converting the entire line to energy-saving electrical equipment, etc. However, the cost of equipment replacement and process rectification corresponding to various adjustment schemes varies greatly. Although some schemes have outstanding carbon emission reduction effects and a large amount of surplus carbon allowances, the overall project will suffer losses due to excessive investment in the early stage of transformation. This embodiment, while maintaining the rigid constraint of carbon quota compliance, adds an economic benefit calculation step. It calculates the construction and modification costs and surplus carbon quota trading revenue for each sub-project's compliant parameter scheme, selecting the optimal parameters based on the net profit after deducting costs. While ensuring project carbon compliance and feasible construction procedures, it avoids the wasteful additional investment resulting from unilaterally pursuing extreme carbon reduction. From the project's operational perspective, it optimizes the combination of adjustable factors that balances compliance and economics, filling the technological gap in traditional quota optimization that only controls carbon emissions without considering the project's actual economic benefits. In the specific application of this embodiment, construction and modification costs can be obtained by statistically analyzing the equipment shift change costs, building material loss adjustment costs, construction process modification costs, and incremental labor costs resulting from adjusting adjustable factor parameters. The market revenue corresponding to surplus carbon quotas can be obtained by statistically analyzing the total amount of surplus carbon quotas after project optimization, combined with the current regional carbon trading market listing price and the converted carbon quota trading revenue. For example, when adjusting adjustable parameters such as fuel consumption of construction machinery and electricity consumption during construction, the various renovation expenditures incurred by equipment replacement, energy-saving equipment installation, and construction schedule optimization can be calculated item by item, and the total construction renovation cost of this parameter adjustment can be obtained by summing them up. At the same time, the remaining compliant carbon allowances that are not consumed after optimization are taken as surplus carbon allowances. Combined with the current average trading price of carbon in the construction industry, the market benefits that can be obtained through carbon trading and allowance replacement can be accurately calculated, providing accurate data support for subsequent net income calculation.

[0051] After selecting the optimal combination of adjustable factor parameters, in order to verify whether the quota results after substituting the parameters meet the constraints and avoid data deviation, this embodiment sets up parameter refresh and secondary verification steps: Specifically, the key construction factors of the corresponding construction sub-project are updated using the optimal combination of adjustable factor parameters. All the updated key construction factors are substituted into the carbon quota calculation model to recalculate the carbon quota of each construction sub-project and the total carbon quota of the individual construction project. After completing the secondary verification, the final carbon quota calculation data is output.

[0052] In light of the limitations of existing carbon quota calculation methods, such as the inability to verify the deviation of optimized parameters in a single calculation and the potential for aggregation calculation errors due to batch adjustments of multiple parameters during the optimization process in this embodiment, the technical effectiveness of the parameter refresh and secondary verification steps is explained.

[0053] Existing carbon quota calculation technologies, taking the traditional fixed-quota one-time calculation scheme as an example, suffer from several drawbacks. First, once parameters are selected, they are not recalculated or verified. Second, optimized parameters are only theoretically derived without a full re-modeling and calculation. This leads to inconsistencies between the paper data and the actual modeling and calculation results, ultimately resulting in an over-limit and invalidated quota. Therefore, this embodiment optimizes the scheme based on the aforementioned factor binary classification constraint and the multi-scheme economic selection rule. However, during optimization, it was found that the optimal parameters after economic screening are only derived from step-by-step trial calculations. Without a full recalculation using the carbon quota calculation model, the cumulative error of each item can easily accumulate and amplify. To address the potential mismatch between the cumulative error of the step-by-step trial calculations and the theoretical parameters and actual modeling results, this embodiment incorporates parameter refresh and secondary verification steps. This aims to eliminate the cumulative error from the step-by-step trial calculations by fully updating factor parameters and re-modeling and calculating the entire project, ensuring that the final output quota strictly adheres to the approved limit. In a simplified example, during the step-by-step parameter optimization process for the pile foundation construction and main structure pouring sub-projects, each individual calculation retained a small positive margin, ensuring that the quotas for each sub-project met compliance requirements and achieved optimal returns. However, when both sets of optimal parameters were simultaneously updated to all construction factors of a single construction project and substituted into the overall carbon quota calculation model for unified full-scale accounting, the originally small positive margin errors of each sub-item accumulated, causing the total carbon quota of the integrated single construction project to exceed the approved limit. Therefore, through the secondary verification step in this embodiment, the highly sensitive adjustable parameters are slightly corrected and the overall calculation is rechecked to eliminate the cumulative deviation caused by step-by-step optimization, ultimately ensuring that the output optimal parameter combination simultaneously meets the quota compliance requirements and the goal of optimal economic benefits. Thus, in response to the industry shortcomings of traditional optimization, which relies heavily on theoretical optimization and lacks practical verification, this embodiment improves the parameter optimization logic and parameter refresh and secondary verification steps by introducing an economic benefit screening dimension, achieving multiple goals such as carbon quota compliance, optimal project returns, and accurate calculation results. Unlike existing technologies, this solution takes into account carbon control constraints, economic benefits, and result verification, forming a complete closed-loop calculation system from parameter selection to result output.

[0054] After completing the optimal carbon allowance calculation and secondary verification output for individual construction projects, and considering that individual construction projects do not conduct carbon trading separately and carbon allowances are collected and disposed of in a unified manner by the enterprise as a whole, this embodiment adds a step of building a global allowance ledger to achieve overall allocation and management of carbon allowances among multiple projects.

[0055] Specifically, the optimal carbon allowance calculation results of all individual construction projects are summarized, and the actual carbon allowance consumption status of each individual construction project is monitored according to a preset fixed period. The carbon allowance surplus status and the carbon allowance deficit status are distinguished, and a dynamic ledger of carbon allowances for the entire project is established.

[0056] In the specific application of this embodiment, the optimal carbon allowance calculation results of all individual construction projects are summarized by collecting the final calculation form data of each individual construction project after secondary verification and archiving. For example, the finalized allowance data of each individual construction project under the enterprise is collected and organized item by item and uniformly entered into the corresponding sub-item column of the dynamic ledger. At a fixed period, such as a natural month, the actual carbon allowance consumption status of each individual construction project is obtained by item-by-item accounting through the construction site machinery fuel consumption ledger, water and electricity consumption documents, and main material entry verification ledger, thereby realizing the phased and refined monitoring of allowance consumption for each individual construction project. By combining the item-by-item benchmarking and accounting of the optimal allowance amount of each individual construction project with the actual carbon emission amount of the current period, the distinction between carbon allowance surplus status and deficit status is completed. In a simple example, the monthly construction carbon allowance of a residential building is 'a' tons of CO2. If the actual emission in the current month is less than 'a' tons, it is judged as allowance surplus, i.e., surplus status; if the actual emission in the current month is greater than 'a' tons, it is marked as allowance deficit, i.e., deficit status. Thus, this embodiment has constructed a dynamic carbon quota ledger for all individual construction projects of an enterprise, which includes quota collection, surplus inventory, and gap early warning and control.

[0057] From the perspective of construction companies, reasonable carbon allowance calculation can help them accurately predict carbon emission expenditures for individual construction projects, lock in carbon management budgets in advance, and avoid large additional expenditures caused by sudden carbon allowance shortfalls that force them to purchase allowances from the external market at high prices. Based on the dynamic carbon allowance ledger for the entire project in this embodiment, the allocation of carbon allowances within construction companies has been optimized.

[0058] Specifically, the dynamic ledger of carbon quotas for all projects in the region is retrieved to calculate the input cost required for projects with shortfalls to make up their quotas based on their own key construction factors and the quota revenue after making up their quotas. When the input cost required is greater than the quota revenue, the surplus carbon quotas of surplus projects are allocated to supplement projects with shortfalls. When the input cost required is less than or equal to the quota revenue, projects with shortfalls adjust their own key construction factors to make up their quotas themselves.

[0059] In the specific application of this embodiment, the cost required for a project to make up for its quota shortfall by relying on its own key construction factors, and the quota revenue after the shortfall, can be calculated by combining the aforementioned construction and renovation cost accounting rules and the market pricing standards for surplus carbon quotas. Thus, by summarizing the renovation investment item by item, calculating the increased revenue based on the current carbon price, and making numerical benchmarks, a comparison between the required investment cost and the quota revenue can be achieved, providing a basis for the internal transfer and allocation of carbon quotas or the independent rectification of projects. In a simple example, for a residential building with a quota shortfall, if the renovation investment to make up for the shortfall by optimizing equipment fuel consumption and reducing building material waste is higher than the market revenue from surplus quotas, then surplus quotas will be transferred from other residential buildings with surplus quotas within the enterprise to make up the shortfall; if the renovation investment is lower than the increased revenue from quotas, then the shortfall-stricken residential building will independently optimize key construction factors to complete the emission reduction and quota replenishment. Thus, this embodiment, based on the carbon quota dynamic ledger of the entire project and the quota data and cost pricing logic of each individual construction project, achieves the management objectives of optimal allocation of internal carbon quota resources, reduced external carbon quota procurement costs, and controllable carbon emissions across the entire project through a management approach that combines precise calculation of individual projects, comparison of profit and loss costs, and internal quota surplus and deficit allocation. It should be noted that the above technical solution can also play a role in precise carbon control, cost reduction and efficiency improvement, and optimized carbon resource allocation in scenarios such as multi-project parallel management, annual carbon quota coordination, and phased construction optimization in construction companies. In various engineering scenarios such as prefabricated construction, municipal infrastructure, and public building construction, this solution can be used to complete the selection of construction parameters, accurate verification of quotas, and dynamic allocation of internal quotas, demonstrating strong versatility and engineering applicability.

[0060] The application and effect of the multi-dimensional carbon quota calculation method for building construction in this embodiment are explained by comparing examples of existing technologies with examples of this embodiment.

[0061] Under the current common model in the construction industry, after a construction company obtains its annual carbon allowance from the government, the legally mandated quota is uniformly retained in the group headquarters account. Internally, the total allowance is divided into four categories using a fixed ratio: project-based rigid allowance, regional reserve allowance, headquarters contingency reserve, and technological upgrade incentive allowance. The proportions of these four types of allowances are fixed at the beginning of the year, and the allowances in the pool cannot be flexibly adjusted according to the actual working conditions of the project during the subsequent construction cycle. This embodiment adopts the existing industry management system of legally mandated allowances being collected at the headquarters and uniformly fulfilled by the enterprise. It breaks the limitation of the fixed ratio of the four types of allowances. Based on the dynamic carbon allowance ledger of the entire project, it summarizes the allowance surplus and deficit data of each individual construction project in real time, and dynamically adjusts the scale of funds consumption of each allowance pool as needed to adapt to changes in the project construction pace.

[0062] In the quota calculation stage of individual construction projects, existing technologies generally adopt single calculation methods such as output value intensity, building area, and historical emission base. Relying on fixed industry coefficients, they calculate the overall quota from a macroscopic perspective, without breaking down key construction details such as machinery fuel consumption, main material losses, and construction organization, and ignoring the differences in on-site construction conditions across different projects. This embodiment builds upon existing technologies to achieve multi-dimensional optimization of carbon emission analysis for individual construction projects. It breaks away from the traditional quota calculation framework, using a superior database to refine and break down various key construction factors of the project, generating multiple alternative quota schemes that closely match the actual construction conditions of individual construction projects, thus achieving refined quota calculation.

[0063] Regarding carbon quota verification, existing technologies complete project quota verification and issue internal control targets at the beginning of the year, only determining the final quota value. This lacks economic comparison of different construction schemes, forcing individual construction projects to passively adhere to the predetermined quota without a technological path for autonomous carbon control through optimized construction parameters. This embodiment, based on multiple alternative schemes, calculates the transformation costs and surplus quota benefits corresponding to each construction scheme, selecting the optimal combination of key construction parameters that balances carbon emission compliance and economic benefits. This achieves emission reduction from the construction source through process optimization, fundamentally reducing the risk of subsequent quota overruns. Furthermore, traditional schemes do not re-verify or correct quota data once verified, leading to the continuous accumulation of errors from itemized statistics and a high deviation between the final verified quota and the actual carbon emissions of the project. This embodiment, after selecting the optimal construction parameters, fully substitutes all key construction factors into the calculation model for overall recalculation, offsetting the accumulated errors from step-by-step calculations. After a second verification, the final quota for each individual construction project is determined, improving the accuracy of quota verification.

[0064] Entering the monthly management phase, existing technologies calculate project energy consumption monthly. If a quota shortfall occurs, priority is given to using branch office reserve quotas and headquarters' flexible quotas. If quotas are insufficient, the group must purchase quotas from the carbon market at a high price; otherwise, it faces compliance risks such as exceeding carbon emission standards, failing annual compliance, being included in the carbon emission blacklist, and incurring hefty fines. Surplus quotas circulate internally at a fixed discount. This embodiment relies on a monthly updated comprehensive ledger to distinguish the surplus and shortfall status of each project. It differentiates the handling based on the relationship between the project's self-rectification investment and quota revenue: when rectification investment exceeds quota revenue, surplus quotas within the company are allocated to fill the gap; when rectification investment is more economical, the project optimizes construction parameters to complete the emission reduction and quota replenishment. During the year-end settlement phase, existing technologies only buy and sell quotas based on the overall quota surplus or deficit of the entire enterprise. Performance evaluation is only tied to the final quota surplus result. Carbon quota management and project construction plan optimization are disconnected. In contrast, this embodiment moves carbon quota calculation to the construction plan selection stage and relies on dynamic ledgers for overall management and control throughout the entire cycle, achieving deep integration of project cost control and carbon asset management.

[0065] Therefore, compared with the existing passive management system of fixed quota calculation, quota solidification, and post-event guarantee purchase of the shortfall, the multi-dimensional carbon quota calculation method for building construction in this embodiment forms a complete closed loop of refined sub-item calculation, economic optimization parameter setting, secondary review and correction, dynamic overall planning of the whole domain ledger, and differentiated internal allocation without changing the carbon account compliance rules. It transforms carbon management from ex-post remediation to ex-ante optimization, effectively reducing the cost of purchasing carbon quotas for enterprises and improving the carbon resource utilization efficiency of the entire enterprise.

[0066] Based on the above, the multi-dimensional carbon quota calculation method for building construction in this embodiment overcomes the shortcomings of existing methods such as extensive quota calculation, fixed quota ratios, and passive external purchase of carbon quotas for shortfalls through a series of coordinated steps, including detailed calculation of key construction factors, selection of the best economic option from multiple schemes, secondary verification of calculation results, establishment of a dynamic quota ledger for the entire enterprise, and differentiated allocation of internal carbon quotas based on cost and benefit. It can accurately calculate the carbon emissions of individual projects, optimize processes from the construction source to reduce the probability of exceeding emission limits, coordinate the surplus and deficit of quotas across the entire enterprise based on the ledger, revitalize idle internal quota resources, and significantly reduce the enterprise's expenditure on expensive external purchases of quotas.

[0067] Reference Figure 2 , Figure 2 The structural block diagram of the multi-dimensional building construction carbon quota calculation device provided in this embodiment is shown in the figure. In the figure: 10, construction analysis module; 20, model building module; 30, calculation and optimization module.

[0068] like Figure 2 As shown, in a second aspect, this embodiment also discloses a multi-dimensional building construction carbon quota calculation device, which applies the multi-dimensional building construction carbon quota calculation method described above, including: Construction analysis module 10 is used to break down a single construction project into several construction sub-projects, extract the key construction factors that affect carbon emissions from each construction sub-project, and divide the key construction factors into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan based on preset construction implementation constraints. The model building module 20 is used to combine the impact of each key construction factor on carbon emissions to build a carbon quota calculation model for each construction sub-project. The carbon quota calculation model takes the key construction factors of the construction sub-project as input parameters and outputs the corresponding carbon quota of the construction sub-project. The calculation and optimization module 30 is used to keep all fixed factors unchanged, change the parameters of adjustable factors, and calculate the carbon quota of each construction sub-project one by one through the carbon quota calculation model. The total carbon quota of a single construction project is obtained by accumulating the carbon quota of all construction sub-projects. The parameters of the adjustable factors are optimized with the maximum approved carbon quota of a single construction project as a constraint to obtain the optimal carbon quota calculation result of a single construction project.

[0069] Thirdly, this embodiment also discloses a multi-dimensional building construction carbon quota calculation device, including at least one processor, at least one memory and a data bus; The processor and memory communicate with each other via a data bus; The memory stores program instructions that can be executed by the processor, which calls the program instructions to execute the multi-dimensional carbon quota calculation method for building construction as described above.

[0070] Fourthly, this embodiment also discloses a medium on which a computer program is stored, which, when executed by a processor, implements the multi-dimensional carbon quota calculation method for building construction as described above.

[0071] It should be noted that the multi-dimensional carbon quota calculation device, equipment, and medium for building construction in this embodiment correspond to the aforementioned multi-dimensional carbon quota calculation method for building construction. Therefore, any content not specifically described in the multi-dimensional carbon quota calculation device, equipment, and medium for building construction in this embodiment, including but not limited to functional definitions, working principles, and technical effects, can be referred to the description in the aforementioned multi-dimensional carbon quota calculation method for building construction, and will not be repeated here.

[0072] In summary, unlike traditional extensive accounting methods that are only used for report filling, the multi-dimensional carbon quota calculation method, device, equipment and medium of this embodiment realizes accurate carbon quota calculation for construction and runs through the entire chain of bidding, construction, settlement and carbon trading.

[0073] The following five aspects summarize how the multi-dimensional carbon emission calculation method, apparatus, equipment, and medium used in this embodiment generate real benefits for construction companies: First, reduce compliance procurement costs. Accurately predict annual quota surpluses and deficits by itemizing items such as machinery oil, temporary electricity, and main materials, and purchase quotas with shortfalls during off-peak periods and sell surpluses when appropriate; rely on ledgers to realize the paid transfer of internal quotas, reduce the scale of external purchases, and at the same time, apply for the full amount of official free quotas by accurately calculating carbon emission intensity, directly reducing carbon compliance expenses.

[0074] Second, optimize bid pricing and obtain project premiums. Incorporate carbon costs into project costs to avoid losses due to omitting carbon expenses in bids; use complete and quantifiable carbon accounting data as a basis for bonus points in bids for green building and EPC (Engineering Procurement Construction) projects, and leverage low-carbon qualifications to achieve bid premiums.

[0075] Third, energy conservation and cost reduction at construction sites. By relying on sub-item carbon quotas to identify high carbon consumption points such as idling machinery and ineffective transportation, we guide the optimization of equipment selection and construction flow, link subcontract carbon assessments, and select low-carbon building materials to achieve direct reduction in water, electricity, and fuel consumption.

[0076] Fourth, revitalize carbon assets to achieve diversified revenue generation. Accurately inventory surplus allowances and sell them on the market when appropriate; quantify emission reductions from prefabricated construction, on-site photovoltaics, etc., to develop CCERs (Chinese Certified Emission Reductions) for compliance deduction or external sales; improve carbon inventory materials to support carbon asset pledging and enjoy green low-interest loans.

[0077] Fifth, ensure compliance and risk avoidance, and realize policy benefits. Prepare sufficient quotas in advance to avoid penalties and credit risks for exceeding standards; apply for green building and prefabricated construction subsidies with formal carbon calculation data, improve ESG (Environmental, Social, and Governance) disclosures, meet the access requirements of high-standard clients such as central enterprises, and broaden cooperation channels.

[0078] In summary, the multi-dimensional carbon quota calculation method, device, equipment, and media of this embodiment simultaneously achieve carbon purchase cost control, increase bidding revenue, reduce construction energy consumption, revitalize carbon assets, and avoid compliance risks, resulting in significant economic benefits and remarkable industrial application value.

[0079] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0080] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A multi-dimensional method for calculating carbon emission allowances in building construction, characterized in that, include: The single construction project is broken down into several construction sub-projects. The key construction factors affecting carbon emissions of each construction sub-project are extracted. Based on the preset construction implementation constraints, the key construction factors are divided into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan. Based on the impact of key construction factors on carbon emissions, a carbon quota calculation model is constructed for each construction sub-project. The carbon quota calculation model uses the key construction factors of the construction sub-project as input parameters and outputs the corresponding carbon quota of the construction sub-project. The construction of carbon quota calculation models for each construction sub-project includes: collecting measured parameters of key construction factors and corresponding measured carbon emission data for each construction sub-project; fitting the variation patterns between key construction factors and carbon emissions; determining the fixed conversion relationship between carbon emissions and carbon quotas based on current project carbon quota accounting standards; and integrating the variation patterns and fixed conversion relationships to generate carbon quota calculation models. With all fixed factors kept constant, the parameters of adjustable factors are changed, and the carbon allowances for each construction sub-project are calculated one by one using the carbon allowance calculation model. The total carbon allowance for a single construction project is obtained by summing the carbon allowances of all construction sub-projects. The parameters of the adjustable factors are optimized using the maximum approved carbon allowance for a single construction project as a constraint, and the optimal carbon allowance calculation result for a single construction project is obtained.

2. The multi-dimensional carbon quota calculation method for building construction according to claim 1, characterized in that, During the optimization of the adjustable factor parameters, the construction and renovation costs generated by parameter adjustments and the market revenue corresponding to surplus carbon quotas are statistically analyzed simultaneously. The optimal combination of adjustable factor parameters is determined by maximizing the net revenue of a single construction project after deducting construction and renovation costs.

3. The multi-dimensional carbon quota calculation method for building construction according to claim 2, characterized in that, The key construction factors of the corresponding construction sub-projects are updated by using the optimal combination of adjustable factor parameters. All the updated key construction factors are then substituted into the carbon quota calculation model to recalculate the carbon quota of each construction sub-project and the total carbon quota of the individual construction project. After the second verification is completed, the final carbon quota calculation data is output.

4. The multi-dimensional carbon quota calculation method for building construction according to claim 1, characterized in that, The optimal carbon allowance calculation results of all individual construction projects are summarized, and the actual carbon allowance consumption status of each individual construction project is monitored according to a preset fixed period. The carbon allowance surplus status and the carbon allowance deficit status are distinguished, and a dynamic carbon allowance ledger for the entire project is established.

5. The multi-dimensional carbon emission calculation method for building construction according to claim 4, characterized in that, Retrieve the dynamic ledger of carbon quotas for all projects in the region, calculate the input cost required for projects with shortfalls to make up their quotas by relying on their own key construction factors, and the quota revenue after making up the quotas; when the required input cost is greater than the quota revenue, allocate the surplus carbon quotas of surplus projects to supplement projects with shortfalls; when the required input cost is less than or equal to the quota revenue, projects with shortfalls adjust their own key construction factors to make up their quotas themselves.

6. The multi-dimensional carbon quota calculation method for building construction according to claim 1, characterized in that, The first-order and second-order variation characteristics of the influence of adjustable factors on carbon emissions are extracted; the control priority of each adjustable factor is determined based on the first-order variation characteristics; the parameter adjustment critical value of the adjustable factor is limited based on the second-order variation characteristics; and the actual adjustable parameter range of the adjustable factor is limited by combining the control priority and the parameter adjustment critical value.

7. A multi-dimensional carbon emission calculation device for building construction, employing the multi-dimensional carbon emission calculation method for building construction as described in any one of claims 1 to 6, characterized in that, include: The construction analysis module is used to break down a single construction project into several construction sub-projects, extract the key construction factors that affect carbon emissions from each construction sub-project, and classify the key construction factors into fixed factors with unchangeable parameters and adjustable factors with changeable parameters in the construction plan based on preset construction implementation constraints. The model building module is used to combine the impact of various key construction factors on carbon emissions to build a carbon quota calculation model for each construction sub-project. The carbon quota calculation model takes the key construction factors of the construction sub-project as input parameters and outputs the corresponding carbon quota of the construction sub-project. The calculation and optimization module is used to keep all fixed factors unchanged, change the parameters of adjustable factors, and calculate the carbon quota of each construction sub-project one by one through the carbon quota calculation model. The total carbon quota of a single construction project is obtained by summing the carbon quotas of all construction sub-projects. The parameters of the adjustable factors are optimized with the maximum approved carbon quota of a single construction project as a constraint to obtain the optimal carbon quota calculation result of a single construction project.

8. A multi-dimensional carbon quota calculation device for building construction, characterized in that, Includes at least one processor, at least one memory, and a data bus; The processor and the memory communicate with each other via the data bus; The memory stores program instructions that can be executed by the processor, which invokes the program instructions to execute the multi-dimensional building construction carbon quota calculation method according to any one of claims 1 to 6.

9. A medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the multi-dimensional carbon quota calculation method for building construction as described in any one of claims 1 to 6.

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