CN117422594A - High space-time resolution highway van carbon emission metering method and device - Google Patents
High space-time resolution highway van carbon emission metering method and device Download PDFInfo
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Abstract
The invention discloses a high space-time resolution carbon emission metering method and device for a highway van, which are used for identifying highway carbon sources and determining space-time distribution of the carbon sources. The method comprises the following steps: establishing a carbon emission metering model of the expressway passenger and freight car by using traffic flow data of a networking charging system of the expressway; and identifying the highway carbon source according to the established highway van carbon emission metering model and determining the space-time distribution of the carbon source. The method classifies and measures the carbon emission of different motor vehicles so as to identify main highway carbon sources and accurately position the time-space distribution of the main highway carbon sources, thereby laying a foundation for formulating traffic carbon emission reduction policies and finely managing urban space. The method utilizes high-precision networking charging big data, reduces the space scale to road sections (less than or equal to 10 km), refines the time precision to hours (1 h), and can provide more specific and diversified measures for expressway carbon emission reduction and environment management.
Description
Technical Field
The invention relates to the field of geography, in particular to a method and a device for measuring carbon emission of a highway van with high space-time resolution.
Background
Traffic carbon emission belongs to mobile source emission, and is currently internationally accepted as two carbon emission calculation methods provided by IPCC, namely a top-down method and a bottom-up method (IPCC, 1997;IPCC,2006;Svirejeva-Hopkins et al, 2008). The top-down method is used for measuring and calculating the total carbon emission of the traffic according to the energy consumption of different types of traffic in cities and the corresponding carbon emission coefficient, and is widely used in the field of traffic carbon emission research due to the characteristics of easy acquisition of statistical data, simple calculation method and the like. For example, amin et al calculate the traffic sector's average carbon dioxide emissions based on the European Union's average energy consumption, average GDP, etc., and analyze the impact of economic growth, energy consumption, and urbanization on transportation carbon emissions under the environmental Coulomb's (EKC) curve frame (Amin et al 2020). Xu et al set localized carbon emission factors, calculated total traffic carbon emission values including transportation, storage, etc. links based on fossil fuel consumption by various provinces of transportation departments in china and analyzed for spatial differences (Xu et al 2021). The "bottom-up" rule calculates the total energy consumption based on the mileage and the energy consumption per unit mileage of different vehicles, and then calculates the total carbon emission of the traffic by multiplying the energy carbon emission coefficient.
By comparing the two main traffic carbon emission metering methods, under the technical background that fine granularity statistical data is difficult to obtain, the total traffic carbon emission value can be estimated approximately by the 'top-down method', which is beneficial to analyzing the problems of urban industrial carbon emission structure, time change rule of traffic carbon emission and the like, and further guiding the problems of industrial structure adjustment, urban traffic infrastructure supply, carbon emission quota transaction and the like. The defects are as follows: (1) the metering value is the total carbon emission of the traffic department, and it is difficult to distinguish whether the carbon emission is derived from links such as transportation, equipment manufacturing, road construction and the like; (2) the carbon emission generated by different traffic modes cannot be classified and measured, and the guiding effect on the adjustment of the traffic structure is weak. Compared with the top-down method and the bottom-up carbon emission metering method, the method obviously further subdivides the traffic modes, can even distinguish passenger transportation, freight transportation and the like, is beneficial to transversely comparing carbon emission differences of different traffic modes, and is also beneficial to analyzing how people flow and logistics are transferred in different traffic modes, so that comprehensive traffic planning is scientifically guided. However, the conventional "bottom-up" method also has certain drawbacks: (1) the space data acquisition difficulty is high, the space difference of the carbon emission of the road section is difficult to explain, and the problem of 'which path the high-value zone of the traffic carbon emission is distinguished on' is answered. Specifically, because the data to be counted and collected are numerous and complicated, and some data processing has certain difficulty, the calculation of the carbon emission of the traffic by the bottom-up method is to obtain the average driving mileage of the vehicle, the number of registered vehicles and the like based on the existing statistical data, the space range is limited by administrative limits, large-scale carbon emission space difference analysis is carried out by taking province and city as basic units, the space difference analysis comprises the steps of transversely comparing the space differences of the carbon emission of different urban traffic, exploring factors influencing the carbon emission of the traffic of the area and the like, and the method is difficult to refine to specific road sections, and the space difference of the carbon emission of the road network is analyzed based on fine-granularity statistical source data. (2) Classification of vehicles is rough, and it is difficult to answer the question of which vehicle has the greatest influence on the carbon emission of the area. At present, small-scale traffic carbon emission is less studied based on a bottom-up method, the study is mainly focused on scenic spots and traffic site ranges, sample data, questionnaire investigation data and the like are used for more, the average driving mileage of a certain type of traffic tool is counted, and the vehicle carbon emission cannot be truly and comprehensively quantified.
In combination with the above, the method for calculating the carbon emission of the traffic from bottom to top is helpful for perspective of the carbon emission characteristics of different traffic modes, so that the method for controlling the environmental pollution and planning the traffic roads becomes a hot spot research field. However, the method is limited by statistical data such as vehicle journey, attribute and number, and the like, most of current researches take province and urban areas as statistical units, measure and calculate carbon emission in the range of the statistical units, and measure and analyze all types of passenger trucks based on high-precision space-time scales (road section scales and hour time scales) and deeply explore space-time differences of road network carbon emission.
The motor vehicle emission model can be divided into an average speed model and a driving condition model according to a simulation method. The average speed model mainly comprises models such as COPERT, MOBILE; the driving condition model mainly comprises a PHEM model and the like. The average speed model takes the average speed of the vehicle in running as a characterization parameter, corrects the unit mileage emission factor of the motor vehicle based on the average speed, and multiplies the unit mileage emission factor by the running mileage of the motor vehicle to obtain the total emission amount. The driving condition model is used for paying attention to the instantaneous driving state of the motor vehicle, and measuring the emission characteristics of the motor vehicle per second under the microscopic scale based on the instantaneous working condition (including speed, acceleration and the like) test data. The research scale of the pollutant emission of the motor vehicle is continuously expanded to a microscopic level, and the research on the emission of greenhouse gases is still mainly based on an average speed model method at present. The following will describe the main models covering the emission of greenhouse gases of motor vehicles, including the COPERT model in europe, HBEFA emission factor handbook; a Mobile model in the united states, a carbon emission coefficient model of IPCC, and the like.
The COPERT (Computer Programme to calculate Emissions from RoadTransport) model is part of the road vehicle emission factor calculation in the European Environmental Agency (EEA) "air pollutant emission inventory guide", the latest version of COPERT4 at present is an integration of the European related algorithm in recent years, and the COPERT4 model can be used for estimating the main atmospheric pollutants (CO, NOx, volatile organic compounds, PM, NH) produced by six types of vehicles, passenger car (Passenger car), light commercial vehicle (light commercial vehicle), bus (bus), heavy truck (heavy duty vehicles), motorcycle (Motorcycle), and light motorcycles (Mopeds) 3 、SO 2 Etc.) emissions and greenhouse gases (CO) 2 、N 2 O、CH 4 ) The emission amount can also be used for calculating the energy consumption of the motor vehicle.
The COPERT4 model divides the vehicle emissions source into 3 phases, a hot emissions phase, a cold start emissions phase, and an evaporative emissions phase, respectively. Because, the theoretical model of carbon emission for motor vehicles is:
E TOTAL ＝E HOT +E COLD +E EVA (1)
the hot emission phase refers to carbon emission generated when the engine is at normal working temperature, and the cold emission phase is carbon emission in the warm-up phase when the engine is started, and evaporation emission is only limited to non-methane volatile organic matter emission caused by the light gasoline vehicle, and is not considered here. In view of the characteristics of relatively closed expressways, high requirements on driving behavior of motor vehicles (such as non-fault factors on roads do not allow for stop-and-go), and the like, most of motor vehicles in road sections are in normal and stable driving states, only carbon emission in a thermal emission stage of the motor vehicles is considered in the study, namely:
E HIGHWAY ＝E HOT (2)
the calculation formula of the vehicle thermal emission proposed by the COPERT4 model is as follows:
E HOT；k,r ＝N k ×M k,r ×e k,r (3)
in the formula (3), E HOT ； k,r The carbon dioxide heat emission amount of the k-type vehicle on the r-type road is expressed in g; n (N) k The number of the motor vehicles in k classes is the number of the motor vehicles in k classes; m is M k,r The driving mileage of the k-class vehicle on the r-class road is given as a unit km; e, e k,r Is the carbon dioxide emission factor, unit g/(vehicle-km).
The COPERT4 model proposes a number of vehicle emission factor metering methods for different emissions. For pollutants such as CO, HC and PM, the emission factor at each speed can be calculated based on a speed-emission relation curve model, and the operation can be simplified through average speed. Whereas for CO 2 The COPERT4 model is used for obtaining the carbon emission according to the energy consumption of the motor vehicle multiplied by the correlation coefficient. The calculation method comprises the following steps:
in the formula (4), EF EC The energy consumption coefficient is the unit mileage of the vehicle, and the unit g/km; v is the running speed of the vehicle, and the unit is km/h; alpha, beta, gamma, delta, epsilon, theta and tau are oil consumption calculation parameters. In the formula (5), EF CO2 Is carbon dioxide emission coefficientIn g/km. r is (r) H:C Is the hydrocarbon ratio of r fuel. r is (r) FC:EC Is the relation between the fuel consumption coefficient and the energy consumption coefficient.
Compared with other emission models, the COPERT model is applicable to countries with less traffic data materials, has higher flexibility of use, and can be used for developing a motor vehicle emission database with high space-time resolution. In addition, the origin European of the COPERT model is similar to the motor vehicle technology in China, and the COPERT model can also be compatible with the motor vehicle emission control standard in China (for example, the latest national VI standard in China extends the European standard system on a framework structure), so that the COPERT model has wide application in the field of China traffic emission research.
The traditional traffic carbon emission research has a series of problems of difficult classification of vehicle types, lower space analysis precision and the like, and is difficult to realize source management and space refined management of traffic carbon emission, so that the implementation of the energy conservation and emission reduction policies of the expressways is effectively promoted. From the study content, the current carbon emission study of transportation is focused on carbon emission generated by air transportation, railway transportation and the like (Lin et al, 2017; li et al, 2020), and in recent years, as the study is continued, many scholars are focusing on the carbon emission problem of urban internal "public transportation" systems, such as urban rail systems (Wang et al, 2015;Aggarwal et al, 206) of subways and light rails, public transportation (Saxe et al, 2008;Beaudet,2011;Keuken et al, 2014; ning Xiaoju and the like, 2014) of buses and electric trains and the like. In all traffic modes, the research on carbon emission of focusing highways and expressways is less, and the problems of main sources of the carbon emission of the expressways, the differences of the carbon emission of different motor vehicles, the space-time distribution pattern of the carbon emission and the like are needed to be further explored.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a high space-time resolution carbon emission metering method and device for expressway trucks, so as to identify the carbon source of the expressway and determine the space-time distribution of the carbon source.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
in a first aspect, the present invention provides a method for metering carbon emissions of a highway van with high space-time resolution, comprising:
establishing a carbon emission metering model of the expressway passenger and freight car by using traffic flow data of a networking charging system of the expressway;
and identifying the highway carbon source according to the established highway van carbon emission metering model and determining the space-time distribution of the carbon source.
Further, the traffic data includes multi-spatial scale O-D traffic data, multi-type vehicle trajectory data, multi-temporal scale traffic variation data.
Further, the highway van carbon emission metering model comprises:
a type of vehicle, a t period, and a carbon emission metering model running on an r road section:
in the formula, HCE atr Carbon emission amount of r road section for a type a vehicle t period; f (F) a The fuel consumption is hundred kilometers of a type vehicle, and L; mr is the length of the r road section; n (N) atr The number of t time periods on the r road segments for the type a vehicle; VFC (very fast frequency converter) a Is the fuel consumption coefficient of the type a vehicle.
Further, the carbon emission metering model of the type a vehicle, the period t and the road r further comprises:
the zone conditions were incorporated into the calculation model as follows:
when the r road section is located in the urban area, F a Taking F a(urban) The urban working condition is the fuel quantity of the vehicle in the expressway section of the urban area; when the r road section is located outside the urban area, F a Taking F a(suburb) The "suburban operating mode", i.e. the amount of fuel that the vehicle is driving on a highway segment outside the urban area.
Further, the highway van carbon emission metering model further comprises:
full type vehicle, t period, carbon emission metering model driving on r road segment:
in the formula, HCE tr The total carbon emission amount of the whole-type vehicle in the r road section in the t period; n is the total number of vehicle types.
Further, the highway van carbon emission metering model further comprises:
full type of vehicle, full period of time, carbon emission metering model driving in r road section:
in the formula, HCE r The total carbon emission amount of the whole-class vehicle running on the r section in the whole time period; l is the total time period division.
Further, if the period takes one day, l=24; if the time period takes two days, l=48.
Further, the highway van carbon emission metering model further comprises:
full type car, full period of time, full highway section carbon emission measurement model:
wherein HCE is the total carbon emission of the expressway; m is the total number of road segments.
In a second aspect, the present invention provides a high space-time resolution highway van carbon emission metering device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of any of the methods described above when the computer program is executed.
In a third aspect, the present invention provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of any of the methods described above.
Compared with the prior art, the invention has the beneficial effects that:
the method classifies and measures the carbon emission of different motor vehicles so as to identify main highway carbon sources and accurately position the time-space distribution of the main highway carbon sources, thereby laying a foundation for formulating traffic carbon emission reduction policies and finely managing urban space. The method utilizes high-precision networking charging big data, reduces the space scale to road sections (less than or equal to 10 km), refines the time precision to hours (1 h), and can provide more specific and diversified measures for expressway carbon emission reduction and environment management.
Drawings
FIG. 1 is a flow chart of the high space-time resolution highway van carbon emission metering provided in embodiment 1 of the present invention;
FIG. 2 is a schematic diagram of a networked toll collection system for a highway in the prior art;
FIG. 3 is a graph showing daily carbon emission changes of various passenger cars in Guangdong province;
FIG. 4 is a graph showing daily changes in carbon emissions for various trucks in Guangdong province;
fig. 5 is a schematic diagram of the carbon emission metering device for highway trucks with high space-time resolution according to the embodiment 2 of the present invention.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Example 1:
the prior study of carbon emission of highway traffic has the problem that the types of passenger and cargo vehicles cannot be subdivided. Road passenger vehicles include cars, intercity buses, and the like; freight is distributed among light, medium and heavy trucks of different types. The energy supply mode, the oil consumption characteristic, the cargo type, the transportation radius and the like of the motor vehicles are different, and the carbon emission of the highway and the space-time distribution of the carbon emission are directly or indirectly influenced.
To this end, as shown in fig. 1, the present invention establishes a highway carbon emission metering model including cars, buses, small to heavy trucks using traffic data of a highway networking toll system to identify highway carbon sources and determine the spatial and temporal distribution of the carbon sources.
The principle schematic diagram of the existing networking charging system of the expressway is shown in fig. 2, and a "staged charging mode" is implemented, namely, the expressway is segmented, each charging road section is provided with a charging portal frame (also called a portal frame), the charging portal frame can record the vehicle information of the road section, and a networking charging database is formed by summarizing. The database is covered with massive information of auxiliary charge settlement such as vehicle type, driving path, up-down high-speed time and the like, and the information can be converted into multi-space-scale O-D traffic flow data (road section scale, city scale and the like), multi-type motor vehicle track data (buses and trucks), multi-time-scale traffic flow change data (time to time period) and the like through a big data analysis technology, so that traffic flow digitization is realized.
According to industry standard of toll road vehicle classification (JT/T489-2019), the types of expressway vehicles can be divided into 10 types, wherein 4 types are buses and 6 types are trucks. From table 1, the attribute characteristics, the division criteria, and the like of different types of vehicles can be known.
TABLE 1 Tab.1Classification ofexpressway vehicles in Guangdong Province for Highway motor vehicle Classification in Guangdong province
Identifying a highway carbon source according to the established highway van carbon emission metering model and determining a carbon emission metering thought of combining carbon source space-time distribution with IPCC from bottom to top, wherein the highway carbon emission is the product of the driving mileage, unit mileage oil consumption and carbon emission coefficient of a motor vehicle, namely:
HCE＝M×F×VFC (1)
wherein HCE is highway carbon emission (highway carbon emissions) in kg; m is the driving mileage (milage) of the motor vehicle, and is converted into the length of a toll road section, and the unit is km; VFC is the fuel consumption coefficient of the motor vehicle (vehicle fuel consumption coefficient). F is fuel consumption (fuel consumption) of the motor vehicle, and the unit is L;
on the basis of the model, the high space-time precision and full-vehicle model sample expressway carbon emission metering model provided by the embodiment follows metering ideas of a single section of a single type vehicle in a single period and a full section of a full type vehicle in a full period, and specifically comprises the following steps:
(1) Establishing a carbon emission metering model of an a-type vehicle, a t period and a road r section:
in the formula, HCE atr The carbon emission quantity of the vehicle in the r road section is kg in the t period of the type a vehicle; f (F) a The fuel consumption is hundred kilometers of a type vehicle, and L; mr is the length of r road section, km; n (N) atr The number (number) of t slots on the r road segments for a type of vehicle. VFC (very fast frequency converter) a Is the fuel consumption coefficient of the type a vehicle.
Considering that the difference of congestion time, speed and the like can bring different oil consumption when the motor vehicle runs on suburban road sections and urban road sections, and further influence the carbon emission of the vehicle, the regional working condition is brought into a calculation model in the study, and the study is as follows:
when the r road section is located in the urban area, F a Taking F a(urban) The urban working condition is the fuel quantity of the vehicle in the expressway section of the urban area; when the r road section is located outside the urban area, F a Taking F a(suburb) The "suburban operating mode", i.e. the amount of fuel that the vehicle is driving on a highway segment outside the urban area.
(2) Establishing a carbon emission metering model of a full-type vehicle, a t period and a road r section:
in the formula, HCE tr The total carbon emission amount of the whole type vehicle in the r road section in the t period is kg; n is the total number of vehicle types.
(3) Establishing a carbon emission metering model of a full-type vehicle, a full period of time and a road r section:
in the formula, HCE r The total carbon emission of the whole-type vehicle in the r section in the whole time period is kg; l is the total time interval division, l=24 (integer) if the time interval takes one day, and l=48 (integer) if the time interval takes two days.
(3) The method comprises the following steps of establishing a full-type vehicle, full-period and full-road-section carbon emission metering model:
wherein HCE is the total carbon emission of the expressway and kg; m is the total number of road segments. The carbon emission coefficient and the oil consumption value are all used for referencing the previous research results, and the car on the highway in Guangdong province mainly consumes gasoline with the carbon emission coefficient of 2.93kg CO 2 /kg; other types of motor vehicles mainly consume diesel oil, and have carbon emission coefficient of 3.10kg CO 2 /kg。
As shown in fig. 3-4, for the atlas obtained by the method of the embodiment, it can be seen that the method of the invention classifies and measures carbon emissions of different motor vehicles so as to identify main highway carbon sources and accurately position time-space distribution thereof, and lays a foundation for making traffic carbon emission reduction policies and finely managing urban space. The method utilizes high-precision networking charging big data to reduce the space scale to road sections (less than or equal to 10 km) and refine the time precision to hours (1 h), thereby providing more concrete and more measures for expressway carbon emission reduction and environment management, improving the space-time analysis precision of carbon emission, classifying and metering the carbon emission of different motor vehicles and providing a new method for the space refinement management and control of expressway road sections and the energy conservation and emission reduction of expressways.
Example 2:
referring to fig. 5, the high space-time resolution carbon emission metering device for expressway trucks provided in this embodiment includes a processor 51, a memory 52, and a computer program 53 stored in the memory 52 and executable on the processor 51, such as a high space-time resolution carbon emission metering program for expressway trucks. The processor 51, when executing the computer program 53, implements the steps of embodiment 1 described above, such as the steps shown in fig. 1.
Illustratively, the computer program 53 may be partitioned into one or more modules/units that are stored in the memory 52 and executed by the processor 51 to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 53 in the high space-time resolution highway truck carbon emission metering device.
The high space-time resolution highway van carbon emission metering device can be computing equipment such as a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The high space-time resolution highway van carbon emission metering device may include, but is not limited to, a processor 51, a memory 52. It will be appreciated by those skilled in the art that fig. 5 is merely an example of a high space-time resolution highway truck carbon emission metering device and does not constitute a limitation of a high space-time resolution highway truck carbon emission metering device, and may include more or fewer components than shown, or may combine certain components, or different components, such as the high space-time resolution highway truck carbon emission metering device may also include input and output devices, network access devices, buses, and the like.
The processor 51 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (FieldProgrammable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 52 may be an internal memory element of the high spatial-temporal resolution highway truck carbon emission metering device, such as a hard disk or memory of the high spatial-temporal resolution highway truck carbon emission metering device. The memory 52 may also be an external storage device of the high space-time resolution expressway van carbon emission measuring device, such as a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card) or the like, which is provided on the high space-time resolution expressway van carbon emission measuring device. Further, the memory 52 may also include both internal and external memory devices of the high spatial-temporal resolution highway truck carbon emission metering apparatus. The memory 52 is used to store the computer program and other programs and data required for the high spatial-temporal resolution highway truck carbon emission metering device. The memory 52 may also be used to temporarily store data that has been output or is to be output.
Example 3:
the present embodiment provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method described in embodiment 1.
The computer readable medium can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer readable medium may even be paper or another suitable medium upon which the program is printed, such as by optically scanning the paper or other medium, then editing, interpreting, or otherwise processing as necessary, and electronically obtaining the program, which is then stored in a computer memory.
The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, and are not intended to limit the scope of the present invention. All equivalent changes or modifications made in accordance with the essence of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A high space-time resolution highway van carbon emission metering method, comprising:
establishing a carbon emission metering model of the expressway passenger and freight car by using traffic flow data of a networking charging system of the expressway;
and identifying the highway carbon source according to the established highway van carbon emission metering model and determining the space-time distribution of the carbon source.
2. The high spatial-temporal resolution highway van carbon emission metering method of claim 1, wherein the traffic data comprises multi-spatial scale O-D traffic data, multi-type motor vehicle trajectory data, multi-temporal scale traffic variation data.
3. The high space-time resolution highway van carbon emission metering method of claim 1, wherein the highway van carbon emission metering model comprises:
a type of vehicle, a t period, and a carbon emission metering model running on an r road section:
in the formula, HCE atr Carbon emission amount of r road section for a type a vehicle t period; f (F) a The fuel consumption is hundred kilometers of a type vehicle, and L; mr is the length of the r road section; n (N) atr The number of t time periods on the r road segments for the type a vehicle; VFC (very fast frequency converter) a Is the fuel consumption coefficient of the type a vehicle.
4. A high space-time resolution highway van carbon emission metering method as claimed in claim 3, wherein the a-type vehicle, t-period, carbon emission metering model for driving on r-section further comprises:
the zone conditions were incorporated into the calculation model as follows:
when the r road section is located in the urban area, F a Taking F a(urban) The urban working condition is the fuel quantity of the vehicle in the expressway section of the urban area; when the r road section is located outside the urban area, F a Taking F a(suburb) The "suburban operating mode", i.e. the amount of fuel that the vehicle is driving on a highway segment outside the urban area.
5. A high space-time resolution highway van carbon emission metering method as claimed in claim 3, wherein said highway van carbon emission metering model further comprises:
full type vehicle, t period, carbon emission metering model driving on r road segment:
in the formula, HCE tr The total carbon emission amount of the whole-type vehicle in the r road section in the t period; n is the total number of vehicle types.
6. A high space-time resolution highway van carbon emission metering method as claimed in claim 3, wherein said highway van carbon emission metering model further comprises:
full type of vehicle, full period of time, carbon emission metering model driving in r road section:
in the formula, HCE r The total carbon emission amount of the whole-class vehicle running on the r section in the whole time period; l is the total time period division.
7. The high space-time resolution highway van carbon emission metering method as claimed in claim 6, wherein if the period takes one day, l=24; if the time period takes two days, l=48.
8. The high spatial-temporal resolution highway van carbon emission metering method of claim 6, wherein said highway van carbon emission metering model further comprises:
full type car, full period of time, full highway section carbon emission measurement model:
wherein HCE is the total carbon emission of the expressway; m is the total number of road segments.
9. A highway truck carbon emission metering device of high space-time resolution comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the method according to any one of claims 1 to 8 when said computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 8.
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