Accounting method and system for carbon emissions of highway in seasonal frozen region throughout life cycle

Abstract

The present disclosure relates to a seasonal frozen region highway full life cycle carbon emission accounting method and system, relating to the field of traffic data processing, comprising: constructing a localized three-level hash mapping repository to retrieve carbon emission factors corresponding to pre-processed multi-source engineering data; dividing the highway full life cycle into material production stage, material transportation stage, road construction stage and operation and maintenance stage; considering material flow transfer overlap and seasonal frozen maintenance carbon emission increment to calculate highway full life cycle carbon emission; using recursive traversal algorithm to divide highway engineering into multiple types of unit engineering, calculating total carbon emission of highway engineering life cycle and carbon emission intensity per unit of unit engineering per unit of mileage; multi-thread parallel random sampling of all high sensitivity parameters of seasonal frozen highway, calculating carbon emission of each sample group in the full life cycle of the highway, calculating the contribution proportion of each high sensitivity parameter carbon emission, marking high carbon emission units in the highway; generating a carbon assessment report. The present disclosure improves the accounting efficiency and accuracy.

Description

Technical Field

[0001] This disclosure relates to the field of traffic data processing, and in particular to a method and system for calculating carbon emissions throughout the entire life cycle of highways in seasonally frozen areas. Background Technology

[0002] The full life-cycle carbon emission accounting of highways in seasonally frozen areas plays an irreplaceable supporting role in the low-carbon transformation of regional transportation and the implementation of industry dual-carbon goals.

[0003] Currently, China's highway carbon emission accounting mainly relies on the traditional LCA (Life Cycle Assessment), which adopts an independent, phased, manual calculation model or uses general-purpose commercial LCA software for calculation.

[0004] Manual Excel segmented calculations calculate carbon emissions for material production, transportation, construction, and maintenance separately, using nationally standardized building materials and power grid emission factors, without cold-region correction, manually matching project quantities, and relying on manual data aggregation; manual calculation of carbon emissions for the entire life cycle of highways in seasonally frozen areas is extremely inefficient.

[0005] General-purpose commercial LCA software (SimaPro, eBalance) is more efficient than manual segmented calculations using Excel and can complete basic carbon emission calculations. However, if used directly for roads in seasonally frozen areas, it may result in inaccurate calculations.

[0006] Therefore, it is necessary to design a method and system that balances efficiency and accuracy for the full life-cycle carbon emission accounting of highways in seasonally frozen areas. Summary of the Invention

[0007] Therefore, it is necessary to provide a method and system for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle, addressing the issue that the efficiency and accuracy of carbon emission calculations cannot be balanced.

[0008] To solve the above problems, the present disclosure adopts the following technical solution: Firstly, this disclosure provides a method for calculating carbon emissions throughout the entire life cycle of highways in seasonally frozen areas, including: A localized carbon emission factor library for the frozen zone is obtained and a three-level hash mapping repository is constructed based on the mapping relationship, which consists of a regional code hash layer, a building material category hash layer, and a sub-building material hash layer. The sub-building material hash layer stores the localized carbon emission factor entity data for the frozen zone. Acquire multi-source engineering data, including highway engineering bill of quantities and highway engineering machinery shift quotas, and preprocess the multi-source engineering data; The carbon emission factor corresponding to the preprocessed multi-source engineering data was retrieved using a three-level hash mapping repository. The entire life cycle of a highway is divided into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. Based on the carbon emission factors corresponding to the pre-processed multi-source engineering data, and under the premise of eliminating material flow overlap, the carbon emission increment of seasonal freezing maintenance is considered to calculate the carbon emissions of the entire life cycle of the highway. A recursive traversal algorithm is used to divide highway engineering into multiple types of unit projects; a two-dimensional matrix of unit project-carbon emissions is constructed, and the total carbon emissions of highway engineering over its life cycle and the carbon emission intensity per unit mileage of unit projects are calculated based on the matrix. Multiple high-sensitivity parameters for seasonally frozen highways were selected; based on the carbon emission factors of preprocessed multi-source engineering data, multi-threaded parallel random sampling was performed on all high-sensitivity parameters, with one thread corresponding to each type of high-sensitivity parameter, and a sample group was obtained after random sampling of each type of high-sensitivity parameter. The carbon emission amount of each sample group in the entire life cycle of the highway was calculated; the carbon emission contribution ratio of each high-sensitivity parameter was statistically analyzed and sorted in descending order, and high-carbon emission units in the highway were automatically marked. Generate and output carbon assessment reports, which include information on carbon emission intensity and emission reduction measures for various types of projects.

[0009] In a preferred embodiment, the carbon emission increment for seasonal freezing maintenance is the carbon emission increment from winter snow removal machinery energy consumption, year-round tunnel heating, freeze-thaw repair and overhaul, and de-icing agent production and transportation.

[0010] In a preferred embodiment, the formula for calculating the carbon emissions over the entire life cycle of the highway is as follows: ; in, This refers to the carbon emissions throughout the entire life cycle of a highway. This refers to carbon emissions during the material production stage. To eliminate carbon emissions from the material transportation stage after material flow overlaps, This refers to carbon emissions during the road construction phase. Carbon emissions during the operation and maintenance phase. This refers to the increased carbon emissions from seasonal freezing maintenance, namely, the increased energy consumption of snow removal machinery in winter, year-round heating of tunnels, freeze-thaw repair and major overhauls, and the production and transportation of de-icing agents.

[0011] In a preferred embodiment, the various types of unit projects include roadbed, pavement, bridge and culvert, tunnel, intersection, ancillary facilities, and temporary works; the unit projects include three types of carbon emissions, namely material emissions, transportation emissions, and machinery emissions.

[0012] In a preferred embodiment, the formula for calculating the total carbon emissions over the life cycle of the highway project is as follows: in: The total carbon emissions from highway engineering projects; For the first Total carbon emissions per unit of project For the first Material emissions for similar unit projects; For the first Transportation emissions of similar unit projects; For the first Mechanical emissions of similar unit projects; The formula for calculating the carbon emission intensity per unit mileage of the project is as follows: in: For the first Carbon emission intensity per unit mileage of similar unit projects For the first The total length of the route for a unit project of this type.

[0013] In a preferred embodiment, the selected highly sensitive parameters include cement consumption, steel consumption, average material transportation distance, fuel consumption of construction machinery, and winter heating duration of tunnels.

[0014] In a preferred embodiment, the method further includes the step of outputting a sensitivity analysis list, the sensitivity analysis list including the name of the high carbon emission unit and the carbon emissions of all high-sensitivity parameters for each high carbon emission unit.

[0015] In a preferred embodiment, the report also includes information on the proportion of carbon emission contribution of highly sensitive parameters and information on high carbon emission units in highways.

[0016] In a preferred embodiment, the step of generating the carbon assessment report includes: automatically matching route optimization, low-carbon building materials, recycled pavement, and photovoltaic tunnel emission reduction methods based on high carbon emission units in highways and combined with the emission reduction knowledge base for seasonally frozen areas, to generate emission reduction measures.

[0017] Secondly, this disclosure provides a life-cycle carbon emission accounting system for highways in seasonally frozen areas, including: The module is used to obtain a localized carbon emission factor library for the frozen zone and construct a three-level hash mapping repository based on it, with the mapping relationship being a regional code hash layer, a building material category hash layer, and a subdivided building material hash layer. The subdivided building material hash layer stores the localized carbon emission factor entity data for the frozen zone. The acquisition module is used to acquire multi-source engineering data of highways in seasonally frozen areas to be subject to carbon emission accounting. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota of shifts for highway engineering machinery. The preprocessing module is used to preprocess multi-source engineering data; The retrieval module is used to retrieve the carbon emission factor corresponding to the preprocessed multi-source engineering data using a three-level hash mapping repository. The entire life cycle of a highway is divided into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. Based on the carbon emission factors corresponding to the pre-processed multi-source engineering data, and under the premise of eliminating material flow overlap, the carbon emission increment of seasonal freezing maintenance is considered to calculate the carbon emissions of the entire life cycle of the highway. The first calculation module is used to divide highway engineering into multiple types of unit projects using a recursive traversal algorithm; it is used to construct a two-dimensional matrix of unit project-carbon emissions, and to calculate the total carbon emissions of highway engineering over its life cycle and the carbon emission intensity per unit mileage of unit project based on the matrix. The selection module is used to select various highly sensitive parameters for seasonally frozen roads; The sampling module is used to perform multi-threaded parallel random sampling of all high-sensitivity parameters based on the carbon emission factors of preprocessed multi-source engineering data. Each type of high-sensitivity parameter corresponds to one thread, and each type of high-sensitivity parameter is randomly sampled to obtain a sample group. The second calculation module is used to calculate the carbon emissions of each sample group throughout the entire life cycle of the highway. The statistical labeling module is used to calculate the carbon emission contribution ratio of each highly sensitive parameter and sort them in descending order, automatically labeling high carbon emission units in highways. The report generation module is used to generate and output carbon assessment reports, which include carbon emission intensity information and emission reduction measures for various types of projects.

[0018] The aforementioned method and system for calculating carbon emissions throughout the entire life cycle of highways in seasonally frozen areas constructs a localized three-level hash mapping repository for seasonally frozen regions. This repository is used to retrieve carbon emission factors, divide the highway's entire life cycle, and calculate the total carbon emissions throughout the highway's life cycle, taking into account overlapping material flows and the incremental carbon emissions from seasonal maintenance. A recursive traversal algorithm divides highway projects into multiple types of unit projects. Multi-threaded parallel random sampling and calculation of carbon emissions throughout the highway's life cycle are performed on all highly sensitive parameters to identify high-carbon emission units and ultimately generate a carbon assessment report. This design balances accuracy and efficiency in carbon accounting for highways in seasonally frozen areas. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a method in one embodiment of the present disclosure; Figure 2 A schematic diagram of the emission factors stored in the three-level hash map repository of this disclosure; Figure 3 This is a two-dimensional matrix diagram of carbon emissions per unit project disclosed in this publication; Figure 4A bar chart showing the total carbon emissions of seven types of unit projects; Figure 5 A schematic diagram illustrating the carbon emission composition across three dimensions for seven types of unit projects; Figure 6 A radar chart showing carbon emission intensity per unit mileage; Figure 7 This is a diagram of a multi-threaded parallel Monte Carlo sensitivity analysis architecture. Detailed Implementation

[0020] The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and preferred embodiments.

[0021] See Figure 1 This embodiment provides a method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle, including: A localized carbon emission factor library for the frozen zone is obtained and a three-level hash mapping repository is constructed based on the mapping relationship, which consists of a regional code hash layer, a building material category hash layer, and a sub-building material hash layer. The sub-building material hash layer stores the localized carbon emission factor entity data for the frozen zone. Obtain multi-source engineering data for highways in seasonally frozen areas that are to be carbon emission accounted for. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota for highway engineering machinery shifts. Preprocess the multi-source engineering data. The carbon emission factor corresponding to the preprocessed multi-source engineering data was retrieved using a three-level hash mapping repository. The entire life cycle of a highway is divided into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. Based on the carbon emission factors corresponding to the pre-processed multi-source engineering data, and under the premise of eliminating material flow overlap, the carbon emission increment of seasonal freezing maintenance is considered to calculate the carbon emissions of the entire life cycle of the highway. A recursive traversal algorithm is used to divide highway engineering into multiple types of unit projects; a two-dimensional matrix of unit project-carbon emissions is constructed, and the total carbon emissions of highway engineering over its life cycle and the carbon emission intensity per unit mileage of unit projects are calculated based on the matrix. Multiple high-sensitivity parameters for seasonally frozen highways were selected; based on the carbon emission factors of preprocessed multi-source engineering data, multi-threaded parallel random sampling was performed on all high-sensitivity parameters, with one thread corresponding to each type of high-sensitivity parameter, and a sample group was obtained after random sampling of each type of high-sensitivity parameter. The carbon emission amount of each sample group in the entire life cycle of the highway was calculated; the carbon emission contribution ratio of each high-sensitivity parameter was statistically analyzed and sorted in descending order, and high-carbon emission units in the highway were automatically marked. Generate and output carbon assessment reports, which include information on carbon emission intensity and emission reduction measures for various types of projects.

[0022] The method of this disclosure is described in detail below, and the method includes: Step 1: Obtain the localized carbon emission factor database and the regional coding location database for the seasonally frozen area, and construct a three-level hash mapping repository based on the mapping relationship, which consists of a regional coding hash layer, a building material category hash layer, and a subdivided building material hash layer.

[0023] First, the regional database is located based on the geographic code. Then, the location is determined step by step according to the building material category and sub-type of building material, and finally the corresponding carbon emission factor is obtained.

[0024] A three-level hash mapping repository is pre-built: a regional coding hash layer → a building material category hash layer → a sub-building material hash layer, which maps and stores carbon emission factors specific to the frozen zone; The first layer of the three-level hash mapping repository is the regional code hash layer. The regional code hash layer uses the project's regional code as the hash key to map the codes of different administrative regions / permafrost zones in the seasonally frozen area to the entry point of the corresponding building material category hash table, quickly locating the exclusive factor set of the target area.

[0025] The second layer of the three-level hash mapping repository is the building materials category hash layer. Under the regional coding hash layer, the names of building materials categories such as cement, sand and gravel, and asphalt are used as hash keys to map to the entry points of the corresponding sub-building materials hash layers, thus completing the rapid filtering of the category range.

[0026] The third layer of the three-level hash mapping repository is the subdivided building material hash layer. Under the building material category hash layer, the name of the subdivided building material with specific specifications is used as the hash key to directly map and store the exclusive carbon emission factor value of the building material in the corresponding frozen zone. It is the only layer that stores the localized carbon emission factor entity data of the frozen zone.

[0027] In this embodiment, building materials are categorized into major categories based on their structure and material function. Further subcategories of building materials are also categorized based on their structure and material function. The hierarchical dimension of major building material categories is greater than that of subcategories. The hierarchical priority and coverage of major building material categories in the classification system are higher than those of subcategories. The classification logic is top-down: major building material categories → subcategories.

[0028] Based on the detailed building material hash layer, it is possible to distinguish the exclusive carbon emission coefficients of four special materials: conventional building materials, cold-region modified asphalt, antifreeze admixtures, and snow melting agents.

[0029] The term "conventional building materials" refers to common engineering building materials such as cement, ordinary sand and gravel, and ordinary steel bars. These directly adopt nationally or regionally applicable carbon emission factors without additional adjustments. The term "cold-region modified asphalt" specifically refers to modified asphalt suitable for low-temperature construction in seasonally frozen regions. Its emission coefficient differs from that of ordinary hot-mix asphalt, and its corresponding low-carbon emission value needs to be calculated separately. The term "antifreeze admixture" refers to antifreeze building material additives specifically designed for winter construction of highways in seasonally frozen regions. The term "snow-melting agent" is a special material essential for winter operation and maintenance of highways in seasonally frozen regions. Its carbon emissions from the entire process of production, transportation, and application need to be calculated separately, differing from the emission coefficients of ordinary road maintenance materials.

[0030] In this embodiment, a three-level hash mapping database is established, using regional code, building material category, and subdivided building material as indexes to enable fast querying of emission factors.

[0031] Let the geographical code of the project location be R, the major category of building materials be C, and the sub-category of building materials be S, then the emission factor retrieval model is expressed as: EF=H(R,C,S); Where: EF represents the carbon emission factor (kgCO2 / kg) corresponding to the building material; H(·) represents the three-level hash mapping function; R represents the regional code; C represents the major category of building materials (such as cement, steel, asphalt, etc.); S represents the sub-category of building materials (such as HRB400 steel bars, SBS modified asphalt, etc.).

[0032] The query process is as follows: R→C→S→EF, which means first locating the regional database based on the regional code, then locating it step by step according to the major categories and sub-categories of building materials, and finally obtaining the corresponding carbon emission factor.

[0033] For special materials from seasonally frozen regions, a classification mapping method is used for retrieval: in: Current building materials; Conventional building materials; Cold-region modified asphalt; Antifreeze additives; Snow melting agent; Carbon emission factor of conventional building materials (kgCO2 / kg); Carbon emission factor of modified asphalt in cold regions (kgCO2 / kg); Carbon emission factor of antifreeze additives (kgCO2 / kg); Carbon emission factor of snow melting agent (kgCO2 / kg).

[0034] The hash function takes the project's regional code and material name as input and directly indexes the corresponding emission factor. The average time complexity of hash table lookup is O(1), requiring only two hash calculations to directly locate the target emission factor without scanning data row by row. This hash indexing method replaces the traditional full table traversal of the database, significantly reducing time complexity. The three-level hash mapping can directly locate the target emission factor, improving retrieval efficiency, and is especially suitable for the rapid query of carbon emission factors of a large number of building materials in frozen areas.

[0035] Figure 2 To represent a portion of the information stored in the three-level hash map repository using a bar chart. Figure 2 The figure shows the carbon emission factors of blue (red) bricks, polyvinyl chloride plastics, silicate cement, low-carbon cement, HRB400 (hot-rolled ribbed steel bars), HRB500 (hot-rolled ribbed steel bars), iron, asphalt, SBS modified asphalt, NaCl, and CaCl2.

[0036] Step 2: Obtain multi-source engineering data for highways in seasonally frozen areas to be carbon emission accounted for. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota for highway engineering machinery shifts. Preprocess the multi-source data; use a three-level hash mapping repository to retrieve the carbon emission factor corresponding to the preprocessed multi-source engineering data.

[0037] Import two basic data sources: bill of quantities for highway engineering projects and standard operating rates for highway engineering machinery. Further, material ledgers (Excel) are also included. Understandably, multi-source heterogeneous files in PDF format may also be included.

[0038] The preprocessing includes data cleaning, data completion, and information binding. Data cleaning includes, but is not limited to: standardizing the coding of building materials such as steel, cement, and sand; standardizing the model coding of machinery such as excavators, air compressors, and dump trucks; and standardizing the unique IDs for roadbed / pavement / bridge / culvert engineering levels. Data completion includes, but is not limited to: automatically completing missing material usage and shift data using interpolation algorithms, with the interpolation algorithms based on data from the same land area for seasonally frozen roads (a shorthand for roads built in seasonally frozen soil regions). Information binding includes, but is not limited to: reading the project's geographical location tag and automatically binding the regional power grid and a complete set of local building material carbon emission parameters based on the project's geographical location tag.

[0039] Step 3, Four-stage layered coupling deduplication matrix calculation: The entire life cycle of a highway is divided into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. Under the premise of eliminating the overlap of material flow and considering the carbon emission increment of seasonal freezing maintenance, the carbon emissions of the entire life cycle of the highway are calculated.

[0040] The term "highway life cycle" as used in this article refers to the narrow definition of the highway life cycle.

[0041] The entire life cycle of a highway is divided into four stages (i.e., four layers): material production, material transportation, road construction, and operation and maintenance. It incorporates a material flow weight reduction operator and a seasonal freezing maintenance carbon emission increment compensation operator. 1) Parallel computation of the matrix for the material production stage: , This indicates the code for the major category of building materials. This indicates the total number of categories in the building materials category. Building materials category Total consumption, Building materials categories obtained by hash retrieval Carbon emission factors of materials in frozen zones This refers to the carbon emissions during the material production stage.

[0042] 2) Material transportation stage coupling weight reduction correction: Automatically identify the multi-level transfer links of building materials from "raw material plant - mixing plant - construction site", merge the total transportation mileage of the same material, and eliminate the carbon emissions of transportation that are repeatedly superimposed in segments; 3) Calculation of mechanical energy consumption matrix during road construction: Calculate the carbon emissions generated by diesel and electricity consumption in batches according to machine shifts, and distinguish the statistics of high energy-consuming equipment such as tunnel air compressors, roadbed dump trucks, and bridge drilling rigs. 4) Calculation of incremental compensation for seasonal freezing maintenance: The calculation includes four categories of specific carbon emission increments: increased energy consumption of winter snow removal machinery, year-round tunnel heating, freeze-thaw repair and major overhaul, and production and transportation of de-icing agents. ; 5) Full-cycle coupled carbon emissions: The deduplication operator automatically deducts the amount of repeated material transfers that are repeatedly calculated. This refers to the carbon emissions throughout the entire life cycle of a highway. This refers to carbon emissions during the material production stage. To eliminate carbon emissions from the material transportation stage after material flow overlaps, This refers to carbon emissions during the road construction phase. To eliminate carbon emissions during the operation and maintenance phase after material flow overlap. This refers to the increased carbon emissions from seasonal freezing maintenance, namely, the increased energy consumption of snow removal machinery in winter, year-round heating of tunnels, freeze-thaw repair and major overhauls, and the production and transportation of de-icing agents.

[0043] Step 4: Using a recursive traversal algorithm, highway engineering projects are divided into multiple types of unit projects; a two-dimensional matrix of unit project-carbon emissions is constructed, where rows of the two-dimensional matrix correspond to a type of unit project and columns correspond to a type of carbon emissions of the unit project, or columns correspond to a type of unit project and rows correspond to a type of carbon emissions of the unit project. Based on the two-dimensional matrix, the total carbon emissions of the highway engineering project over its life cycle and the carbon emission intensity per unit mileage of the unit project are calculated.

[0044] A recursive traversal algorithm is used to automatically split the project into seven types of unit projects: roadbed engineering, pavement engineering, bridge and culvert engineering, tunnel engineering, intersection engineering, ancillary facilities, and temporary engineering. Using the attributes of the engineering entity as the splitting dimension, the project is classified according to the different professional attributes of the seven types of projects, and engineering entities with completely different functions and construction processes are automatically assigned to the corresponding unit project category.

[0045] The recursive traversal algorithm uses the entire project data as the root node and recursively scans all project sub-units layer by layer downwards, matching the above-mentioned partitioning rules. When encountering independent large structures such as bridges and tunnels, they are automatically separated from the main project and marked as independent unit projects. The recursion stops when the smallest indivisible project unit is reached, completing all classification and marking, and outputting the complete partitioning result.

[0046] That is, if highway engineering can be divided into 7 types of unit projects, then the set of unit projects is represented as: in: Roadbed engineering; Road surface engineering; Bridge and culvert engineering; Tunnel engineering; Cross-disciplinary engineering; Ancillary facilities; Temporary project.

[0047] The carbon emissions of each unit project are calculated sequentially using a recursive traversal method. The recursive relationship can be expressed as follows: in: Unit project category number; : No. Total carbon emissions (kgCO2) calculated cumulatively from the start of each unit project. : No. Carbon emissions (kgCO2) of a unit project; For the For a type of unit project, its quantity is recorded as: ; The unit project includes three categories of carbon emissions: material emissions, transportation emissions, and machinery emissions.

[0048] The material emissions are ; in: Carbon emissions from materials (kgCO2); : No. Unit project quantity (m) 3 (e.g., t, etc.) Material emission factor (kgCO2 / unit project quantity).

[0049] The transportation emissions are ; in: Carbon emissions from transportation (kgCO2); Transportation emission factor (kgCO2 / unit of project volume).

[0050] The mechanical emissions are in: Carbon emissions from mechanical construction (kgCO2); Mechanical emission factor (kgCO2 / unit engineering volume).

[0051] No. The total carbon emissions per unit project are: ; in: : No. Total carbon emissions per unit of project (kgCO2); : No. Material emissions for similar unit projects; : No. Transportation emissions of similar unit projects; : No. Mechanical emissions of a type of unit project.

[0052] A two-dimensional carbon emission matrix is ​​constructed for each unit project, organizing the carbon emissions of the seven types of unit projects into a two-dimensional matrix: In this matrix, each row represents a type of unit project; the first column represents material emissions (carbon emissions from materials), the second column represents transportation emissions (carbon emissions from transportation), and the third column represents machinery emissions (carbon emissions from machinery).

[0053] In one embodiment, a two-dimensional unit project-carbon emission matrix is ​​generated: the rows of the matrix are the various sub-projects, and the columns of the matrix are three dimensions: material emissions, transportation emissions, and machinery emissions. The computer solves the total carbon emissions and carbon emission intensity per unit mileage for each sub-project in parallel batches.

[0054] For calculating carbon emission intensity per unit mileage, we can set the first... The total route length of the unit project is Then the first The carbon emission intensity per unit mileage of a project is: in: : No. Carbon emission intensity per unit mileage of a type of unit project (kgCO2 / km). : No. Total carbon emissions (kgCO2) of a unit project; : No. Total route length (km) for a given type of unit project.

[0055] The total carbon emissions over the entire lifecycle of the highway project are: in: Total carbon emissions from highway engineering projects (kgCO2); : No. Total carbon emissions per unit of project.

[0056] Figure 3 This is a two-dimensional matrix of unit project-carbon emissions obtained in a specific embodiment. Figure 4 A bar chart showing the total carbon emissions of seven types of unit projects. Figure 5 This is a schematic diagram showing the carbon emission composition of seven types of unit projects across three dimensions. Figure 6 This is a radar chart of carbon emission intensity per unit mileage. The numbers 200, 400, 600, and 800 in the chart represent radial scale values, specifically referring to carbon emission intensity per unit mileage.

[0057] Step 5: Select multiple high-sensitivity parameters for seasonally frozen highways; based on the carbon emission factors of preprocessed multi-source engineering data, perform multi-threaded parallel random sampling on all high-sensitivity parameters, with one thread corresponding to each type of high-sensitivity parameter, and obtain a corresponding sample group for each type of high-sensitivity parameter after random sampling, calculate the carbon emission of each sample group throughout the highway's life cycle; statistically analyze the carbon emission contribution ratio of each high-sensitivity parameter and sort them in descending order, and automatically mark high-carbon emission units in the highway according to the carbon emission contribution ranking results of the high-sensitivity parameters.

[0058] For the comparison between seasonally frozen roads and non-seasonally frozen roads, parameters with large differences in carbon emissions can be selected. For example, parameters with large differences in carbon emissions can be sorted in descending order, and the parameters with the largest differences in carbon emissions can be selected as highly sensitive parameters, or parameters with large differences in carbon emissions can be selected.

[0059] In this embodiment, five types of highly sensitive parameters for seasonally frozen highways were selected: cement consumption, steel consumption, average material transportation distance, fuel consumption of construction machinery, and winter heating duration of tunnels. Enable multi-threaded parallel random sampling and batch calculate the carbon emissions of each sample group over the entire cycle. The system automatically calculates the carbon emission contribution ratio of each parameter and sorts them in descending order, automatically marks high-carbon emission units such as bridges, culverts, and tunnels (key high-carbon emission control units), and outputs a sensitivity analysis list.

[0060] In the full life-cycle carbon emission accounting of highways in seasonally frozen areas, engineering units with emission intensity far exceeding the average level of the entire route are identified as high-carbon emission units, which serve as the core target for subsequent carbon reduction and control. This is the core premise for targeted carbon reduction of seasonally frozen highways.

[0061] In one specific embodiment, the sensitivity analysis list includes the name of the high-carbon emission unit and the carbon emissions of all highly sensitive parameters for each high-carbon emission unit.

[0062] In another specific embodiment, the sensitivity analysis list includes basic attribute parameters of high-emission units (basic engineering attributes and material parameters specific to the frozen region), material-side sensitivity factors (fluctuation range of carbon emission factors of core high-carbon materials such as cement, steel bars, and antifreeze asphalt), energy and construction-side sensitivity factors (fluctuation range of fuel and electricity consumption intensity of construction machinery in the frozen environment; impact of energy consumption changes of special construction processes in cold regions on emissions), and life-cycle operation and maintenance-side sensitivity factors (the impact of changes in the frequency of frost damage repair and maintenance energy consumption of bridges, culverts, and tunnels in the frozen region; the impact of energy consumption fluctuations of ventilation and lighting systems during tunnel operation on long-term total emissions).

[0063] Step 5 describes a multi-threaded parallel Monte Carlo sensitivity solution method. For the multi-threaded parallel Monte Carlo sensitivity analysis architecture, please refer to [link to relevant documentation]. Figure 7 ,include: Highly sensitive parameter input: As the starting node of the process, it completes the definition, value range configuration and initial data import of all highly sensitive parameters to be analyzed; Main task scheduler controller: It is the core scheduling hub of the entire parallel architecture. It is responsible for splitting the total computing task into multiple independent subtasks, distributing them to different sub-threads for execution, and coordinating thread resource allocation and task synchronization. Multi-threaded parallel simulation: A parallel computing cluster is formed by sub-thread 1, sub-thread 2, up to sub-thread N. Each thread independently completes the simulation calculation of the randomly sampled sample assigned to it, without blocking each other, which greatly reduces the overall computing time. Results aggregation and contribution ranking: Collect simulation calculation results returned by all sub-threads, complete data summary and verification, automatically calculate the contribution ratio of each parameter and sort them from high to low values; Sensitivity Report and High-Carbon Unit Marking: As the final output node of this process, a complete sensitivity analysis report is generated, and key control units with high carbon emissions are automatically identified and marked, completing the closed loop of the entire process analysis.

[0064] Compared to traditional single-threaded serial Monte Carlo calculations, this architecture linearly improves computational speed, with the efficiency advantage becoming more pronounced as the sample size increases. It is well-suited for complex sensitivity analysis scenarios involving multiple parameters and large sample sizes, such as carbon emissions from seasonally frozen roads, and can quickly output reliable quantitative analysis results.

[0065] Step 6: Generate and output a carbon assessment report. The report includes carbon emission intensity information for various unit projects (which can be presented in the form of a comparison chart), carbon emission proportion information for each stage of the highway's entire life cycle (showing the percentage of carbon emissions in each of the four stages of material production, material transportation, road construction, and operation and maintenance to the total carbon emissions of the highway's entire life cycle, for example, presented in the form of a bar chart or a pie chart), carbon emission contribution proportion information for highly sensitive parameters (which can be presented in a bar chart), information on high-carbon emission units in the highway (including the names of high-carbon emission units in the highway), and emission reduction measures.

[0066] Understandably, the carbon assessment report is automatically generated, meaning the information in the report is obtained through automatic organization and drawing.

[0067] Emission reduction measures are generated by combining the knowledge base on emission reduction in seasonally frozen areas. Specifically, emission reduction measures are generated based on high carbon emission units in highways and the knowledge base on emission reduction in seasonally frozen areas.

[0068] It automatically matches differentiated emission reduction measures such as route optimization, low-carbon building materials, recycled pavement, and photovoltaic tunnel emission reduction methods, generates emission reduction measures, and exports a Word / PDF carbon accounting report that complies with the Ministry of Transport's green highway review standards.

[0069] Specifically, it can automatically generate and present a graph of the carbon emission contribution percentage of each high-carbon emission unit as a highly sensitive parameter in the report.

[0070] This disclosure also provides a life-cycle carbon emission accounting system for highways in seasonally frozen areas, including: The module is used to obtain a localized carbon emission factor library for the frozen zone and construct a three-level hash mapping repository based on it, with the mapping relationship being a regional code hash layer, a building material category hash layer, and a subdivided building material hash layer. The subdivided building material hash layer stores the localized carbon emission factor entity data for the frozen zone. The acquisition module is used to acquire multi-source engineering data of highways in seasonally frozen areas to be subject to carbon emission accounting. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota of shifts for highway engineering machinery. The preprocessing module is used to preprocess multi-source engineering data; The retrieval module is used to retrieve the carbon emission factor corresponding to the preprocessed multi-source engineering data using a three-level hash mapping repository. The module is used to divide the entire life cycle of a highway into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. The first calculation module is used to calculate the carbon emissions of the highway throughout its entire life cycle based on the carbon emission factors corresponding to the preprocessed multi-source engineering data, while eliminating the overlap of material flow and taking into account the carbon emission increment of seasonal freezing maintenance. The second calculation module is used to divide highway engineering into multiple types of unit projects using a recursive traversal algorithm; it is used to construct a two-dimensional matrix of unit project-carbon emissions, and to calculate the total carbon emissions of highway engineering over its life cycle and the carbon emission intensity per unit mileage of unit project based on the matrix. The selection module is used to select various highly sensitive parameters for seasonally frozen roads; The sampling module is used to perform multi-threaded parallel random sampling of all high-sensitivity parameters based on the carbon emission factors of preprocessed multi-source engineering data. Each type of high-sensitivity parameter corresponds to one thread, and each type of high-sensitivity parameter is randomly sampled to obtain a sample group. The third calculation module is used to calculate the carbon emissions of each sample group throughout the entire life cycle of the highway. The statistical labeling module is used to calculate the carbon emission contribution ratio of each highly sensitive parameter and sort them in descending order, automatically labeling high carbon emission units in highways. The report generation module is used to generate and output carbon assessment reports, which include carbon emission intensity information and emission reduction measures for various types of projects.

[0071] An electronic device can be implemented according to the method of this disclosure, the electronic device comprising: a memory; one or more processors; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for executing the life cycle carbon emission accounting method for seasonally frozen roads according to any of the above embodiments.

[0072] This disclosure also provides a computer-readable storage medium including instructions that, when executed on a computer, cause the computer to perform the steps of the life-cycle carbon emission accounting method for seasonally frozen highways described in any of the above embodiments.

[0073] That is, a computer program is stored in a computer-readable storage medium, and when the program is executed by a processor, it implements all the steps of the above steps 1 to 6 for the full life cycle carbon emission accounting method of highways in seasonally frozen areas.

[0074] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0075] Memory can include various types of storage units, such as USB flash drives, hard drives, server storage, cloud storage, and embedded software chips. It can be system memory, read-only memory (ROM), and permanent storage devices. Furthermore, memory can include any combination of computer-readable storage media, such as semiconductor memory chips, disks, and optical discs.

[0076] The method and system disclosed herein are used in a certain expressway with a total length of 339.429 km, a two-way four-lane expressway, including 4 extra-large bridges, 87 large bridges, and 18 tunnels, which is a typical long-distance seasonally frozen mountain expressway.

[0077] The implementation process includes: Import the bill of quantities and machinery shift quotas of the high-speed construction drawings. The system automatically cleans up and unifies the building materials and machinery codes, marks the regional labels, and binds the power grid carbon emission factor. Hash algorithms are used to retrieve localized carbon emission factors for cement, steel, asphalt, and sand and gravel. The coupling deduplication matrix calculation of the four stages of the entire life cycle (material production, material transportation, road construction, operation and maintenance) automatically merges the multi-level transfer mileage of sand and gravel and asphalt, and superimposes the winter maintenance compensation item; The project is recursively divided into seven types of unit projects, including roadbed, pavement, bridges and culverts, and tunnels, and the carbon emissions of each item are calculated in parallel. Multi-threaded Monte Carlo analysis identified cement, steel, and tunnel heating as the most sensitive parameters, and bridges and tunnels as the primary emission reduction control units. The system automatically outputs information such as total carbon emissions of 6.1065 million tons of CO2e (ten thousand tons of carbon dioxide equivalent) and carbon emission intensity per unit mileage of 90,900 tons of CO2e / km, and generates a report on recommendations for low-carbon retrofitting of seasonally frozen highways.

[0078] Using the existing general Excel segmentation algorithm without seasonal freezing compensation and without weight reduction, the total carbon emissions of the same highway were calculated to be 7.3682 million tCO2e, which is 20.66% different from the calculation result of this invention, proving that the accuracy advantage of this invention is significant.

[0079] This disclosure can be directly applied to carbon accounting for newly built expressways, national and provincial highways, and rural roads in seasonally frozen areas, supporting green highway applications, dual-carbon transportation planning, and highway energy conservation assessments; it automatically identifies high-carbon emission units such as bridges, culverts, and tunnels, providing quantitative data support for low-carbon design and maintenance scheme optimization for seasonally frozen roads. This disclosure fills the gap in intelligent carbon accounting specifically for roads in seasonally frozen areas.

[0080] This disclosure presents a method and system for calculating carbon emissions throughout the entire lifecycle of highways in seasonally frozen areas. It provides an intelligent method and system for carbon emission accounting for highways in seasonally frozen areas, constructing a localized three-level hash mapping repository. This repository is used to retrieve carbon emission factors, divide the highway's entire lifecycle, and calculate the total carbon emissions throughout the highway's lifecycle, considering overlapping material flows and the incremental carbon emissions from seasonal maintenance. A recursive traversal algorithm divides highway projects into multiple types of unit projects, performs multi-threaded parallel random sampling and calculation of carbon emissions throughout the highway's lifecycle for all highly sensitive parameters, identifies high-carbon-emission units, and finally generates a carbon assessment report. This design balances accuracy and efficiency in carbon accounting for highways in seasonally frozen areas.

[0081] Specifically: This disclosure improves the accuracy and efficiency of carbon accounting for highways in seasonally frozen areas.

[0082] This disclosure establishes a hash mapping repository for carbon emissions specific to the frozen zone, which rapidly matches emission parameters for cold regions by three levels of mapping: region, major building material category, and sub-building material. This solves the pain points of the general model lacking localization factors and having large calculation errors, reducing the error from 22% to less than 6%, and reducing the carbon accounting error by 16 percentage points. This disclosure presents a four-stage material flow coupling deduplication operator for the entire life cycle of highways, introduces multi-level material transfer deduplication logic, automatically merges the segmented transportation mileage of building materials, eliminates the duplicate statistics caused by traditional independent calculation in each stage, and significantly improves the authenticity of carbon accounting results. This disclosure also considers the carbon emission increment of seasonal freezing maintenance, that is, it adds the carbon emission increment compensation of seasonal freezing maintenance, and specifically embeds the carbon emission increment of winter snow removal machinery energy consumption, tunnel year-round heating, freeze-thaw repair and overhaul, and de-icing agent production and transportation, filling the gap in the existing model for special calculation of maintenance in areas without severe cold, and improving the authenticity of carbon accounting results. Eliminating the bias of double counting and solving the problem of inflated carbon emissions in traditional segmented algorithms, the calculation results are in line with ISO 14040 (the core general standard under the ISO 14000 environmental management system published by the International Organization for Standardization), IPCC 2006 (the 2006 IPCC National Greenhouse Gas Inventory Guide), and the highway LCA evaluation standard (the implementation and refinement of the ISO 14040 general framework in the highway field).

[0083] This public disclosure combines hash retrieval, recursive matrix parallel decomposition, and multi-threaded Monte Carlo parallel computation. It employs a recursive traversal algorithm to divide highway engineering projects into multiple unit projects; and utilizes multi-threaded Monte Carlo parallel computation to perform multi-threaded parallel random sampling of all highly sensitive parameters and calculate the carbon emissions of each sample group throughout the highway's entire lifecycle. This design achieves intelligent and efficient computation, reducing the calculation time for large-scale highways by more than 99%.

[0084] This disclosure can not only output the total carbon emissions, but also automatically locate high carbon emission control units such as bridges, culverts, and tunnels, with high efficiency in identifying emission reduction targets.

[0085] This disclosure achieves full-process automation, eliminating the need for manual breakdown of project quantities, manual statistics, and manual comparison, thus reducing human calculation errors and resulting in higher calculation accuracy.

[0086] This disclosure can be directly packaged into a Python / Java program, embedded into highway design and carbon management digital platforms, and output officially recognized standardized carbon verification documents, making it highly applicable to engineering projects.

[0087] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] The embodiments described above are merely illustrative of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these all fall within the protection scope of this disclosure. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for calculating carbon emissions throughout the entire life cycle of highways in seasonally frozen areas, characterized in that, include: A localized carbon emission factor library for the frozen zone is obtained and a three-level hash mapping repository is constructed based on the mapping relationship, which consists of a regional code hash layer, a building material category hash layer, and a sub-building material hash layer. The sub-building material hash layer stores the localized carbon emission factor entity data for the frozen zone. Obtain multi-source engineering data for highways in seasonally frozen areas that are to be carbon emission accounted for. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota for highway engineering machinery shifts. Preprocess the multi-source engineering data. The carbon emission factor corresponding to the preprocessed multi-source engineering data was retrieved using a three-level hash mapping repository. The entire life cycle of a highway is divided into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. Based on the carbon emission factors corresponding to the preprocessed multi-source engineering data, and under the premise of eliminating material flow overlap, the carbon emission increment of seasonal freezing maintenance is considered to calculate the carbon emissions of the highway throughout its entire life cycle. A recursive traversal algorithm is used to divide highway engineering into multiple types of unit projects; Construct a two-dimensional matrix of unit project-carbon emissions, and calculate the total carbon emissions over the life cycle of the highway project and the carbon emission intensity per unit mileage of the unit project based on the matrix; Selecting multiple highly sensitive parameters for seasonally frozen roads; Based on the carbon emission factors of the preprocessed multi-source engineering data, multi-threaded parallel random sampling is performed on all high-sensitivity parameters. Each type of high-sensitivity parameter corresponds to one thread, and each type of high-sensitivity parameter is randomly sampled to obtain a sample group. The carbon emission of each sample group in the entire life cycle of the highway is calculated. The carbon emission contribution ratio of each high-sensitivity parameter is statistically analyzed and sorted in descending order, and high carbon emission units in the highway are automatically marked. Generate and output carbon assessment reports, which include information on carbon emission intensity and emission reduction measures for various types of projects.

2. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The incremental carbon emissions from seasonal freezing maintenance include the increased carbon emissions from winter snow removal machinery energy consumption, year-round tunnel heating, freeze-thaw repair and major overhauls, and the production and transportation of de-icing agents.

3. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The formula for calculating the carbon emissions of the highway throughout its entire life cycle is as follows: ； in, This refers to the carbon emissions throughout the entire life cycle of a highway. This refers to carbon emissions during the material production stage. To eliminate carbon emissions from the material transportation stage after material flow overlaps, This refers to carbon emissions during the road construction phase. This refers to carbon emissions during the operation and maintenance phase. This refers to the increased carbon emissions from seasonal freezing maintenance, namely, the increased energy consumption of snow removal machinery in winter, year-round heating of tunnels, freeze-thaw repair and major overhauls, and the production and transportation of de-icing agents.

4. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The various types of unit projects include roadbed engineering, pavement engineering, bridge and culvert engineering, tunnel engineering, intersection engineering, ancillary facilities, and temporary works; unit projects include three types of carbon emissions, namely material emissions, transportation emissions, and machinery emissions.

5. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 4, characterized in that, The formula for calculating the total carbon emissions over the life cycle of the highway project is as follows: in: The total carbon emissions from highway engineering projects; For the first Total carbon emissions per unit of project For the first Material emissions for similar unit projects; For the first Transportation emissions of similar unit projects; For the first Mechanical emissions of similar unit projects; The formula for calculating the carbon emission intensity per unit mileage of the project is as follows: in: For the first Carbon emission intensity per unit mileage of similar projects For the first The total length of the route for a unit project of this type.

6. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The selected highly sensitive parameters include cement consumption, steel consumption, average material transportation distance, fuel consumption of construction machinery, and winter heating duration in tunnels.

7. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The method also includes the step of outputting a sensitivity analysis list, which includes the name of the high carbon emission unit and the carbon emissions of all high-sensitivity parameters for each high carbon emission unit.

8. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The report also includes information on the contribution percentage of carbon emissions from highly sensitive parameters and information on high-carbon emission units in highways.

9. The method for calculating the carbon emissions of highways in seasonally frozen areas throughout their entire life cycle according to claim 1, characterized in that, The steps for generating the carbon assessment report include: automatically matching route optimization, low-carbon building materials, recycled pavement, and photovoltaic tunnel emission reduction methods based on high-carbon emission units in highways and combined with the emission reduction knowledge base for seasonally frozen areas, and generating emission reduction measures.

10. A life-cycle carbon emission accounting system for highways in seasonally frozen areas, characterized in that, include: The module is used to obtain a localized carbon emission factor library for the frozen zone and construct a three-level hash mapping repository based on it, with the mapping relationship being a regional code hash layer, a building material category hash layer, and a subdivided building material hash layer. The subdivided building material hash layer stores the localized carbon emission factor entity data for the frozen zone. The acquisition module is used to acquire multi-source engineering data of highways in seasonally frozen areas to be subject to carbon emission accounting. The multi-source engineering data includes the bill of quantities for highway engineering projects and the quota of shifts for highway engineering machinery. The preprocessing module is used to preprocess multi-source engineering data; The retrieval module is used to retrieve the carbon emission factor corresponding to the preprocessed multi-source engineering data using a three-level hash mapping repository. The module is used to divide the entire life cycle of a highway into the material production stage, the material transportation stage, the road construction stage, and the operation and maintenance stage. The first calculation module is used to calculate the carbon emissions of the highway throughout its entire life cycle based on the carbon emission factors corresponding to the preprocessed multi-source engineering data, while eliminating the overlap of material flow and taking into account the carbon emission increment of seasonal freezing maintenance. The second calculation module is used to divide highway engineering into multiple types of unit projects using a recursive traversal algorithm; This is used to construct a two-dimensional matrix of carbon emissions per unit project, which is then used to calculate the total carbon emissions over the life cycle of a highway project and the carbon emission intensity per unit mileage of the project based on the matrix. The selection module is used to select various highly sensitive parameters for seasonally frozen roads; The sampling module is used to perform multi-threaded parallel random sampling of all high-sensitivity parameters based on the carbon emission factors of preprocessed multi-source engineering data. Each type of high-sensitivity parameter corresponds to one thread, and each type of high-sensitivity parameter is randomly sampled to obtain a sample group. The third calculation module is used to calculate the carbon emissions of each sample group throughout the entire life cycle of the highway. The statistical labeling module is used to calculate the carbon emission contribution ratio of each highly sensitive parameter and sort them in descending order, automatically labeling high carbon emission units in highways. The report generation module is used to generate and output carbon assessment reports, which include carbon emission intensity information and emission reduction measures for various types of projects.

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