Comprehensive transport hub distribution and collection traffic carbon emission accounting method based on efficiency evaluation

Abstract

The application discloses a comprehensive traffic hub gathering and distributing traffic carbon emission accounting method based on efficiency evaluation, belongs to the technical field of low-carbon traffic and energy saving and emission reduction, and comprises the following steps: determining a carbon emission accounting region and calculation basis of gathering and distributing traffic in the hub; identifying main gathering and distributing traffic modes and matching corresponding carbon emission accounting formulas; collecting traffic flow and driving distance data of each traffic mode in the accounting region, and accounting carbon emission in a selected time range; constructing a carbon emission efficiency evaluation system, determining a decision unit, and calculating input and output indexes; analyzing carbon emission efficiency of each traffic mode based on an SBM-DEA model, and revealing key influencing factors through sensitivity analysis. The application adopts the above-mentioned comprehensive traffic hub gathering and distributing traffic carbon emission accounting method based on efficiency evaluation, performs carbon emission efficiency evaluation on different traffic modes, and provides a scientific basis for formulating more effective energy saving and emission reduction policies.

Description

Technical Field

[0001] This invention relates to the fields of low-carbon transportation and energy conservation and emission reduction technology, and in particular to a method for calculating carbon emissions from integrated transportation hubs based on efficiency assessment. Background Technology

[0002] As global attention to climate change continues to deepen, promoting a low-carbon economic transformation has become an international consensus. However, significant spatial heterogeneity exists in development models and carbon emission performance across regions, particularly in the transportation sector. Some regions rely on high-carbon logistics models, while others have already achieved a green and low-carbon transformation. This necessitates that national transportation emission reduction policies fully consider regional differences. Transportation hubs, as key nodes where different modes of transportation converge, occupy an irreplaceable strategic position in national and regional transportation networks. Studying the carbon emission efficiency of distribution transportation in the context of transportation hubs can not only support the formulation of precise emission reduction policies but also promote the development of low-carbon transportation. Based on environmental production theory, carbon emission efficiency must consider both expected output and the undesired output of carbon emissions. By quantifying input-output efficiency, the low-carbon performance of different modes of transportation can be scientifically assessed. However, current research on the specific scenario of transportation hubs still lacks depth.

[0003] Existing invention patents related to carbon emission efficiency and energy efficiency mainly focus on two major directions: macro-level system assessment and micro-level precise measurement and control. At the macro level, patent CN118982258A constructs a super-efficient random block model to quantify regional carbon emission reduction capabilities, while patent CN120146690A integrates PCA and AHP to achieve a subjective and objective weighted evaluation of comprehensive carbon emission efficiency. At the micro level, patent CN103310107A focuses on the energy efficiency of data center infrastructure, constructing an evaluation system through component energy consumption calculations, while patent CN120122601A uses IoT technology to determine the carbon emission status level of enterprises and link it to carbon quota trading. These patents do not cover the internal distribution transportation system of integrated transportation hubs. Existing solutions either only calculate emissions for a single mode of transportation or only perform total statistics, failing to integrate carbon emission accounting with multi-indicator efficiency analysis. This makes it difficult to identify performance differences and key influencing factors among different distribution transportation modes, necessitating a systematic accounting and evaluation method from an input-output perspective. Summary of the Invention

[0004] The purpose of this invention is to provide a carbon emission accounting method for integrated transportation hubs based on efficiency assessment, to evaluate the carbon emission efficiency of different modes of transportation, and to provide a scientific basis for improving the carbon emission performance of transportation hubs and formulating more effective energy conservation and emission reduction policies.

[0005] To achieve the above objectives, this invention provides a method for calculating carbon emissions from integrated transportation hub distribution traffic based on efficiency assessment, comprising the following steps: S1. Determine the carbon emission accounting area and calculation basis for the distribution of traffic within the transportation hub; S2. Identify the main modes of transportation within the transportation hub and match the corresponding carbon emission accounting formula for each mode of transportation. S3. Collect traffic flow data and driving distance data within the calculation area for each mode of transportation, substitute them into the corresponding carbon emission calculation formula, and calculate the carbon emissions of each mode of transportation within the selected time range. S4. Construct a carbon emission efficiency evaluation system for distribution and transportation, determine the decision-making unit, and collect and calculate the input and output indicators of the carbon emission efficiency evaluation system for distribution and transportation. S5. Based on the Slacks Based Measure Data Envelopment Analysis (SBM-DEA) model, the carbon emission efficiency of each mode of transportation is analyzed by combining input and output indicators, and the key influencing factors of carbon emission efficiency are revealed through sensitivity analysis.

[0006] Preferably, the transportation carbon emission accounting in step S1 only targets carbon dioxide emissions and does not include other carbon-containing greenhouse gases; the accounting stage is limited to the operation stage of the distribution and collection transportation and does not include the construction and maintenance stage of transportation hubs.

[0007] Preferably, the main modes of transportation identified in step S2 include: gasoline-powered cars, electric cars, taxis, buses, and rail transit.

[0008] Preferably, step S2 includes: S21. A carbon emission calculation formula is provided for gasoline-powered passenger cars. ; in, Carbon emissions from gasoline-powered cars (kgCO2); The driving range (km) of a gasoline-powered passenger car; Energy consumption per unit distance of fuel-powered passenger cars (GJ / km). The carbon dioxide emission coefficient for gasoline-powered passenger cars (kgCO2 / GJ); S22. Matching carbon emission accounting formulas for electric vehicles: ; in, Carbon emissions from electric vehicles (kgCO2); The total driving mileage (km) of an electric car throughout its entire life cycle. The driving distance (km) of the electric car within the accounting boundary. Carbon emissions (kgCO2) during the manufacturing process of electric cars. Carbon emission coefficient (kgCO2 / km) for an electric car traveling 100 kilometers. S23. Matching carbon emission accounting formulas for buses: ; in, Carbon emissions from ground public transport (kgCO2); The distance traveled by ground public transport (km); For ground public transport passenger volume (person-times P); The average passenger-kilometer emission factor for ground public transport (kgCO2 / PKM); S24. Matching carbon emission accounting formulas for rail transit: ; in, Carbon emissions from rail transit (kgCO2); The distance traveled by rail transit (km); For rail transit passenger volume (person-times P); The average passenger-kilometer emission factor for rail transit (kgCO2 / PKM); S25. Match the carbon emission accounting formula for taxis, and select the corresponding formula for fuel-powered cars or electric cars according to the energy type of the taxi.

[0009] Preferably, in step S4, the decision-making unit is the dataset of each mode of transportation within a certain time period; Input indicators include: energy consumption (tce), station area per unit turnover (m) 2 / (person·km)), operating costs (Ten thousand yuan / year); Output indicators include: expected output Traffic volume (passengers·km) and undesired output Carbon dioxide emissions (kgCO2).

[0010] Preferably, the station area per unit turnover The calculation method is: total station area divided by annual total turnover, in meters. 2 / (person·km)); where the total station area is calculated separately for each mode of transportation: For rail transit, the effective area of ​​the platform is taken as the sum of the area of ​​the concourse. If there are multiple concourses, the passenger activity area from the turnstile to the platform passage on each level is added together. For buses, the area calculated from the first and last stops is the product of the number of parking spaces and the standard area of ​​a single bus parking space. For cars, the parking lot area is taken as the total area; for multi-story parking lots, it includes the sum of the areas of the parking areas on each floor, including the horizontal projected area of ​​parking spaces, passageways, and ramps. For taxis, the sum of the areas of the passenger pick-up / drop-off area and the waiting area is used; for taxis without a fixed pick-up / drop-off area, the sum of the areas of all areas serving the taxi distribution and operation is used.

[0011] Preferably, step S5 specifically includes: S51. Construct the SBM-DEA model and set slack variables for input indicators. 、 、 Unexpected output slack variables Expected output slack variables ; S52. Solve the model to obtain the carbon emission efficiency value of each decision-making unit; S53. By eliminating individual input or output indicators one by one, recalculate the efficiency value, analyze its variation range, and identify key influencing factors.

[0012] Preferably, in step S51, the SBM-DEA model formula is: ; St ; in, For the distribution of transportation forms Carbon emission efficiency; indicators , , , and They are respectively the forms of collection and distribution of transportation Energy consumption, station area per unit turnover, operating costs, traffic turnover and carbon dioxide emissions; For linear combination coefficients, For the number of decision-making units, This indicates the number of each specific mode of transportation.

[0013] Preferably, step S53 specifically includes: S531. Eliminate individual input or output indicators one by one, and retain the remaining indicators to construct a new evaluation system. S532. Recalculate the carbon emission efficiency of each decision-making unit based on the new system. ; S533. Calculate the absolute deviation of the efficiency values ​​of each decision-making unit before and after removing the indicator. ; S534. Calculate the average of the absolute deviations of all decision-making units. ; S535, according to and To determine the degree of influence of each indicator on the carbon emission efficiency evaluation results, the greater the deviation, the more critical the indicator.

[0014] Therefore, this invention employs the aforementioned carbon emission accounting method for integrated transportation hub distribution systems based on efficiency assessment, filling the technological gap in carbon emission accounting and efficiency evaluation for integrated transportation hub distribution systems. It establishes specific accounting formulas for five core transportation modes to achieve accurate carbon emission measurement. The SBM-DEA model scientifically quantifies the carbon emission efficiency of each mode, clearly identifying subways and buses as highly efficient and low-carbon modes. Sensitivity analysis accurately identifies key influencing factors such as energy consumption and station area, providing data support for emission reduction policy formulation. This method balances accounting accuracy with comprehensive efficiency analysis, helping transportation hubs optimize resource allocation and reduce carbon emissions, providing a practical and feasible technical path for low-carbon transportation development.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the carbon emission accounting area according to an embodiment of the present invention; Figure 2 This is a flowchart of a method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the sensitivity analysis results of various transportation modes after deleting the energy consumption index in an embodiment of the present invention; Figure 4 This is a schematic diagram of the sensitivity analysis results of various transportation modes after deleting the land area index in an embodiment of the present invention; Figure 5 This is a schematic diagram of the sensitivity analysis results of various transportation modes after deleting the operating cost indicator in an embodiment of the present invention; Figure 6 This is a schematic diagram showing the sensitivity analysis results of various transportation modes after removing the carbon dioxide emission index in an embodiment of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0018] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example 1 Hongqiao Integrated Transportation Hub, as one of the largest and most modern integrated transportation hubs in China, occupies a pivotal position in the national transportation network, handling enormous passenger and freight volumes daily. Its carbon emissions have thus attracted widespread attention from all sectors of society. Figure 1 As shown, this embodiment takes the Hongqiao Transportation Hub as an example to further illustrate the specific application of the technical method of the present invention. A method for calculating carbon emissions from the distribution of traffic in a comprehensive transportation hub based on efficiency assessment includes the following steps, as follows: Figure 2 As shown: S1. Determine the carbon emission accounting area for traffic gathering and dispersal within the transportation hub ( Figure 1 ) and the basis for calculation; Among them, the carbon emission accounting for transportation only targets carbon dioxide emissions and does not include other carbon-containing greenhouse gases; the accounting stage is limited to the operation stage of the distribution and collection transportation and does not include the construction and maintenance stage of transportation hubs.

[0020] S2. Identify the main modes of transportation within the transportation hub and match the corresponding carbon emission accounting formula for each mode of transportation. The main modes of transportation identified include: gasoline-powered cars, electric cars, taxis, buses, and rail transit. The carbon emission calculation formulas for each mode of transportation are as follows: Formula for calculating carbon emissions of gasoline-powered cars: ; in, Carbon emissions from gasoline-powered cars (kgCO2); The driving range (km) of a gasoline-powered passenger car; Energy consumption per unit distance of fuel-powered passenger cars (GJ / km). The carbon dioxide emission coefficient for gasoline-powered passenger cars (kgCO2 / GJ); Formula for calculating carbon emissions of electric cars: ; in, Carbon emissions from electric vehicles (kgCO2); The total driving mileage (km) of an electric car throughout its entire life cycle. The driving distance (km) of the electric car within the accounting boundary. Carbon emissions (kgCO2) during the manufacturing process of electric cars. Carbon emission coefficient (kgCO2 / km) for an electric car traveling 100 kilometers. Formula for calculating carbon emissions for buses: ; in, Carbon emissions from ground public transport (kgCO2); The distance traveled by ground public transport (km); For ground public transport passenger volume (person-times P); The average passenger-kilometer emission factor for ground public transport (kgCO2 / PKM); Formula for calculating carbon emissions from rail transit: ; in, Carbon emissions from rail transit (kgCO2); The distance traveled by rail transit (km); For rail transit passenger volume (person-times P); The average passenger-kilometer emission factor for rail transit (kgCO2 / PKM); The carbon emission accounting formula for taxis is matched, and the corresponding formula for fuel-powered cars or electric cars is selected according to the energy type of the taxi.

[0021] S3. Collect traffic flow data and travel distance data within the calculation area for each mode of transportation, substitute them into the corresponding carbon emission calculation formula, and calculate the carbon emissions of each mode of transportation within the selected time period; specifically including: S31, Traffic flow data uses the official 2023 daily passenger flow data for the Hongqiao Hub; S32. The travel distance is calculated separately for the inherent route length or average travel distance of the five modes of transportation within the calculation area; S33. For private cars (gasoline-powered and electric vehicles), assuming drivers prefer to park nearby (i.e., prioritize parking in available spaces on the entrance / exit level), based on actual survey data, and considering that some vehicles may directly proceed to other levels during peak hours when the entrance / exit level is congested, or be forced to choose another level after circling around, a correction distance is added to the distance required to park on each level. This is based on the calculated average mileage required for parking: ; in, Indicates the parking garage's first layer; Select the driver The probability of parking on a floor is determined by the proportion of available parking spaces on that floor to the total number of spaces. The correction probability for the decrease from the entry / exit level to other levels is caused by the driver's tendency to park nearby. For the driver to reach the first from the entrance Average driving distance for each level of parking space; In order to be in Add a correction distance to the required distance for multi-level parking; The vertical distance of a car moving up or down a parking garage does not affect the length of the ramp; instead, it is calculated as a horizontal distance. It is assumed that the probability of a driver starting (or ending) on ​​either the north or south side of the Hongqiao Hub is equal. The average driving distance for a driver entering the Hongqiao Hub's calculation area and completing parking or leaving the hub area via various parking garages is shown in Table 1. Table 1 Average driving distance of cars at Hongqiao Transportation Hub

[0022] S34. Regarding taxis, taxis enter the corresponding pick-up areas from the north and south high-speed rail taxi waiting areas and leave the Hongqiao area according to fixed routes. The route lengths of taxis on both the north and south sides within the calculated area are shown in Table 2, based on their operating routes. Table 2. Taxi pick-up area corresponding to driving distance at Hongqiao Transportation Hub

[0023] S35. Regarding buses, the bus routes of the Hongqiao Hub, encompassing both the East and West Transportation Centers, are taken as the research object. The route lengths of each route within the calculation area are shown in Table 3. Table 3. Bus route numbers and section lengths at Hongqiao Transportation Hub

[0024] S36. Regarding rail transit, Metro Lines 2, 10, and 17 pass through the carbon emission accounting area of ​​Hongqiao Hub. The length of each line's route within the accounting area is calculated based on its operating route map, as shown in Table 4. Table 4. Rail Transit Line Numbers and Section Lengths at Hongqiao Transportation Hub

[0025] S37. Apply the corresponding formulas to each mode of transportation and substitute the daily passenger flow data of the 2023 distribution transportation system for calculation.

[0026] S4. Construct a carbon emission efficiency evaluation system for distribution and transportation, determine the decision-making unit, and collect and calculate the input indicators (energy consumption, station area per unit turnover, operating cost) and output indicators (distribution and transportation turnover, carbon dioxide emissions) of the carbon emission efficiency evaluation system for distribution and transportation. Since the number of decision-making units should not be less than the product of the number of input and output indicators, and not less than three times the number of input and output indicators, and considering the influencing factors of carbon emissions from the Hongqiao Hub's distribution transportation, and taking into account that the distribution transportation modes and input and output indicators should not be increased or decreased, the data of five distribution transportation modes in four different quarters are used as the analysis object, and twenty decision-making units are established. The carbon emission efficiency of each transportation mode is the average of the carbon emission efficiency in the four seasons. Input indicators are energy consumption Equivalent, measured in tons of standard coal equivalent (tce), according to the Chinese national standard "General Rules for Calculation of Comprehensive Energy Consumption" (GB / T 2589-2020): ; ; Convert fuel energy consumption and electricity consumption into the same unit; The station area per unit turnover, in m² 2 / (person·km), where, for rail transit, it is the sum of the platform and concourse areas; for buses, it is the converted area of ​​the first and last stations; for cars, it is the parking lot area; and for taxis, it is the sum of the passenger pick-up and drop-off area and the waiting area. Operating costs, expressed in RMB 10,000 per year, include all personnel and maintenance costs related to the distribution and transportation of goods. Output indicators are divided into expected output... Traffic volume (passengers·km) and CO2 emissions from undesired outputs (kgCO2).

[0027] S5. Based on the Slacks Based Measure Data Envelopment Analysis (SBM-DEA) model, the carbon emission efficiency of each mode of transportation is analyzed by combining input and output indicators, and the key influencing factors of carbon emission efficiency are revealed through sensitivity analysis.

[0028] S51. Construct the SBM-DEA model and set slack variables for input indicators. , , Unexpected output slack variables Expected output slack variables ; The formula for the SBM-DEA model is: ; St ; in, For the distribution of transportation forms Carbon emission efficiency; indicators , , , and They are respectively the forms of collection and distribution of transportation Energy consumption, station area per unit turnover, operating costs, traffic turnover and carbon dioxide emissions; For linear combination coefficients, For the number of decision-making units, This represents the number of each specific mode of transportation. The corresponding carbon efficiency value and slack variable value for each mode of transportation are obtained, as shown in Table 5. The results are sorted by carbon efficiency value, as shown in Table 6.

[0029] Table 5 Output results of SBM-DEA model Table 6 Ranking of carbon emission efficiency of distribution and transportation modes S52. Solve the model to obtain the carbon emission efficiency value of each decision-making unit; S53. By eliminating individual input or output indicators one by one, recalculate the efficiency value, analyze its variation range, and identify key influencing factors.

[0030] S531. Eliminate individual input or output indicators one by one, and retain the remaining indicators to construct a new evaluation system. S532. Recalculate the carbon emission efficiency of each decision-making unit based on the new system. ; S533. Calculate the absolute deviation of the efficiency values ​​of each decision-making unit before and after removing the indicator. ; S534. Calculate the average of the absolute deviations of all decision-making units. ; S535, according to and To determine the degree of influence of each indicator on the carbon emission efficiency evaluation results, the greater the deviation, the more critical the indicator.

[0031] For the Hongqiao Hub case, since the expected output only includes the single indicator of traffic turnover, to ensure the DEA model's identification capability and result reliability, the sensitivity analysis only involved the deletion of three input indicators and one undesirable output indicator one by one. The results are as follows. Figure 3-6 As shown.

[0032] Therefore, this invention employs the aforementioned carbon emission accounting method for integrated transportation hub distribution systems based on efficiency assessment, filling the technological gap in carbon emission accounting and efficiency evaluation for integrated transportation hub distribution systems. It establishes specific accounting formulas for five core transportation modes to achieve accurate carbon emission measurement. The SBM-DEA model scientifically quantifies the carbon emission efficiency of each mode, clearly identifying subways and buses as highly efficient and low-carbon modes. Sensitivity analysis accurately identifies key influencing factors such as energy consumption and station area, providing data support for emission reduction policy formulation. This method balances accounting accuracy with comprehensive efficiency analysis, helping transportation hubs optimize resource allocation and reduce carbon emissions, providing a practical and feasible technical path for low-carbon transportation development.

[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for calculating carbon emissions from integrated transportation hub distribution traffic based on efficiency assessment, characterized in that, Includes the following steps: S1. Determine the carbon emission accounting area and calculation basis for the distribution of traffic within the transportation hub; S2. Identify the main modes of transportation within the transportation hub and match the corresponding carbon emission accounting formula for each mode of transportation. S3. Collect traffic flow data and driving distance data within the calculation area for each mode of transportation, substitute them into the corresponding carbon emission calculation formula, and calculate the carbon emissions of each mode of transportation within the selected time range. S4. Construct a carbon emission efficiency evaluation system for distribution and transportation, determine the decision-making unit, and collect and calculate the input and output indicators of the carbon emission efficiency evaluation system for distribution and transportation. S5. Based on the Slacks Based Measure Data Envelopment Analysis model, the carbon emission efficiency of each mode of transportation is analyzed by combining input and output indicators, and the key influencing factors of carbon emission efficiency are revealed through sensitivity analysis. In step S1, the carbon emission accounting for transportation only targets carbon dioxide emissions and does not include other carbon-containing greenhouse gases; the accounting stage is limited to the operation stage of the distribution and collection transportation and does not include the construction and maintenance stage of transportation hubs. Step S2 includes: S21. A carbon emission calculation formula is provided for gasoline-powered passenger cars. ； in, Carbon emissions from gasoline-powered cars; This refers to the mileage of a gasoline-powered passenger car. Energy consumption per unit mileage for gasoline-powered passenger cars; The carbon dioxide emission coefficient for gasoline-powered passenger cars; S22. Matching carbon emission accounting formulas for electric vehicles: ； in, Carbon emissions from electric cars; The total driving mileage of an electric car throughout its entire lifecycle; The mileage traveled by the electric car within the accounting boundary; Carbon emissions from the manufacturing process of electric cars; The carbon emission coefficient for an electric car traveling 100 kilometers; S23. Matching carbon emission accounting formulas for buses: ； in, Carbon emissions from ground public transportation; This refers to the mileage traveled by ground public transport. This refers to the passenger volume of ground public transport. The average passenger-kilometer emission factor for ground public transport; S24. Matching carbon emission accounting formulas for rail transit: ； in, Carbon emissions from rail transit; The distance traveled by rail transit; For rail transit passenger volume; The average passenger-kilometer emission factor for rail transit; S25. Match carbon emission accounting formulas for taxis and select the corresponding formulas for fuel-powered cars or electric cars based on the energy type of the taxi. In step S4, the decision-making unit is the dataset of each mode of transportation within a certain time period; Input indicators include: energy consumption Station area per unit turnover Operating costs ; Output indicators include: expected output Traffic volume and unexpected output Carbon dioxide emissions; Step S5 specifically includes: S51. Construct the SBM-DEA model and set slack variables for input indicators. , , Unexpected output slack variables Expected output slack variables ; S52. Solve the model to obtain the carbon emission efficiency value of each decision-making unit; S53. By eliminating individual input or output indicators one by one, recalculate the efficiency value, analyze its variation range, and identify key influencing factors. In step S51, the formula for the SBM-DEA model is: ； S.t. ; in, For the distribution of transportation forms Carbon emission efficiency; indicators , , , and They are respectively the forms of collection and distribution of transportation Energy consumption, station area per unit turnover, operating costs, traffic turnover and carbon dioxide emissions; For linear combination coefficients, For the number of decision-making units, The number representing each specific mode of transportation; Step S53 specifically includes: S531. Eliminate individual input or output indicators one by one, and retain the remaining indicators to construct a new evaluation system. S532. Recalculate the carbon emission efficiency of each decision-making unit based on the new system. ; S533. Calculate the absolute deviation of the efficiency values ​​of each decision-making unit before and after removing the indicator. ; S534. Calculate the average of the absolute deviations of all decision-making units. ; S535, according to and To determine the degree of influence of each indicator on the carbon emission efficiency evaluation results, the greater the deviation, the more critical the indicator.

2. The carbon emission accounting method for integrated transportation hub distribution traffic based on efficiency assessment according to claim 1, characterized in that, The main modes of transportation identified in step S2 include: gasoline-powered cars, electric cars, taxis, buses, and rail transit.

3. The carbon emission accounting method for integrated transportation hub distribution traffic based on efficiency assessment according to claim 1, characterized in that, Station area per unit turnover The calculation method is: total station area divided by total annual turnover; whereby the total station area is calculated separately for each mode of transportation: For rail transit, the effective area of ​​the platform is taken as the sum of the area of ​​the concourse. If there are multiple concourses, the passenger activity area from the turnstile to the platform passage on each level is added together. For buses, the area calculated from the first and last stops is the product of the number of parking spaces and the standard area of ​​a single bus parking space. For cars, the parking lot area is taken as the total area; for multi-story parking lots, it includes the sum of the areas of the parking areas on each floor, including the horizontal projected area of ​​parking spaces, passageways, and ramps. For taxis, the sum of the areas of the passenger pick-up / drop-off area and the waiting area is used; for taxis without a fixed pick-up / drop-off area, the sum of the areas of all areas serving the taxi distribution and operation is used.

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