Regional building carbon measurement and prediction method and system based on LCA-LEAP model, medium and processor
Through the LCA-LEAP model, regional building carbon emissions are divided into physical and chemical and usage consumption stages, and combined with macro factors to measure and predict, solving the problem of lack of effective measurement in the existing technology, and achieving effective management and prediction of regional building carbon emissions. It provides a scientific basis for the sustainable development of the construction industry.
Patent Information
- Application Number
- CN202411043470.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-31
- Publication Date
- 2024-12-24
AI Technical Summary
There is a lack of effective regional construction carbon emission measurement and prediction methods in the prior art, making it difficult to accurately understand and manage carbon emissions in the construction industry, and thus formulate emission reduction strategies.
Using the regional building carbon measurement and prediction method based on the LCA-LEAP model, the construction is constructed by dividing carbon emissions into the physical and chemical stage and the consumption stage, and using macro factors such as population size, per capita GDP, industrial structure, and urbanization rate. Carbon emissions throughout the life cycle are measured and predicted. Specifically, it includes energy consumption calculation, carbon emission factor coefficient acquisition, correlation calculation and prediction calculation.
Effective measurement and forecast of regional construction carbon emissions have been achieved, helping to achieve the sustainable development goals of the construction industry, and providing a scientific basis for improving energy efficiency and reducing greenhouse gas emissions.
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Figure CN119179842A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of regional building carbon emission monitoring, and in particular to a regional building carbon measurement and prediction method, system, medium and processor based on an LCA-LEAP model. Background Art
[0002] Regional building carbon measurement and forecasting refers to the process of measuring, analyzing, evaluating and forecasting the carbon emissions generated by all buildings in a specific area during their life cycle. This includes the design, construction, operation, maintenance and final demolition of buildings. The purpose of regional building carbon measurement is to better understand and manage carbon emissions in the construction industry, so as to develop effective emission reduction strategies. However, there is currently no effective measurement method for regional building carbon emissions, and it is urgent to explore regional building carbon measurement methods.
[0003] In view of this, a method, system, medium and processor for regional building carbon measurement and prediction based on the LCA-LEAP model are needed. Summary of the invention
[0004] In view of the problem that there is no effective measurement and prediction method for regional building carbon emissions in the prior art, the present invention provides a regional building carbon measurement and prediction method, system, medium and processor based on the LCA-LEAP model, which can effectively measure and predict the carbon emissions of regional buildings. The specific technical solution is as follows:
[0005] A regional building carbon measurement and prediction method based on the LCA-LEAP model, wherein the LCA model divides regional building carbon emissions into a materialization stage and a use and consumption stage, and measures carbon emissions in each stage;
[0006] Based on the carbon emission measurement of regional buildings, the LEAP model uses population size, per capita GDP, industrial structure, and urbanization rate as macro factors affecting building carbon emissions to calculate and predict future building carbon emissions; specifically, the following steps are included:
[0007] Obtain the building's energy use activity level and energy consumption intensity, and calculate the building's energy consumption over its entire life cycle;
[0008] Obtain the carbon emission factor coefficient and calculate the carbon emissions of the building throughout its life cycle;
[0009] Based on the calculated energy consumption and carbon emissions, the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is calculated;
[0010] Based on the correlation calculation, the carbon emissions of the building throughout its life cycle are predicted and calculated.
[0011] Furthermore, the energy consumption calculation formula for the entire life cycle of the building is as follows:
[0012]
[0013] In the above formula, ET is the total energy use of the building throughout its life cycle; n represents the energy type; i represents the different stages of the building's life cycle, including the materialization stage and the use and consumption stage; j represents the activity sector, including the primary, secondary and tertiary industries; AL refers to the energy use activity level of the j sector using energy type n in the i stage of the building's life cycle; EI represents the energy consumption intensity of the j sector using energy type n in the i stage of the building's life cycle.
[0014] Furthermore, the calculation formula of the energy usage activity level AL is as follows:
[0015] AL = SC × JG × TR;
[0016] In the above formula, SC represents the regional GDP; JG represents the proportion of industrial structure; TR represents the proportion of the corresponding industrial structure in the materialization stage of the construction industry.
[0017] Furthermore, the formula for calculating the carbon emissions of a building over its entire life cycle is as follows:
[0018]
[0019] In the above formula, CET is the carbon emission in the whole life cycle of the building; EF is the carbon emission factor coefficient of energy type n used by department j in stage i of the whole life cycle of the building.
[0020] Furthermore, the correlation calculation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is as follows:
[0021]
[0022] In the above formula, P represents the permanent urban population; P T represents the total population of the region; C ET Represents the building energy carbon emission coefficient; ET P represents the per capita energy consumption intensity of building operation; U represents the urbanization rate.
[0023] Furthermore, the carbon emissions during the entire life cycle of the building are predicted and calculated using the following calculation formula:
[0024] ΔCET=CET T -CET 0 =ΔC ET +ΔET P +ΔU+ΔP T ;
[0025] In the above formula, △CET is the change in carbon emissions during the entire life cycle of the building; △C ET is the impact effect of building energy carbon emission coefficient; △ET P represents the impact of per capita energy consumption intensity of building operation; △U represents the impact of urbanization rate; △P T represents the total population impact of the region; [0, T] is a decomposition time period in the entire life cycle of the building, CET 0 The carbon emissions at the beginning of the period, CET T For future carbon emissions.
[0026] Furthermore, the calculation formula for the impact effect of the building energy carbon emission coefficient is as follows:
[0027]
[0028] In the above formula, The initial building energy carbon emission coefficient is: Carbon emission coefficient of building energy for the future.
[0029] A regional building carbon measurement and prediction system based on the LCA-LEAP model is used to implement the regional building carbon measurement and prediction method as described above, comprising:
[0030] Energy consumption calculation module, which is used to obtain the building's energy use activity level and energy consumption intensity, and calculate the building's energy consumption over its entire life cycle;
[0031] Carbon emission calculation module, which is used to obtain carbon emission factor coefficients and calculate the carbon emissions of the building throughout its life cycle;
[0032] A correlation calculation module is used to calculate the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation based on the calculated energy consumption and carbon emissions;
[0033] The measurement module is used to predict and calculate the carbon emissions of a building throughout its life cycle based on correlation calculations.
[0034] A computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the regional building carbon measurement and prediction method as described above.
[0035] A processor is used to run a program, wherein the program executes the regional building carbon measurement and prediction method as described above when running.
[0036] Compared with the prior art, the present invention has the following beneficial effects:
[0037] 1. Be able to effectively measure and predict the carbon emissions of regional buildings.
[0038] 2. It can solve a series of problems related to building carbon emissions and help achieve the sustainable development goals of the construction industry.
[0039] 3. It can calculate regional building energy usage and regional building carbon emissions, and realize regional building energy and carbon emissions forecasts under different scenarios, providing a scientific basis for improving energy efficiency and reducing greenhouse gas emissions. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.
[0041] Figure 1 It is a flow chart of a method for measuring and predicting regional building carbon based on the LCA-LEAP model of the present invention;
[0042] Figure 2 It is a schematic diagram of the LCA-LEAP model structure of the present invention;
[0043] Figure 3 This is a schematic diagram of the carbon emissions prediction curve for the entire life cycle of a building. DETAILED DESCRIPTION
[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0045] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.
[0046] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.
[0047] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0048] Embodiment 1
[0049] The present invention is a regional building carbon measurement method based on the LCA-LEAP model. The LCA and LEAP models are combined to collect data from the bottom up, calculate and predict regional building carbon emissions more comprehensively, and evaluate their environmental impact and policy effects.
[0050] Based on the building life cycle theory, this study uses the LCA-LEAP model to establish Figure 2 The theoretical framework for calculating and predicting carbon emissions is shown in the figure. Based on the construction phase and the use and consumption phase as the main timeline, the carbon emissions of the building materials production and manufacturing phase, the construction phase, the use phase, and the demolition phase are calculated respectively. Figure 2 As shown in Figure 1, the LCA model divides regional building carbon emissions into the materialization stage and the use and consumption stage, and measures the carbon emissions in each stage. Based on the carbon emission measurement boundary, the carbon emissions of buildings throughout their life cycle mainly include the following three categories (such as Figure 2 (as shown in the LCA model in ): First, the carbon emissions caused by construction and building materials production are also called carbon emissions in the construction stage, that is, the implicit carbon emissions of buildings; secondly, the carbon emissions caused by fossil energy directly consumed in the building operation stage are mainly generated in activities such as cooking, hot water and decentralized heating in the building, that is, direct carbon emissions from buildings; finally, the carbon emissions caused by the two secondary energy sources of electricity and heat consumed in the building operation stage are the main sources of indirect carbon emissions in the building operation stage. Since direct carbon emissions and indirect carbon emissions occur during the use of the building, they are carbon emissions in the building use and consumption stage. The nature of carbon emissions in the building demolition stage is still secondary energy such as electricity as the emission source, so it also belongs to the implicit carbon emissions of buildings, and is calculated together with the indirect carbon emissions in the building operation stage.
[0051] Based on the carbon emission measurement of regional buildings at each stage, the LEAP model uses population size, per capita GDP, industrial structure, and urbanization rate as macro factors affecting building carbon emissions to calculate and predict future building carbon emissions.
[0052] From the above model, it can be seen that the carbon emissions in the construction stage involve the input and output consumption of the construction industry by other terminal sectors, and the carbon emissions in the building use stage involve various resident activities such as electricity, heat, cooking and decentralized heating. Figure 2 As shown in the LEAP model, population size, per capita GDP, industrial structure, urbanization rate, etc. will all affect building carbon emissions as macro factors and should be considered in the future forecast of building carbon emissions. Among them, population size affects the scale of building urbanization from the demand side and has a direct impact on carbon emissions during the building use phase. Per capita GDP and urbanization rate play a role in upgrading the energy consumption structure and are related to the electrification of building use terminals. The optimization of industrial structure helps to reduce carbon emissions in the production and manufacturing process of building materials, thereby achieving emission reduction and carbon reduction in the construction stage.
[0053] like Figure 1 The figure shows a flow chart of a regional building carbon measurement and prediction method based on the LCA-LEAP model, which specifically includes the following steps:
[0054] S1: Obtain the energy usage activity level and energy consumption intensity of the building, and calculate the energy consumption of the building throughout its life cycle.
[0055] In specific implementation, the energy consumption calculation formula for the entire life cycle of the building is as follows:
[0056]
[0057] In the above formula, ET is the total energy use of the building throughout its life cycle; n represents the energy type; i represents the different stages of the building's life cycle, including the materialization stage and the use and consumption stage; j represents the activity sector, including the primary, secondary and tertiary industries; AL refers to the energy use activity level of the j sector using energy type n in the i stage of the building's life cycle; EI represents the energy consumption intensity of the j sector using energy type n in the i stage of the building's life cycle.
[0058] S2: Obtain the carbon emission factor coefficient and calculate the carbon emissions of the building over its entire life cycle.
[0059] In specific implementation, the formula for calculating the carbon emissions of a building over its entire life cycle is as follows:
[0060]
[0061] In the above formula, CET is the carbon emission in the whole life cycle of the building; EF is the carbon emission factor coefficient of energy type n used by department j in stage i of the whole life cycle of the building.
[0062] Furthermore, the calculation formula of the energy usage activity level AL is as follows:
[0063] AL = SC × JG × TR;
[0064] In the above formula, SC represents the regional GDP; JG represents the proportion of industrial structure; TR represents the proportion of the corresponding industrial structure in the materialization stage of the construction industry.
[0065] Table 1 below is a table showing the proportion of GDP and industrial structure in a certain region in a certain year, Table 2 is a table showing the proportion of input of other industries in the materialization stage of the construction industry, and Table 3 is a table showing energy intensity:
[0066] Table 1
[0067] City Regional GDP (100 million yuan) Primary industry (%) Secondary industry (%) Tertiary industry (%) 28231.97 1.1 27.4 71.6
[0068] Table 2
[0069] Primary industry (%) Secondary industry (%) Tertiary industry (%) The proportion of other industries in the construction industry 0.1634 0.2203 0.1222
[0070] Table 3
[0071]
[0072]
[0073] The carbon emission factor coefficients corresponding to various energy types are shown in Table 4 below (the default CO2 emission factor in the table):
[0074] Table 4
[0075]
[0076] Calculation of carbon emissions during the construction phase in this region:
[0077] = Regional GDP * Industrial structure * Input ratio of the corresponding industrial structure in the materialization stage of the construction industry * Energy intensity corresponding to the industrial structure * Carbon emission factor
[0078] =319833842.53 (tons of CO2)
[0079] Calculation of carbon emissions during the building operation phase in this region:
[0080] Carbon emission activity level*Energy intensity of building operation in Guangzhou*Carbon emission factor
[0081] =9327644.47 (tons of CO2)
[0082] S3: Based on the calculated energy consumption and carbon emissions, the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is calculated.
[0083] In the specific implementation, the correlation calculation of carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is performed, and the correlation calculation formula is as follows:
[0084]
[0085] In the above formula, P represents the permanent urban population; P T represents the total population of the region; C ET Represents the building energy carbon emission coefficient; ET P represents the per capita energy consumption intensity of building operation; U represents the urbanization rate.
[0086] S4: Based on the correlation calculation, the carbon emissions of the building throughout its life cycle are predicted and calculated.
[0087] In the specific implementation, the carbon emissions in the entire life cycle of the building are predicted and calculated, and the calculation formula is as follows:
[0088] ΔCET=CET T -CET 0 =ΔC ET +ΔET P +ΔU+ΔP T ;
[0089] In the above formula, △CET is the change in carbon emissions during the entire life cycle of the building; △C ET is the impact effect of building energy carbon emission coefficient; △ET P represents the impact of per capita energy consumption intensity of building operation; △U represents the impact of urbanization rate; △P T represents the total population impact of the region; [0, T] is a decomposition time period in the entire life cycle of the building, CET 0 The carbon emissions at the beginning of the period, CET T For future carbon emissions.
[0090] Furthermore, the calculation formula for the impact effect of the building energy carbon emission coefficient is as follows:
[0091]
[0092] In the above formula, The initial building energy carbon emission coefficient is: Carbon emission coefficient of building energy for the future.
[0093] The calculation formula for the impact effect of per capita energy consumption intensity of building operation is as follows:
[0094]
[0095] In the above formula, The per capita energy consumption intensity of building operation at the beginning of the period is: Per capita energy consumption intensity of building operation in the future.
[0096] The calculation formula of the urbanization rate effect is as follows:
[0097]
[0098] In the above formula, U 0 is the initial urbanization rate, U T The urbanization rate in the future.
[0099] The calculation formula for the regional total population effect is as follows:
[0100]
[0101] In the above formula, The total population of the region at the beginning of the period, The total population of the region at the end of the period.
[0102] Table 5 below shows the average annual per capita energy consumption in the region:
[0103] Table 5
[0104] Energy Types 2021 Total (kg standard coal) 465.03 Coal (kg) 3.54 Gasoline (kg) 49.45 Kerosene (kg) 0.23 Diesel (kg) 1.55 Liquefied petroleum gas (kg) 33.78 Electricity (kWh) 1040.97
[0105] Table 6 below shows the impact coefficient of building energy carbon emissions in this region:
[0106] Table 6
[0107] 2016 2017 2018 2019 2020 2021 Factors affecting permanent population changes 5.23％ 4.04％ 2.97％ 1.84％ 2.34％ 0.38％ Factors affecting per capita energy intensity Coal (kg) \ \ \ -7.70％ -2.54％ -31.56％ Gasoline (kg) \ \ \ 33.38％ 0.02％ -20.29％ Kerosene (kg) \ \ \ -25.11％ -1.10％ -13.70％ Diesel (kg) \ \ \ 2.36％ -1.05％ -7.35％ Liquefied petroleum gas (kg) \ \ \ -2.12％ -14.75％ 0.72％ Electricity (kWh) \ \ \ 18.93％ 8.15％ 10.82％ Factors affecting urbanization rate 0.03％ -0.08％ 0.12％ 0.15％ 0.74％ 0.40％
[0108] Combined with the urbanization rate and regional total population data, we can calculate Figure 3 The carbon emissions forecast curve for the entire life cycle of a building is shown.
[0109] Compared with the prior art, the present invention has the following beneficial effects:
[0110] 1. Be able to effectively measure and predict the carbon emissions of regional buildings.
[0111] 2. It can solve a series of problems related to building carbon emissions and help achieve the sustainable development goals of the construction industry.
[0112] 3. It can calculate regional building energy usage and regional building carbon emissions, and realize regional building energy and carbon emissions forecasts under different scenarios, providing a scientific basis for improving energy efficiency and reducing greenhouse gas emissions.
[0113] Regional building carbon measurement is a systematic process that can solve a series of problems related to building carbon emissions and help achieve the sustainable development goals of the construction industry. Combining the LEAP model with the LCA model can calculate regional building energy usage and regional building carbon emissions, and at the same time achieve regional building energy and carbon emissions prediction under different scenarios, providing a scientific basis for improving energy efficiency and reducing greenhouse gas emissions.
[0114] Embodiment 2
[0115] A regional building carbon measurement and prediction system based on the LCA-LEAP model is used to implement the regional building carbon measurement and prediction method as described above, comprising:
[0116] Energy consumption calculation module, which is used to obtain the building's energy use activity level and energy consumption intensity, and calculate the building's energy consumption over its entire life cycle;
[0117] Carbon emission calculation module, which is used to obtain carbon emission factor coefficients and calculate the carbon emissions of the building throughout its life cycle;
[0118] A correlation calculation module is used to calculate the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation based on the calculated energy consumption and carbon emissions;
[0119] The measurement module is used to predict and calculate the carbon emissions of a building throughout its life cycle based on correlation calculations.
[0120] Embodiment 3
[0121] A computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the regional building carbon measurement and prediction method as described above.
[0122] Embodiment 4
[0123] A processor is used to run a program, wherein the program executes the regional building carbon measurement and prediction method as described above when running.
[0124] The present application provides a regional building carbon measurement and prediction method based on the LCA-LEAP model. The LCA model divides the regional building carbon emissions into the materialization stage and the use and consumption stage, and measures the carbon emissions in each stage; on the basis of measuring the carbon emissions of regional buildings, the LEAP model uses population size, per capita GDP, industrial structure, and urbanization rate as macro factors affecting building carbon emissions to calculate and predict the future carbon emissions of buildings; specifically includes the following steps: obtaining the energy use activity level and energy consumption intensity of the building, and calculating the energy consumption of the building throughout its life cycle; obtaining the carbon emission factor coefficient, and calculating the carbon emissions of the building throughout its life cycle; based on the calculated energy consumption and carbon emissions, performing correlation calculations between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient, and per capita energy consumption intensity of building operation; based on the correlation calculations, predicting and calculating the carbon emissions of the building throughout its life cycle. The present application can solve a series of problems related to building carbon emissions and help achieve the sustainable development goals of the construction industry. Combining the LEAP model with the LCA model can calculate regional building energy usage and regional building carbon emissions, and at the same time realize regional building energy and carbon emissions prediction under different scenarios, providing a scientific basis for improving energy efficiency and reducing greenhouse gas emissions.
[0125] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.
[0126] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.
[0127] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0128] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.
[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.
Claims
1. A regional building carbon measurement and prediction method based on LCA-LEAP model, characterized in that: The LCA model divides regional building carbon emissions into the materialization stage and the use and consumption stage, and measures the carbon emissions in each stage; Based on the measurement of carbon emissions of regional buildings, the LEAP model uses population size, per capita GDP, industrial structure, and urbanization rate as macro factors affecting building carbon emissions to calculate and predict future building carbon emissions; The specific steps include: Obtain the building's energy use activity level and energy consumption intensity, and calculate the building's energy consumption over its entire life cycle; Obtain the carbon emission factor coefficient and calculate the carbon emissions of the building throughout its life cycle; Based on the calculated energy consumption and carbon emissions, the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is calculated; Based on the correlation calculation, the carbon emissions of the building throughout its life cycle are predicted and calculated.
2. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 1 is characterized in that: The energy consumption calculation formula for the entire life cycle of the building is as follows: In the above formula, ET is the total energy use of the building throughout its life cycle; n represents the type of energy; i represents different stages in the life cycle of a building, including the materialization stage and the use and consumption stage; j represents the activity sector, including the primary, secondary and tertiary industries; AL refers to the energy use activity level of the j sector using energy type n in the i stage of the building's life cycle; EI represents the energy consumption intensity of the j sector using energy type n in the i stage of the building's life cycle.
3. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 2 is characterized in that: The calculation formula of the energy usage activity level AL is as follows: AL = SC × JG × TR; In the above formula, SC represents the regional GDP; JG represents the proportion of industrial structure; TR represents the proportion of the corresponding industrial structure in the materialization stage of the construction industry.
4. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 2 is characterized in that: The formula for calculating the carbon emissions of a building over its entire life cycle is as follows: In the above formula, CET is the carbon emission in the whole life cycle of the building; EF is the carbon emission factor coefficient of energy type n used by department j in stage i of the whole life cycle of the building.
5. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 4 is characterized in that: The correlation calculation formula for the carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation is as follows: In the above formula, P represents the permanent urban population; P T represents the total population of the region; C ET Represents the building energy carbon emission coefficient; ET P represents the per capita energy consumption intensity of building operation; U represents the urbanization rate.
6. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 5 is characterized in that: The carbon emissions during the entire life cycle of the building are predicted and calculated using the following formula: ΔCET=CET T -CET 0 =ΔC ET +ΔET P +ΔU+ΔP T ; In the above formula, △CET is the change in carbon emissions during the entire life cycle of the building; △C ET is the impact effect of building energy carbon emission coefficient; △ET P Represents the impact effect of per capita energy consumption intensity of building operation; △U represents the impact of urbanization rate; △P T represents the total population impact of the region; [0, T] is a decomposition time period in the entire life cycle of the building, CET 0 The carbon emissions at the beginning of the period, CET T For future carbon emissions.
7. The regional building carbon measurement and prediction method based on the LCA-LEAP model according to claim 6 is characterized in that: The calculation formula for the impact effect of the building energy carbon emission coefficient is as follows: In the above formula, The initial building energy carbon emission coefficient is: Carbon emission coefficient of building energy for the future.
8. A regional building carbon measurement and prediction system based on LCA-LEAP model, characterized in that: The method for implementing the regional building carbon measurement and prediction method according to any one of claims 1 to 7 comprises: Energy consumption calculation module, which is used to obtain the building's energy use activity level and energy consumption intensity, and calculate the building's energy consumption over its entire life cycle; Carbon emission calculation module, which is used to obtain carbon emission factor coefficients and calculate the carbon emissions of the building throughout its life cycle; A correlation calculation module is used to calculate the correlation between carbon emissions and population size, urbanization rate, building energy carbon emission coefficient and per capita energy consumption intensity of building operation based on the calculated energy consumption and carbon emissions; The measurement module is used to predict and calculate the carbon emissions of a building throughout its life cycle based on correlation calculations.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the regional building carbon measurement and prediction method according to any one of claims 1 to 7.
10. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the regional building carbon measurement and prediction method described in any one of claims 1 to 7.