A carbon emission deduction method based on dynamic boundary mapping

Abstract

The present application relates to carbon emission management technical field, especially a kind of carbon emission deduction method based on dynamic boundary mapping, comprising the following steps: obtaining the plot data of target area, the plot data at least includes the plot state of each plot;Receive the project development mode selected by user, generate corresponding mapping rule for determining the corresponding relationship between each plot state and carbon emission category;Three-dimensional dynamic boundary mapping matrix is constructed, and the three-dimensional dynamic boundary mapping matrix is with project development mode, plot state and carbon emission category as three dimensions;According to the current state of each plot, the three-dimensional dynamic boundary mapping matrix is inquired, and the activated carbon emission category of each plot is determined;According to the plot data of each plot and the activated carbon emission category, the carbon emission contribution value of each plot is calculated, and the total amount of regional carbon emission is aggregated;The present application solves the problem that carbon emission accounting rules are not unified under different development modes, reduces the complexity of user operation and error probability.

Description

Technical Field

[0001] This invention relates to the field of carbon emission management technology, and in particular to a carbon emission extrapolation method based on dynamic boundary mapping. Background Technology

[0002] As global climate change becomes increasingly severe, countries around the world have set carbon peaking and carbon neutrality goals. Cities, as major sources of carbon emissions, require low-carbon planning and construction management to achieve these dual carbon objectives. In urban renewal, new construction, or renovation projects, planners need a precise and dynamic tool to assess carbon emission trajectories under different scenarios to support informed decision-making.

[0003] Existing carbon emission accounting methods, when applied at the urban scale, mostly employ fixed calculation boundaries, failing to distinguish the complex mapping relationship between the construction status of land parcels and carbon emission types under different project models such as "existing built-up area accounting," "comprehensive area development," and "urban renewal." Under different project models, the carbon emission sources corresponding to the same land parcel status (e.g., preservation or new construction) are drastically different. Existing built-up areas only require accounting for operational emissions, while new construction areas require a focus on accounting for latent emissions. Users must manually select land parcels and determine their corresponding carbon emission calculation methods, a cumbersome and error-prone process, resulting in inconsistent calculation results across different project models.

[0004] Furthermore, traditional carbon accounting tools are mostly single-result calculations; once parameters are adjusted, the original results are overwritten. This makes it impossible to conduct trial and error and parameter optimization in isolated environments, or to create multiple independent scenarios for horizontal comparison. In terms of carbon peak prediction, existing methods mostly employ static estimation, failing to fully consider the gradual increase in production capacity during construction and operation, the dynamic changes in electric vehicle penetration, and the aggregation effect of one-off carbon emission events such as demolition, new construction, and renovation over time. This leads to distortions in long-term carbon emission trajectory predictions.

[0005] Therefore, there is an urgent need for a carbon emission extrapolation method that can adapt to various project development models, support multi-scheme management and dynamic hypothesis analysis, and achieve high-precision carbon peak prediction. Summary of the Invention

[0006] The purpose of this invention is to propose a carbon emission extrapolation method based on dynamic boundary mapping, which at least solves one of the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A carbon emission extrapolation method based on dynamic boundary mapping includes the following steps:

[0009] Obtain land parcel data for the target area, wherein the land parcel data includes at least the land parcel status;

[0010] Receive the project development mode selected by the user;

[0011] Based on the project development model, corresponding mapping rules are generated, which are used to determine the correspondence between the status of each plot and the carbon emission category;

[0012] A three-dimensional dynamic boundary mapping matrix is ​​constructed, which has three dimensions: project development mode, land parcel status, and carbon emission category.

[0013] Traverse each plot and query the three-dimensional dynamic boundary mapping matrix based on the current state of each plot to determine the activated carbon emission category of each plot;

[0014] Based on the land parcel data and the activated carbon emission categories, the carbon emission contribution value of each parcel is calculated, and the total regional carbon emissions are aggregated.

[0015] A further improvement is that the land parcel status includes at least one of preservation, new construction, demolition, and renovation; the project development mode includes at least one of existing built-up area mode, integrated area development mode, urban renewal mode, and mixed development mode; the carbon emission category includes at least one of building operation emission category, building implicit emission category, demolition emission category, and renovation construction emission category; wherein, the building operation emission category is used to calculate the carbon emissions generated by the daily operation of existing buildings on the land parcel, the building implicit emission category is used to calculate the carbon emissions during the production and construction of new building materials, the demolition emission category is used to calculate the carbon emissions generated by building demolition construction, and the renovation construction emission category is used to calculate the carbon emissions generated by building renovation construction.

[0016] A further improvement is that the specific method for generating the corresponding mapping rules based on the project development mode includes:

[0017] When an existing built-up area mode is selected, only plots in the reserved state will be mapped to the building operation emissions category;

[0018] When a comprehensive development model for a given area is selected, plots in the "reserved" category are mapped to building operation emission categories, and plots in the "newly constructed" category are mapped to building implicit emission categories.

[0019] When the urban renewal mode is selected, plots in the "preservation" status are mapped to the building operation emission category, plots in the "demolition" status are mapped to the demolition emission category, and plots in the "renovation" status are mapped to the renovation construction emission category.

[0020] When a mixed development model is selected, plots in the "Reserved" status are mapped to the building operation emission category, plots in the "New Construction" status are mapped to the building implicit emission category, plots in the "Demolition" status are mapped to the demolition emission category, and plots in the "Remodeling" status are mapped to the remodeling construction emission category.

[0021] A further improvement lies in the specific method for traversing each land parcel, querying the three-dimensional dynamic boundary mapping matrix based on the current state of each parcel, and determining the activated carbon emission category of each parcel, including:

[0022] Read the current status of each plot one by one and obtain the plot identifier of each plot;

[0023] Using the project development mode and the current land parcel status as indexes, query the corresponding list of activation categories in the three-dimensional dynamic boundary mapping matrix;

[0024] The list of activated categories is used as the set of categories for the land parcel to participate in carbon emission calculation. The list of activated categories contains all the carbon emission category names that the land parcel needs to participate in carbon emission calculation under the current project development mode and the current land parcel status.

[0025] A further improvement is that the specific method for calculating the carbon emission contribution value of each plot based on the plot data and the activated carbon emission category, and aggregating to obtain the total regional carbon emissions, includes: for each plot, calling the calculation function corresponding to each activated carbon emission category of the plot, calculating the carbon emission contribution value of each category based on the land use type, area and plot ratio in the plot data; and adding the carbon emission contribution values ​​of each plot under each category to obtain the total regional carbon emissions.

[0026] A further improvement is that the method further includes: in response to the user's scheme creation request, generating an independent simulation scheme, wherein the simulation scheme saves the selected project development mode, land parcel data modification records and the total carbon emissions of the region; the land parcel data modification records include a historical record of each change made by the user to the land parcel status, land use type and area attributes; and different simulation schemes are isolated from each other.

[0027] A further improvement is that the method also includes a step for estimating the year of carbon peak:

[0028] Set the start year and target year, and receive the annual production rate curve, electric vehicle penetration rate change parameters, demolition year, new construction year and renovation year;

[0029] Using the total carbon emissions in the region as a benchmark, operational carbon emissions and primary carbon emissions are calculated year by year and then superimposed to obtain the assessment carbon emission sequence.

[0030] The annual production rate curve is calculated by linear interpolation for each year. The carbon emission in the operational caliber is equal to the sum of the emission categories in the operational caliber multiplied by the production rate and minus the emission reduction amount. The primary carbon emission includes demolition emissions included in the demolition year, implicit emissions included in the new construction year, and renovation construction emissions included in the renovation year.

[0031] When the carbon emission sequence under the aforementioned assessment criteria first shows a decline, the previous year is determined to be the peak year.

[0032] A further improvement is that the method further includes: in response to a user's operation to modify the status of a target plot, re-determining the activated carbon emission category of the target plot according to the mapping rules; recalculating the carbon emission contribution value of the target plot and the carbon emission contribution values ​​of related plots affected by it, and updating the total carbon emissions of the region.

[0033] A further improvement is that the method further includes: creating one or more comparative scenarios within the same simulation scheme, and independently configuring parameter adjustment values ​​for each comparative scenario; the parameter adjustment values ​​include the carbon emission coefficient of residential buildings, the carbon emission coefficient of public buildings, the increase or decrease in electric vehicle penetration rate, the increase or decrease in the proportion of renewable energy, and the green building level; calculating the carbon emission contribution value of each comparative scenario, comparing the calculation results of each comparative scenario with the calculation results of the baseline scenario, and generating the emission change of each scenario.

[0034] A further improvement is that the method further includes an uncertainty propagation step: receiving the uncertainty percentage set by the user for each carbon emission category; calculating the absolute uncertainty of each carbon emission category, wherein the absolute uncertainty is equal to the absolute value of the carbon emission contribution of that carbon emission category multiplied by its uncertainty percentage; synthesizing the total uncertainty using the square root method; and generating a confidence interval for net carbon emissions based on the total uncertainty.

[0035] The beneficial effects of this invention are as follows:

[0036] This invention constructs a dynamic boundary mapping matrix with three dimensions: project development mode, land parcel status, and carbon emission category. This allows the carbon emission calculation boundary to adaptively switch according to different project development modes and land parcel statuses. Compared to existing technologies that use fixed calculation boundaries, this invention achieves automatic mapping between land parcel status and carbon emission category. Users only need to select the project development mode to match the correct carbon emission category for each parcel, eliminating the need for manual parcel selection and calculation rule configuration. This solves the problem of inconsistent carbon emission calculation rules under different development modes, reducing user complexity and the probability of errors. Attached Figure Description

[0037] Figure 1This is a flowchart of a carbon emission extrapolation method based on dynamic boundary mapping according to the present invention;

[0038] Figure 2 A flowchart illustrating a specific method for traversing each land parcel, querying the three-dimensional dynamic boundary mapping matrix based on the current state of each parcel, and determining the activated carbon emission category of each parcel. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. The described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0041] Please refer to the attached document. Figure 1 This invention proposes a carbon emission extrapolation method based on dynamic boundary mapping. The method is applied to a digital management platform for urban carbon emissions, which connects to multiple data sources such as land parcel database, regional boundary database, and carbon emission factor database.

[0042] The carbon emission extrapolation method based on dynamic boundary mapping includes the following steps:

[0043] Step S1: Obtain land parcel data for the target area, wherein the land parcel data includes at least the land parcel status of each parcel.

[0044] Step S2: Receive the project development mode selected by the user.

[0045] Step S3: Generate corresponding mapping rules based on the project development model. The mapping rules are used to determine the correspondence between the status of each land parcel and the carbon emission category.

[0046] Step S4: Construct a three-dimensional dynamic boundary mapping matrix, which has three dimensions: project development mode, land parcel status, and carbon emission category.

[0047] Step S5: Traverse each plot of land, query the three-dimensional dynamic boundary mapping matrix based on the current state of each plot of land, and determine the activated carbon emission category of each plot of land.

[0048] Step S6: Calculate the carbon emission contribution value of each plot based on the plot data and the activated carbon emission categories, and aggregate them to obtain the total regional carbon emissions.

[0049] The method steps of the present invention will be described in detail below:

[0050] Specifically, in step S1, the land parcel data originates from an urban land use planning database or a GIS system, and the data format is CSV or Excel. The land parcel data includes at least the parcel status, parcel identifier, land use type (including residential, commercial, industrial, green space, etc.), region, area, and geographic coordinates (a polygon boundary point set in WKT or GeoJSON format). Based on the geographic coordinates, land parcel polygons are generated on a map, and a land parcel lifecycle database is established to store the current data and historical change records of each parcel.

[0051] It is understandable that the land parcel status is the core basis for determining the carbon emission category, with different statuses corresponding to different carbon emission sources. In this embodiment, the land parcel status refers to the life cycle attribute of the stage of development and construction of the land parcel, including preservation, new construction, demolition, and renovation. Different land parcel statuses correspond to different types of carbon emission sources. Specifically: "Preservation" means that the land parcel maintains its existing construction status, and its carbon emissions mainly come from the daily operation energy consumption of existing buildings; "New Construction" means that the land parcel is developed for the first time from a vacant or undeveloped state, and its carbon emissions mainly come from the energy consumption of building material production, transportation, and construction processes; "Demolition" means that the existing buildings on the land parcel are demolished, and its carbon emissions mainly come from the energy consumption of demolition machinery operations and emissions during the disposal of construction waste; "Renovation" means that the existing buildings on the land parcel are renovated or expanded, and its carbon emissions mainly come from the consumption of building materials and construction energy during the renovation construction process.

[0052] Specifically, in step S2, the project development mode reflects the overall development and construction type of the target area, determining the macro-boundary of carbon emission accounting. Users can select from preset modes through the drop-down menu on the system interface. The project development modes include existing built-up area mode, integrated area development mode, urban renewal mode, and mixed development mode.

[0053] Understandably, different project development models correspond to different carbon emission accounting focuses: the existing built-up area model only needs to account for the daily operation carbon emissions of existing buildings; the integrated development model of a district needs to focus on accounting for the implicit carbon emissions of new buildings in the process of material production, transportation, and construction; the urban renewal model involves the carbon emissions from the demolition of existing buildings and the carbon emissions from renovation construction; and the mixed development model covers all of the above carbon emission types. Therefore, it is necessary to adaptively adjust the activated carbon emission categories for each plot according to the selected model.

[0054] In step S3, the mapping rule is used to determine the correspondence between the status of each land parcel and the carbon emission category, that is, under a certain project development model, which carbon emission categories should a land parcel in a certain status participate in the calculation of.

[0055] Specifically, the carbon emission categories refer to various emission source types involved in carbon emission calculations, with each category corresponding to a specific carbon emission source. After activating the corresponding carbon emission category based on the land parcel status, the appropriate calculation method is invoked to calculate the carbon emission contribution value. Specifically, the carbon emission categories include building operation emission categories, building implicit emission categories, demolition emission categories, and renovation construction emission categories. Among them, the building operation emission category is used to calculate the carbon emissions generated by the daily operation of existing buildings on the land parcel, such as energy consumption emissions from heating, cooling, lighting, and appliance use; the building implicit emission category is used to calculate the carbon emissions during the production and construction of new building materials; the demolition emission category is used to calculate the carbon emissions generated by building demolition construction; and the renovation construction emission category is used to calculate the carbon emissions generated by building renovation construction.

[0056] In this embodiment, the mapping rules are as follows:

[0057] (1) When the user selects an existing built-up area mode, only plots with a status of "reserved" will be mapped to the building operation emissions category.

[0058] Understandably, in the existing built-up area model, existing buildings in the area are already in operation, and carbon emissions mainly come from the energy consumption during the daily operation of the buildings. Therefore, only the operational emission category is activated, without involving carbon emissions related to new construction, demolition, or renovation.

[0059] (2) When the user selects the area integrated development mode, the plots with the status of "reserved" are mapped to the building operation emission category, and the plots with the status of "new" are mapped to the building implicit emission category.

[0060] It is understandable that the comprehensive development of the area is mainly based on new construction, with a small number of existing buildings remaining in the area. Therefore, the emissions from the operation of the existing plots are calculated, while the emissions from the new plots are calculated based on the hidden emissions.

[0061] (3) When the user selects the urban renewal mode, the plots with the status of "reserved" are mapped to the building operation emission category, the plots with the status of "demolition" are mapped to the demolition emission category, and the plots with the status of "renovation" are mapped to the renovation construction emission category.

[0062] Understandably, urban renewal mainly involves the demolition and renovation of existing buildings. Therefore, emissions are calculated for operation on sites that are retained, for demolition sites, for demolition sites, and for renovation sites, for renovation construction emissions.

[0063] (4) When the user selects the hybrid development mode, the plots with the status of "reserved" are mapped to the building operation emission category, the plots with the status of "new construction" are mapped to the building implicit emission category, the plots with the status of "demolition" are mapped to the demolition emission category, and the plots with the status of "remodeling" are mapped to the remodeling construction emission category.

[0064] Understandably, the hybrid development model combines the features of the first three models while activating all carbon emission categories corresponding to the site status.

[0065] Specifically, in step S4, the three dimensions of the three-dimensional dynamic boundary mapping matrix are: project development mode (including existing built-up areas, integrated development of areas, urban renewal, and mixed development), land parcel status (including preservation, new construction, demolition, and renovation), and carbon emission category (including building operation, building concealment, demolition, and renovation construction).

[0066] In this embodiment, the three-dimensional dynamic boundary mapping matrix is ​​implemented using a lookup table. Specifically, each cell in the matrix indicates whether a certain carbon emission category is activated for a plot of land in a specific state under a specific project development mode. When the cell value is "yes", the category is activated for the plot of land; when the cell value is "no", the category is deactivated for the plot of land.

[0067] It is understandable that the three-dimensional dynamic boundary mapping matrix is ​​the core decision-making center for the adaptive switching of carbon emission boundaries. The system quickly determines which carbon emission categories should be activated for calculation and which categories should be ignored for a plot of land under a specific mode and in a certain state by looking up a table.

[0068] Specifically, such as Figure 2 As shown, in step S5, the specific method for traversing each land parcel, querying the three-dimensional dynamic boundary mapping matrix based on the current state of each land parcel, and determining the activated carbon emission category of each land parcel includes:

[0069] S51: Read the current status of each land parcel one by one and obtain the land parcel identifier of each land parcel.

[0070] S52: Using the project development mode and the current land parcel status as indexes, query the corresponding list of activation categories in the three-dimensional dynamic boundary mapping matrix.

[0071] S53: The list of activated categories is used as the set of categories for the land parcel to participate in carbon emission calculation. The list of activated categories contains all the carbon emission category names that the land parcel needs to participate in carbon emission calculation under the current project development mode and the current land parcel status.

[0072] For example, in the "Urban Renewal" model, a plot of land with a status of "Reserved" is identified as having an activation category of "Building Operation Emissions" after querying the matrix; a plot of land with a status of "Demolition" is identified as having an activation category of "Demolition Emissions".

[0073] Specifically, in step S6, the method for calculating the carbon emission contribution value of each plot based on the plot data and the activated carbon emission category, and aggregating to obtain the total regional carbon emissions, includes: for each plot, calling the calculation function corresponding to each activated carbon emission category of the plot, calculating the carbon emission contribution value of each category based on the land use type, area and plot ratio in the plot data; and adding the carbon emission contribution values ​​of each plot under each category to obtain the total regional carbon emissions.

[0074] Taking building operation emissions as an example, the formula for calculating the carbon emission contribution value of building operation is as follows:

[0075]

[0076] in, Contribution to carbon emissions from building operations (unit: tons of CO2). The area of ​​the land parcel is expressed in square meters. Floor area ratio (dimensionless). Operating intensity (unit: tons of CO2 / square meter·year). The grid factor (unit: tons of CO2 / 10,000 kWh) is used for grid factors. The green building coefficient (dimensionless).

[0077] Specifically, the operational intensity This refers to the annual carbon emissions per unit area of ​​a building due to energy consumption for heating, cooling, lighting, and electrical appliances. For residential land, the operating intensity ranges from 0.02 to 0.06 tons of CO2 / m²·year; for commercial land, it ranges from 0.06 to 0.15 tons of CO2 / m²·year; and for office land, it ranges from 0.04 to 0.10 tons of CO2 / m²·year. These values ​​are derived from regional building energy consumption statistics and grid carbon emission factors. The specific value should be selected by the user within the range based on the building type and energy intensity, or the system default value should be used.

[0078] The power grid factor The carbon emission factor of the regional power grid reflects the carbon emission intensity per unit of electricity consumption. The value of the power grid factor ranges from 0.3 to 1.2 tons of CO2 per 10,000 kilowatt-hours. The specific value is derived from the annual power grid emission factor data released by the national or local ecological and environmental authorities. Users can select the corresponding power grid factor value according to the power grid region to which the target area belongs, or the system can automatically match it according to the region to which the plot belongs.

[0079] The green building coefficient The green building coefficient is determined based on the building's green building rating; the basic level has a green building coefficient of 1.0, the one-star level has a coefficient of 0.95, the two-star level has a coefficient of 0.88, and the three-star level has a coefficient of 0.78. The green building coefficient reflects the ability of a green building to reduce operational carbon emissions through energy-saving design and the use of renewable energy; the higher the rating, the more significant the carbon reduction effect.

[0080] The carbon emission contribution of the building's implicit emission category can be calculated in the following ways:

[0081]

[0082] in, Contribution to building's implicit carbon emissions (unit: tons of CO2). This refers to the number of new buildings constructed on the land plot. For the first The building area of ​​the newly constructed building (unit: square meters). For the first The floor area ratio (dimensionless) of a newly constructed building. For the first Implicit carbon intensity of a newly constructed building (unit: tons of CO2 / square meter).

[0083] Specifically, the implicit carbon intensity This refers to the carbon emissions generated per unit building area during the production, transportation, and construction of building materials. For reinforced concrete structures, the implicit carbon intensity ranges from 0.8 to 1.5 tons of CO2 per square meter; for masonry structures, it ranges from 0.4 to 0.8 tons of CO2 per square meter; and for steel structures, it ranges from 1.0 to 2.0 tons of CO2 per square meter. These values ​​are derived from building material carbon emission factor databases, such as the China Building Material Carbon Emission Factor Database or similar international databases. The specific value is selected by the user within the range based on the amount and type of building materials used in the building design scheme, or the system default value is adopted.

[0084] The carbon emission contribution of the aforementioned removal emission category can be calculated in the following way:

[0085]

[0086] in, Carbon emission contribution to dismantling (unit: tons of CO2). This refers to the number of buildings demolished on the plot of land. For the first The building area of ​​the demolished building (unit: square meters). For the first Demolition emission coefficient of the building to be demolished (unit: tons of CO2 / square meter).

[0087] Specifically, the removal emission coefficient The value is determined based on the building structure type and demolition method. For reinforced concrete structures, when using mechanical demolition, the demolition emission factor ranges from 0.03 to 0.08 tons of CO2 / m²; for masonry structures, the range is 0.02 to 0.05 tons of CO2 / m²; and for steel structures, the range is 0.01 to 0.03 tons of CO2 / m². These values ​​are derived from the building material carbon emission factor database and construction machinery energy consumption statistics. The specific value is selected by the user within the stated range based on the actual demolition plan or by using the system default value.

[0088] The carbon emission contribution of the aforementioned renovation construction emission category can be calculated in the following ways:

[0089]

[0090] in, Carbon emission contribution of the renovation and construction (unit: tons of CO2). The number of buildings to be renovated on the site. For the first The renovation area of ​​the building (unit: square meters). For the first Construction intensity of a building renovation project (unit: tons of CO2 / square meter). Carbon emission factor during construction (unit: tons of CO2 / ton of building materials).

[0091] Specifically, the intensity of the renovation construction The carbon emissions per unit area during the renovation process are defined as 0.05 to 0.30 tons of CO2 per square meter, with the specific value determined based on the type of renovation (expansion, reconstruction, or renovation) and scale. The construction carbon emission factor is also mentioned. The carbon emission intensity of energy consumption during construction is defined as 0.5 to 1.5 tons of CO2 per ton of building materials, with the specific value determined based on the construction method and the energy type of the construction machinery.

[0092] Finally, the carbon emission contribution of each plot under each activation category is calculated sequentially, and the carbon emission contribution of all plots is added together to obtain the total regional carbon emissions.

[0093] In a preferred embodiment of the present invention, the method further includes a multi-scheme management step. Multi-scheme management refers to creating and maintaining multiple independent simulation schemes within the system, with each scheme fully storing all analysis parameters and calculation results, allowing users to switch and compare between different schemes. Specifically, it includes the following steps:

[0094] In response to a user's scheme creation request, an independent simulation scheme is generated. This simulation scheme saves the selected project development mode, all global parameters (population, GDP, power grid factor, etc.), land parcel data and modification records for each parcel, the total regional carbon emissions calculated in step S6, and detailed calculation results for each carbon emission category. The land parcel data modification records include a historical record of every change the user made to attributes such as parcel status, land use type, and area. Different simulation schemes are isolated from each other; modifications to one scheme will not affect other schemes. The system also supports the creation, saving, switching, and comparison of schemes. Users can freely switch between multiple schemes for viewing, and can also overwrite or save as a new scheme after modification.

[0095] Understandably, this invention, by introducing a multi-scheme management mechanism, supports users in creating multiple independent and isolated simulation schemes. Each scheme independently saves its selected project development mode, land parcel data modification records, and carbon emission calculation results. Different schemes are independent of each other and do not affect each other. Users can perform parameter optimization and scheme trial and error in an isolated environment, and can switch and compare different schemes at any time, realizing multi-scheme comparison and hypothesis analysis.

[0096] In a preferred embodiment of the present invention, the method further includes a step of estimating the year of carbon peak.

[0097] Understandably, the carbon peak year projection is based on the carbon emission calculation results, and introduces a dynamic extrapolation of the time dimension to simulate the complete trajectory of regional carbon emissions evolving from the current state to the peak and neutralization.

[0098] The calculation of the year of carbon peaking specifically includes the following steps:

[0099] Users set the starting year through the system interface. and target year It accepts the following input parameters: annual production rate curve, electric vehicle penetration rate change parameters, and year of demolition. New Year Year of renovation And annual emission reductions. Among them, This indicates the year in which the demolition event occurred within the target area, meaning that the carbon emissions corresponding to the emission category of the demolition in that year are included in the assessment criteria. This indicates the year in which the new construction event occurred, meaning that the carbon emissions corresponding to the building's implicit emission category in that year were included in the assessment criteria. This indicates the year in which the renovation event occurred, meaning the carbon emissions corresponding to the renovation construction emission category in that year were included in the assessment. The above year parameters are set by the user in the system interface according to the project construction plan.

[0100] The annual production rate curve reflects the process of gradually increasing the building area or population to full capacity ("production rate") from the initial construction phase to mature operation in a region. The production rate is a percentage value that changes annually, for example, 40% in 2024, 70% in 2028, and 100% in 2032. The production rate for intermediate years is calculated using linear interpolation. The formula for linear interpolation is:

[0101]

[0102] in, and For two known interpolation nodes (such as two year points on the production rate curve). For the year to be calculated, This is the interpolation result for the year to be calculated.

[0103] The electric vehicle penetration rate variation parameters are the electric vehicle penetration rate in the starting year and the electric vehicle penetration rate in the target year. The penetration rate in intermediate years is also calculated by linear interpolation.

[0104] Using the total regional carbon emissions obtained in step S6 as a baseline, the following method is used to calculate annually:

[0105] First, for each year The production rate is calculated using the linear interpolation formula described above. and electric vehicle penetration rate .

[0106] Then, calculate the carbon emissions in the operational metric. :

[0107]

[0108] in, The sum of carbon emissions from building operations across all sites. , , These are the carbon emission values ​​for industrial, transportation, and municipal categories, respectively. The carbon absorption value for the carbon sink category. For the first Annual emission reductions for the year.

[0109] Carbon emissions by industry category The total carbon emissions from all industrial land within the target area are calculated as follows: The operational carbon emissions from plots within the target area that are "reserved" and designated for industrial use are aggregated and combined with the region's total industrial output value and industrial carbon emission intensity. Specifically, industrial carbon emission intensity is the carbon emissions per unit of industrial output value (unit: tons of CO2 / 10,000 yuan), ranging from 0.5 to 2.0 tons of CO2 / 10,000 yuan. Specific values ​​can be derived from the regional energy balance sheet and industrial energy consumption statistics.

[0110] Carbon emissions by transportation category The total carbon emissions generated by transportation within the target area are calculated based on the area's vehicle ownership, average annual mileage, and carbon emission factors for various vehicle types. The transportation carbon emission factor ranges from 0.15 to 0.35 kg CO2 / vehicle-kilometer, and specific values ​​can be obtained from the emission factor databases of national or local transportation departments.

[0111] Municipal category carbon emission values The total carbon emissions generated by the operation of municipal infrastructure (including water supply, sewage treatment, waste disposal, street lighting, etc.) within the target area are calculated based on the scale of municipal facilities and the carbon emission intensity per unit of service. The value of municipal carbon emission intensity ranges from 0.05 to 0.20 tons of CO2 per person per year, and the specific value can be derived from municipal utility operation statistics and regional power grid factors.

[0112] Carbon sink category Carbon absorption value The carbon sequestration coefficient is the total amount of carbon dioxide absorbed by ecological land such as parks, green spaces, and woodlands within the target area. It is calculated by summing the areas of plots within the target area that are "reserved" and classified as green space or ecological land, and multiplying this area by the carbon sequestration coefficient per unit area. The carbon sequestration coefficient per unit area represents the amount of carbon dioxide absorbed per square meter of ecological land per year, ranging from 0.5 to 2.0 kg CO2 / m²·year. Different vegetation types (trees, shrubs, grasslands, etc.) correspond to different coefficient values, and the specific values ​​are derived from forestry carbon sequestration monitoring data or regional ecological survey data.

[0113] Next, calculate the one-time carbon emissions. :

[0114]

[0115] in, This represents the total carbon emissions of the dismantling emission category in the baseline year for carbon peak projection. This represents the total carbon emissions of building-inherent emission categories in the baseline year for carbon peak projection. This represents the total carbon emissions of the renovation and construction emission categories in the carbon peak projection base year. All three total emissions are derived from the calculation results of step S6. For indicator functions, when the condition The value is 1 if the condition is true, and 0 otherwise. and Similarly, by introducing the aforementioned indicator function, one-time carbon emissions are only emitted in the user-specified year of demolition. New Year and the year of renovation The carbon emissions included in the assessment are zero in other years. One-off carbon emissions reflect the concentrated carbon emission impact of a construction event in a specific year.

[0116] Finally, the assessment criteria for carbon emissions The sum of operational carbon emissions and primary carbon emissions:

[0117]

[0118] Starting from the year following the initial year, the carbon emission series under the assessment criteria is traversed year by year. At that time, the previous year was judged. For the year of peak, the peak value was The emission values. If there is no decrease by the target year, it is marked as "not peaked".

[0119] Understandably, the carbon peak year prediction process, by integrating production rate curve interpolation, dynamic changes in electric vehicle penetration, aggregation of one-off carbon emission events, and annual emission reduction measures, can realistically simulate the long-term dynamic process of regional carbon emissions from initiation, development, stabilization, to peak, and automatically identify the peak year. It accurately reflects the aggregation effect of construction events such as demolition, new construction, and renovation on the timeline, making the peak prediction results more scientific and valuable for reference.

[0120] In a preferred embodiment of the present invention, the method further includes a real-time editing and dynamic updating step.

[0121] Understandably, real-time editing and dynamic updates enable the system to respond instantly to user interactions, allowing users to see changes in carbon emissions immediately by modifying land parcel data while viewing carbon emission calculation results.

[0122] The specific steps for real-time editing and dynamic updating are as follows:

[0123] In response to a user's operation to modify the status of a target plot, the carbon emission category activated for the target plot is first re-determined according to the mapping rules.

[0124] For example, in the "Urban Renewal" mode, if a user changes the status of a plot of land from "Reserved" to "Demolition", the system will switch the activation category from "Building Operation Emission Category" to "Demolition Emission Category" according to the mapping rules.

[0125] Then, the system only recalculates the carbon emission contribution of the target site and the carbon emission contribution of related sites affected by it, and updates the total carbon emissions of the region.

[0126] Specifically, the relevant land parcels include land parcels belonging to the same region as the target land parcel and land parcels with the same land use type as the target land parcel. The former needs to be updated due to regional summary statistics, while the latter needs to be updated due to changes in macro parameters related to the land use type (such as the total building area of ​​the land use type).

[0127] At the same time, the system performs a full map-wide update: updates the fill color of the target plot polygon on the map (mapped to the corresponding color level according to the new carbon emission contribution value), updates the emission values ​​in its pop-up window, and synchronously updates all relevant charts and key performance indicators in the interface.

[0128] In a preferred embodiment of the present invention, the method further includes a multi-scenario comparison step. The multi-scenario comparison is used to rapidly evaluate the effectiveness of different combinations of low-carbon measures within the same simulation scenario, and the specific method includes:

[0129] Users can create one or more comparison scenarios within the same simulation plan, and independently configure the following parameter adjustment values ​​for each comparison scenario: Residential Building Carbon Emission Coefficient (default 1), Public Building Carbon Emission Coefficient (default 1), Electric Vehicle Penetration Rate Increase / Decrease (percentage), Renewable Energy Proportion Increase / Decrease (percentage), and Green Building Rating (Basic, One-Star, Two-Star, Three-Star). The meanings of the parameter adjustment values ​​are as follows: The Residential Building Carbon Emission Coefficient is an adjustment coefficient for the operational intensity of residential buildings; a value less than 1 indicates a reduction in operational carbon emissions. The Public Building Carbon Emission Coefficient is an adjustment coefficient for the operational intensity of public buildings. The Electric Vehicle Penetration Rate Increase / Decrease is the increase or decrease in the electric vehicle penetration rate. The Renewable Energy Proportion Increase / Decrease is the increase or decrease in the proportion of renewable energy in the power structure. The Green Building Rating is the building's green certification level; the higher the level, the lower the Green Building Coefficient.

[0130] For example, users can create a "low-carbon scenario" (residential coefficient 0.90, public coefficient 0.92, electric vehicle +15%, renewable energy +10%, green building one-star) and an "enhanced low-carbon scenario" (residential coefficient 0.75, public coefficient 0.85, electric vehicle +30%, renewable energy +20%, green building two-star).

[0131] The system calculates the carbon emission contribution for each comparison scenario. Specifically, for each comparison scenario, the corresponding calculation parameters (actual grid factor, actual electric vehicle penetration rate, and residential / public building operation intensity) are adjusted, and the carbon emissions are recalculated using the calculation method in step S6. The calculation results for each comparison scenario are compared with the calculation results for the baseline scenario (all adjustments are 0) to generate the emission change for each scenario.

[0132] The emission changes are used to visualize the synergistic emission reduction effects of various low-carbon measures in stacked bar charts, enabling users to intuitively identify which combinations of measures have the best emission reduction benefits.

[0133] In a preferred embodiment of the present invention, the method further includes an uncertainty propagation step. The uncertainty propagation is used to quantify and transfer the inherent uncertainty of the input parameters to the final result, making the evaluation conclusion more scientific and rigorous. The specific method includes:

[0134] Users can set the uncertainty percentage for each carbon emission category through the system interface. (%), where the carbon emission categories include buildings (including operation, concealment, demolition and renovation construction), industry, transportation, municipal, and carbon sinks. For example, the user sets the uncertainty for buildings to 20%, industry to 30%, transportation to 25%, municipal to 30%, and carbon sinks to 30%.

[0135] Calculate the absolute uncertainty for each carbon emission category. :

[0136]

[0137] in, The contribution value of carbon emissions to this category, This represents the percentage of uncertainty set by the user for this category. For example, if the carbon emissions for the building category are 85,000 tons and the uncertainty is 20%, then the absolute uncertainty is... =8.5×20 / 100=17,000 tons.

[0138] Then, the total uncertainty is synthesized using the sum-of-squares (RSS) method. :

[0139]

[0140] Understandably, the principle behind this method is that the uncertainties of each category are independent, and the total uncertainty is the square root of the sum of the squares of the uncertainties of each category. For example, if the absolute uncertainties of each category are 1.7, 0.36, 0.375, 0.54, 0.15, and 0.24 million tons respectively, then the total uncertainty is... =1.72+0.362+0.3752+0.542+0.152+0.242≈18,900 tons.

[0141] Finally, confidence intervals for net carbon emissions are generated based on the total uncertainty:

[0142]

[0143] For example, if net carbon emissions are 123,000 tons / year and total uncertainty is 18,900 tons / year, then the confidence interval is [104,100, 141,900 tons / year].

[0144] Understandably, this invention, through a multi-scenario comparison step, supports the creation of multiple comparison scenarios within the same scheme and the independent configuration of parameter adjustment values ​​for each scenario, enabling rapid quantification of the synergistic emission reduction effects of different combinations of low-carbon measures. Simultaneously, through an uncertainty propagation step, the square root method is used to quantify the uncertainty of the input parameters and propagate it to the final result, providing a confidence interval for net carbon emissions, making the assessment conclusions more scientific and rigorous.

[0145] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A carbon emission extrapolation method based on dynamic boundary mapping, characterized in that, Includes the following steps: Obtain land parcel data for the target area, wherein the land parcel data includes at least the land parcel status; Receive the project development mode selected by the user; Based on the project development model, corresponding mapping rules are generated, which are used to determine the correspondence between the status of each plot and the carbon emission category; A three-dimensional dynamic boundary mapping matrix is ​​constructed, which has three dimensions: project development mode, land parcel status, and carbon emission category. Traverse each plot and query the three-dimensional dynamic boundary mapping matrix based on the current state of each plot to determine the activated carbon emission category of each plot; Based on the land parcel data and the activated carbon emission categories, the carbon emission contribution value of each parcel is calculated, and the total regional carbon emissions are aggregated.

2. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The land parcel status includes at least one of preservation, new construction, demolition, and renovation; the project development mode includes at least one of existing built-up area mode, integrated area development mode, urban renewal mode, and mixed development mode; the carbon emission category includes at least one of building operation emission category, building implicit emission category, demolition emission category, and renovation construction emission category; wherein, the building operation emission category is used to calculate the carbon emissions generated by the daily operation of existing buildings on the land parcel, the building implicit emission category is used to calculate the carbon emissions during the production and construction of new building materials, the demolition emission category is used to calculate the carbon emissions generated by building demolition construction, and the renovation construction emission category is used to calculate the carbon emissions generated by building renovation construction.

3. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 2, characterized in that, The specific method for generating corresponding mapping rules based on the project development model includes: When an existing built-up area mode is selected, only plots in the reserved state will be mapped to the building operation emissions category; When a comprehensive development model for a given area is selected, plots in the "reserved" category are mapped to building operation emission categories, and plots in the "newly constructed" category are mapped to building implicit emission categories. When the urban renewal mode is selected, plots in the "preservation" status are mapped to the building operation emission category, plots in the "demolition" status are mapped to the demolition emission category, and plots in the "renovation" status are mapped to the renovation construction emission category. When a mixed development model is selected, plots in the "Reserved" status are mapped to the building operation emission category, plots in the "New Construction" status are mapped to the building implicit emission category, plots in the "Demolition" status are mapped to the demolition emission category, and plots in the "Remodeling" status are mapped to the remodeling construction emission category.

4. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The specific method for traversing each land parcel and querying the three-dimensional dynamic boundary mapping matrix based on the current state of each land parcel to determine the activated carbon emission category of each land parcel includes: Read the current status of each plot one by one and obtain the plot identifier of each plot; Using the project development mode and the current land parcel status as indexes, query the corresponding list of activation categories in the three-dimensional dynamic boundary mapping matrix; The list of activated categories is used as the set of categories for the land parcel to participate in carbon emission calculation. The list of activated categories contains all the carbon emission category names that the land parcel needs to participate in carbon emission calculation under the current project development mode and the current land parcel status.

5. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The specific method for calculating the carbon emission contribution value of each plot and aggregating it to obtain the total regional carbon emissions based on the plot data and activated carbon emission categories includes: for each plot, calling the calculation function corresponding to each activated carbon emission category of the plot, calculating the carbon emission contribution value of each category based on the land use type, area and plot ratio in the plot data; and adding the carbon emission contribution values ​​of each plot under each category to obtain the total regional carbon emissions.

6. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The method further includes: in response to a user's scheme creation request, generating an independent simulation scheme, wherein the simulation scheme saves the selected project development mode, land parcel data modification records, and the total carbon emissions of the region; the land parcel data modification records include a historical record of each change made by the user to the land parcel status, land use type, and area attributes; and different simulation schemes are isolated from each other.

7. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The method also includes a step for estimating the year of carbon peak: Set the start year and target year, and receive the annual production rate curve, electric vehicle penetration rate change parameters, demolition year, new construction year and renovation year; Using the total carbon emissions in the region as a benchmark, operational carbon emissions and primary carbon emissions are calculated year by year and then superimposed to obtain the assessment carbon emission sequence. The annual production rate curve is calculated by linear interpolation for each year. The carbon emission in the operational caliber is equal to the sum of the emission categories in the operational caliber multiplied by the production rate and minus the emission reduction amount. The primary carbon emission includes demolition emissions included in the demolition year, implicit emissions included in the new construction year, and renovation construction emissions included in the renovation year. When the carbon emission sequence under the aforementioned assessment criteria first shows a decline, the previous year is determined to be the peak year.

8. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The method further includes: in response to a user's operation to modify the status of a target plot, re-determining the activated carbon emission category of the target plot according to the mapping rules; recalculating the carbon emission contribution value of the target plot and the carbon emission contribution values ​​of related plots affected by it, and updating the total carbon emissions of the region.

9. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The method further includes: creating one or more comparative scenarios within the same simulation scheme, and independently configuring parameter adjustment values ​​for each comparative scenario; the parameter adjustment values ​​include the carbon emission coefficient of residential buildings, the carbon emission coefficient of public buildings, the increase or decrease in electric vehicle penetration rate, the increase or decrease in the proportion of renewable energy, and the green building level; calculating the carbon emission contribution value of each comparative scenario, comparing the calculation results of each comparative scenario with the calculation results of the baseline scenario, and generating the emission change of each scenario.

10. The carbon emission extrapolation method based on dynamic boundary mapping according to claim 1, characterized in that, The method further includes an uncertainty propagation step: receiving the uncertainty percentage set by the user for each carbon emission category; calculating the absolute uncertainty of each carbon emission category, wherein the absolute uncertainty is equal to the absolute value of the carbon emission contribution of that carbon emission category multiplied by its uncertainty percentage; synthesizing the total uncertainty using the square root method; and generating a confidence interval for net carbon emissions based on the total uncertainty.

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