1. An emission manifest construction method, comprising:

dividing a target area into a plurality of grids;

determining a plurality of sampling periods corresponding to each vehicle in each grid;

calculating the pollutant discharge amount of each vehicle in each sampling period;

overlapping the pollutant emission of each vehicle in a plurality of sampling periods corresponding to each grid to obtain the emission of each vehicle in each grid;

and summarizing the pollutant discharge amount of all vehicles corresponding to each grid to obtain a discharge list of the target area.

2. The method of claim 1, wherein the determining a corresponding number of sampling periods for each vehicle in each grid comprises:

detecting the driving position of the starting moment of each sampling period and/or the driving position of the ending moment of each sampling period;

and matching the driving position with the grids to determine the sampling period corresponding to each grid.

3. The method of claim 2, wherein the matching comprises:

the driving position at the starting moment of the sampling period is in the grid; or

The driving position at the end moment of the sampling period is in the grid; or

The travel position at the start of the sampling period and the travel position at the end of the sampling period are both in the grid.

4. The method of claim 1, wherein the amount of pollutant emissions is calculated from a pollutant emission factor and a distance traveled over a sampling period.

5. The method of claim 4, wherein the distance traveled is calculated from location information of the vehicle over a sampling period.

6. The method of claim 4, further comprising modifying the pollutant emission factor, comprising:

the pollutant emission factor is modified according to one or more of an environmental modification factor, a vehicle speed modification factor, a vehicle degradation modification factor, and a vehicle other usage condition modification factor.

7. The method of claim 6, wherein the formula for calculating the pollutant emission factor comprises:

in the formula: EF_i,po,sAn emission factor representing the pollutant po of the vehicle i at time s; BEF_i,poA composite baseline emission factor representing a pollutant po of vehicle i;representing an environmental correction factor; gamma ray_sA speed correction factor representing the vehicle at time s; λ represents a vehicle deterioration correction factor; theta represents other usage condition correction factors of the vehicle.

8. The method of claim 1, wherein the contaminants comprise one or more air contaminants of carbon monoxide, hydrocarbons, nitrogen oxides, and particulates.

9. An emissions manifest construction system, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing the method of emission list construction according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, implements the emission manifest construction method as defined in any one of claims 1 to 8.

Background

With the increasing urbanization process and the rapid increase of economy, automobiles are also becoming important emission sources of pollutants such as nitrogen oxides (NOx) and Particulate Matters (PM). In order to analyze the emission characteristics (e.g., emission amount, emission concentration, etc.) of pollutants in a region, a method currently used is to establish an emission list of various pollutants. The pollutant discharge list is the detail of the discharge amount of various pollutants in a region in a period of time, and is also basic data for knowing the discharge characteristics of atmospheric pollutants in the region and carrying out pollution reduction. However, the current pollutant discharge list usually calculates the pollutant discharge amount of the whole area, and the specific discharge amount of each part (such as different road sections in each road in the area) in the area is not clear. Therefore, the current emission list construction method cannot support the requirements of emission list construction with high resolution and space precision management.

Disclosure of Invention

The invention provides an emission list construction method, an emission list construction system and a readable storage medium, which aim to solve the problem that the existing emission list construction method cannot support the high-resolution emission list construction and the requirement of space precise management.

In order to solve at least the above problems, the present invention proposes a method of constructing an emission list. According to the method, the target area is divided into grids, and the pollutant emission amount of each grid is calculated, so that the spatial resolution of an emission list is improved. And calculating the number of corresponding sampling periods when the vehicles pass through the grids, and overlapping the emission of the corresponding sampling periods in the grids, thereby obtaining the pollutant emission of all vehicles in each grid. The accuracy of pollutant discharge amount in each grid is effectively guaranteed through the calculation mode, and the construction of a high-resolution discharge list is facilitated.

In one aspect, the present invention provides an emissions manifest construction method comprising: dividing a target area into a plurality of grids; determining a number of sampling periods corresponding to each vehicle in each grid; calculating the pollutant discharge amount of each vehicle in each sampling period; overlapping the pollutant emission of each vehicle in a plurality of sampling periods corresponding to each grid to obtain the emission of each vehicle in each grid; and summarizing the pollutant discharge amount of all vehicles in each grid to obtain a discharge list of the target area.

In one embodiment, the determining a corresponding number of sampling periods for each vehicle in each grid comprises: detecting the driving position of the starting moment of each sampling period and/or the driving position of the ending moment of each sampling period; and matching the driving position with the grids to determine the sampling period corresponding to each grid.

In one embodiment, the matching comprises: the driving position at the starting moment of the sampling period is in the grid; or the driving position at the end of the sampling period is in the grid; or both the travel position at the start time of the sampling period and the travel position at the end time of the sampling period are in the grid.

In one embodiment, the pollutant discharge amount is calculated according to a pollutant discharge factor and a driving distance in a sampling period.

In one embodiment, the distance traveled is calculated based on positioning information of the vehicle during a sampling period.

In one embodiment, further comprising modifying the pollutant emission factor, comprising: the pollutant emission factor is modified according to one or more of an environmental modification factor, a vehicle speed modification factor, a vehicle degradation modification factor, and a vehicle other usage condition modification factor.

In one embodiment, the formula for calculating the pollutant emission factor includes:

in the formula: EF_i,po,sAn emission factor representing the pollutant po of the vehicle i at time s; BEF_i,poA composite baseline emission factor representing a pollutant po of vehicle i;representing an environmental correction factor; gamma ray_sA speed correction factor representing the vehicle at time s; λ represents a vehicle deterioration correction factor; theta represents other usage condition correction factors of the vehicle.

In one embodiment, the contaminants include one or more air contaminants of carbon monoxide, hydrocarbons, nitrogen oxides, and particulates.

In another aspect, the present invention provides an emissions manifest construction system comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the aforementioned emission manifest construction method when executing the computer program.

In yet another aspect, the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the aforementioned emission manifest construction method.

The invention can obtain the discharge list with high spatial resolution by dividing the target area into grids and calculating the pollutant discharge amount of each grid. And in each grid, calculating the number of corresponding sampling periods when the vehicle passes through the grid, and overlapping the emission of a plurality of corresponding sampling periods in the grid, thereby acquiring the pollutant emission conditions of all vehicles in each grid. Since the driving position of the vehicle and the pollutant discharge amount in the sampling period are monitored in each grid in near real time according to the sampling period, the grid-based discharge list can position the pollutant discharge amount to the driving position of the vehicle. Based on the method, the high-resolution emission list can be constructed by using the method, and the space precision management of the current region is facilitated.

Drawings

The foregoing and other objects, features and advantages of exemplary embodiments of the present invention will be readily understood by reading the following detailed description with reference to the accompanying drawings. Several embodiments of the present invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar or corresponding parts and in which:

FIG. 1 is a schematic diagram of an emissions manifest construction method according to one embodiment of the present invention;

FIG. 2 is a schematic diagram of a method for determining a corresponding sampling period in each grid according to an embodiment of the invention;

FIG. 3 is a schematic diagram of a vehicle traveling through a grid in accordance with one embodiment of the present invention;

FIG. 4 is a schematic diagram of a distribution of sampling periods in a grid according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a sampling period spanning two different grids in accordance with one embodiment of the present invention;

FIG. 6 is a schematic diagram of calculating a vehicle distance traveled based on latitude and longitude according to an embodiment of the present invention;

FIG. 7 is a schematic illustration of the distribution of pollutant emissions in a grid according to an embodiment of the present invention;

FIG. 8 is a schematic overview of pollutant emission lists for different vehicles in accordance with one embodiment of the present invention;

FIG. 9 is a schematic diagram of a grid for administrative areas of a certain region according to an embodiment of the present invention;

FIG. 10 is a schematic illustration of an emissions listing for a region according to an embodiment of the present invention;

FIG. 11 is a schematic enlarged partial view of an emissions listing for a region according to one embodiment of the present invention;

FIG. 12 is a schematic diagram of an emissions manifest construction system according to one embodiment of the present invention.

Detailed Description

Embodiments will now be described with reference to the accompanying drawings. It will be appreciated that for simplicity and clarity of illustration, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the embodiments described herein. However, it will be understood by those of ordinary skill in the art that the embodiments described herein may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the embodiments described herein. Moreover, this description is not to be taken as limiting the scope of the embodiments described herein.

Cities are the center of population gathering and energy consumption, and various types of motor vehicles in the cities are becoming important emission sources of various pollutants. In recent years, in order to cope with global climate change and reduce pollutant emission, pollutant emission lists are established and corresponding energy-saving emission-reducing control measures are issued in many cities around the world. Through the pollutant discharge list, researchers can deeply research the discharge characteristics (such as discharge amount, discharge concentration and the like) of pollutants in an area and accordingly make corresponding measures to reduce the discharge amount of the pollutants. However, the current pollutant discharge list usually calculates the pollutant discharge amount of the whole area, and the specific discharge amount of each part (such as different road sections in each road in the area) in the area is not clear. Therefore, the current emission list construction method cannot support the requirements of emission list construction with high resolution and space precision management.

According to the method, the target area is divided into a plurality of grids, and the pollutant discharge amount in the grids is calculated, so that the resolution of the target area discharge list is improved. And when the pollutant discharge amount in the grids is calculated, the corresponding sampling period in each grid in the driving process of the vehicle is determined, the pollutant discharge amount of each period is calculated, then the pollutant discharge amounts of a plurality of sampling periods in each grid are superposed, the pollutant discharge amounts of all vehicles are summarized, and the obtained data of the discharge list is more accurate. The emission list established by the method has higher resolution and data precision, and can provide reliable data guarantee for space precision management.

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

Fig. 1 is a schematic diagram illustrating an emission manifest construction method according to an embodiment of the present invention. As shown in fig. 1, the emission manifest construction method of the present invention may include the following steps:

step S101: the target area is divided into a number of meshes. In an implementation scenario, taking a certain city as an example, an administrative region of the city may be divided into 1km × 1km grids, a plurality of grids may be divided according to a region area of the city, and each grid may set a corresponding number as a grid ID.

Step S102: after the grids are divided, determining a plurality of sampling periods of each vehicle corresponding to each grid so as to conveniently summarize the pollutant discharge amount. Taking one of the vehicles as an example, in one implementation scenario, the driving information of the vehicle is acquired once every other sampling period, so as to obtain the driving data of the vehicle. In the running data of the vehicle, if the vehicle is located in the same grid in a set number of sampling periods, the sampling period corresponding to the vehicle in the grid can be determined to be the set number, and therefore the vehicle can be determined to correspond to the set number of sampling periods in the grid. Further, the sampling period may be determined according to the device that collects the vehicle information. Taking the example of collecting vehicle information by using an OBD (remote on-board diagnostic system) device on a vehicle, in one scenario, a sampling period (OBD upload data frequency) may be set to 1 s.

Step S103: and calculating the pollutant emission amount of each vehicle in each sampling period. In one scene, the pollutant discharge amount of the motor vehicle can be calculated according to the information such as the vehicle type, the vehicle speed, the discharge factors of different pollutants, the driving mileage of the vehicle and the like.

Step S104: and superposing the pollutant discharge amount of each vehicle in a plurality of sampling periods corresponding to each grid.

Step S105: and summarizing the pollutant discharge amount of all vehicles corresponding to each grid to obtain a gridded discharge list of the target area. The pollutant emission list established by the method steps can provide more refined pollutant emission characteristics in the target area and can provide data support for the air quality model.

The principles of the method of building an emissions manifest of the present invention are introduced above in connection with FIG. 1, and implementations of each process are described further below. In one embodiment, to obtain the aforementioned emissions manifest, it is necessary to first grid the target area. In one implementation scenario, the target area may be divided into grids according to grids of 1km × 1km on a GIS (Geographic Information System), so that the target area includes a plurality of grids, and each grid is assigned with a unique grid ID. It is understood that the aforementioned mesh size can be set in various forms such as 2km × 2km or 4km × 5km according to the requirement, and those skilled in the art can set the mesh size according to the specific shape of the target area or the data analysis requirement.

After the target area is gridded, in order to accurately obtain the pollutant discharge amount in each grid, the running process of the motor vehicle in the grid needs to be monitored, that is, a set number of sampling periods when the vehicle runs in the grid is determined. Specifically, as shown in fig. 2, the following steps may be adopted: step S201: the travel position at the start of each sampling period and/or the travel position at the end of the sampling period is detected. Step S202: the driving position is matched with the grids to determine the sampling period corresponding to each grid.

The above briefly describes the manner of setting a number of sampling periods corresponding to each grid, and the following describes in detail the implementation manner of each step. In one implementation scenario, the travel position at the start of each sampling period is detected, and if there are travel positions at the start of several sampling periods in the aforementioned grid, the corresponding sampling period in the grid can be determined. In one embodiment, as shown in FIG. 3Taking the driving process of a certain vehicle in the target area as an example, the process of uploading driving data for 14 times is totally performed in the driving process of the vehicle in the area (respectively corresponding to the position points of the number I in fig. 3Number location point), i.e., comprising 14 sampling periods. The time that the vehicle travels in each grid is not exactly the same due to differences in vehicle speed, road length, etc., and therefore the number of sampling periods in each grid is also not exactly the same. If it is determined to which grid the sampling period belongs at the vehicle position at the start of the sampling period, 14 sampling periods as shown in fig. 4 may be included and distributed in different grids during the vehicle traveling. Based on this, the 14 sampling periods are respectively distributed in different grids, and the number of the corresponding sampling periods in each grid is not completely the same.

In another implementation scenario, it is also possible to detect the travel position at the end of each sampling period, which corresponds to several sampling periods if there are travel positions in the aforementioned grid at the end of the sampling periods. In yet another implementation scenario, the travel position of the vehicle at the start time and the travel position of the vehicle at the end time of each sampling period are both detected, and if the travel position at the start time and the travel position at the end time of the sampling period are both in the grid, the sampling period is made to correspond to the grid.

Further, when determining the corresponding sampling periods in each grid, there may be a case where the vehicle crosses two different grids within the sampling period. The method by which the sampling period corresponds to the grid in this case will be explained next. As shown in fig. 5, if a certain sampling period starts at time t₁Is in a certain grid G1 and the sampling period ends at time t₂The driving position of (2) in grid G2, the manner of crossing two grids can determine the matching relationship of the sampling period and the grid in the following ways. In one implementation scenario, this may beThe sampling period corresponds to the grid G1, i.e. at the start of the sampling period t₁Determines the matching relationship between the sampling period and the grid, and takes the pollutant discharge amount obtained by subsequent calculation according to the sampling period as the discharge amount in the grid G1. In another implementation scenario, the sampling period may be made to correspond to the grid G2, i.e., at the end of the sampling period, time t₂The matching relationship between the sampling period and the grid is determined, and the pollutant discharge amount obtained by calculation according to the sampling period is used as the discharge amount in the grid G2. In another implementation scenario, the foregoing case where the sampling period spans two different grids may be ignored, and only the case where the driving position at the start time of the sampling period and the driving position at the end time of the sampling period are both in a certain grid is retained.

The foregoing describes a manner of determining the matching relationship between the sampling period and the grid according to the driving position, and a manner of acquiring the driving position will be described next. In an implementation scenario, the driving position of the vehicle at the start time of the sampling period and the driving position of the vehicle at the end time of the sampling period may be obtained by using a GPS, and then, through an intersection function or an open source algorithm in a GIS, the latitude and longitude of the vehicle at the start time and/or the end time of the sampling period may also be obtained and directly compared with the latitude and longitude of four corners of the grid, so as to determine the grid corresponding to the sampling period. It should be understood by those skilled in the art that the above-described embodiments are exemplary and not limiting, and that those skilled in the art can select an appropriate manner of determining the vehicle position as desired.

The determination method of the sampling period corresponding to each grid is described in detail above, and the specific means for acquiring the pollutant discharge amount in each sampling period will be described next. In one implementation scenario, the pollutant emission amount may be calculated according to the pollutant emission factor and the travel distance in the sampling period. Specifically, the emission amount of the pollutants may be a product of a pollutant emission factor and a travel distance in a sampling period.

The above explains the two factors for calculating the amount of pollutant discharge, and the following will be describedThe way in which one of the factors, namely the travel distance, is calculated is described in detail. In one application scenario, the distance traveled may be calculated based on positioning information of the vehicle during a sampling period. For example, as shown in fig. 6, the first longitude and latitude information is obtained by positioning the start time of the sampling period by using GPS (corresponding to t in fig. 6)₁Latitude and longitude information of the moment) and positioning the end moment of the sampling period to obtain second latitude and longitude information (corresponding to t in fig. 6)₂Latitude and longitude information of the moment), and then the linear distance between two times of positioning can be calculated through the following calculation formula (because the sampling period is shorter, the influence of the driving route between two times of positioning as a straight line is assumed to be smaller). The calculation formula includes:

D＝R×C

in the formula: d is the linear distance between two positionings (the linear distance traveled at the start time and the end time of sampling), m; r is the radius of the earth, and is 6371000m generally; C. a are respectively calculated intermediate parameters; long₁And long₂Respectively representing the longitude and the degree of two adjacent position points; lat₁And lat₂Respectively representing the latitude and the degree of two adjacent position points;andrespectively the latitude values of the previous position and the next position, and expressed in radian form; lambda [ alpha ]₁The longitude value of the last position and is expressed in radian;and Δ λ represent the difference in latitude radians and the difference in longitude radians at the upper and lower two positions, respectively. In another scenario, information in the driving odometer of the vehicle can be directly collected, and the driving distance of the vehicle in the corresponding sampling period can be obtained by calculating the difference value between the mileage information at the sampling end time and the mileage information at the sampling start time.

The foregoing describes in detail the manner of calculating the travel distance of the vehicle, and the manner of calculating the emission factor, which is another factor affecting the amount of pollutants discharged, will be described in detail below. The pollutant discharge factor is related to the vehicle type of the vehicle, the current vehicle speed and other factors. In one scenario, the pollutant discharge factor may be determined based on an average travel speed over a sampling period (e.g., the average travel speed is represented by a ratio of travel distance over the sampling period to the sampling period). For example, a person skilled in the art can obtain the pollutant emission factor of the vehicle type at the speed from the emission factor database according to the average running speed, and can also calculate according to a related formula. Since the calculation process does not belong to the technical solution of the present invention, it is not described herein again. After the emission factor is obtained in the above manner, the emission amount of the vehicle in the sampling period can be calculated according to the following formula:

E_i，s，po＝EF_i，po，s×L_i，s

in the formula: e_i,h,poRefers to the discharge amount, g, of pollutants po of the vehicle i at the moment s (one collection period: e.g. 30 s); EF_i,po,sRefers to the emission factor (p) of the pollutant po of the vehicle i at the moment s_oThe method comprises the following steps: CO, HC, NOx, and PM_2.5One or more of (a), g/km; l is_i,sRefers to the distance traveled by vehicle i at time s, km.

The foregoing describes a method for calculating pollutant emissions of a vehicle, and in order to further improve the accuracy of the pollutant emission calculation, in one embodiment, the method further includes a manner of correcting the pollutant emission factors. For example, the influencing factors for the pollutant emission factor can be selected and used to correct the pollutant emission factor. In one implementation scenario, the aforementioned pollutant emission factor may be modified according to one or more of an environmental modification factor, a vehicle speed modification factor, a vehicle degradation modification factor, and a vehicle other usage condition modification factor. Specifically, the aforementioned environmental correction factor may include a temperature correction factor, a humidity correction factor, and an altitude correction factor. The temperature correction factor and the humidity correction factor are ambient temperatures of the vehicle during travel, and this data can come from relevant weather websites. The altitude correction factor is derived from the average altitude condition of the target area (city), and may be used when the altitude is unknown. The average speed correction factor can be divided into five grades according to the speed to be corrected respectively. And (3) speed grading: <20, 20-0, 30-40, 40-80 and >80 km/h. For other use condition correction factors of the vehicle, oil quality correction and load factor correction can be adopted. Assuming that all vehicles use national six-standard vehicle gasoline and diesel, the vehicle weight coefficient can be 50% when unknown.

The foregoing describes several influencing factors for pollutant emission factors with which the pollutant emission factors can be corrected. In one implementation scenario, the following calculation formula may be used for the correction calculation:

in the formula: EF_i,po,sAn emission factor, g/km, representing the pollutant po of the vehicle i at time s; BEF_i,poAn integrated baseline emission factor, g/km, representing the pollutant po of vehicle i;representing an environmental correction factor; gamma ray_sA speed correction factor representing the vehicle at time s; λ represents a vehicle deterioration correction factor; theta represents other usage condition correction factors of the vehicle.

The calculation method for obtaining the pollutant emission amount of each vehicle in each sampling period is described in detail above, and the process of superimposing the pollutant emission amounts of a plurality of sampling periods corresponding to each grid will be explained next. In an implementation scenario, as shown in fig. 7, the calculated pollutant emission amount of each sampling period is superimposed according to a corresponding grid, so as to obtain a corresponding pollutant emission situation in the grid. Specifically, the pollutant discharge amount can be distinguished according to the number, and the larger the number is, the larger the pollutant discharge amount is. If the levels of emissions are measured in numbers 1-20 at different levels, the different grids in fig. 7 correspond to levels 10, 13, 18, 13, 16 and 12 of pollutant emissions, respectively. Further, each grid can be filled with colors, and the discharge amount of different grades can be distinguished according to the shade of the colors or different colors, wherein the darker the colors, the greater the discharge amount of pollutants. Further, different colors may be used in combination with shades as different levels of pollutant emissions.

Further, after the pollutant discharge amount of each vehicle in the grid is calculated and superimposed, the pollutant discharge amounts of all vehicles in each grid can be summarized according to the method to obtain the pollutant discharge conditions of all vehicles corresponding to all grids in the target area, that is, the discharge list of the target area. Take the process of superposition of the pollutant emissions of 3 different vehicles as an example. As shown in fig. 8, different pollutant emission levels (pollutant emission amounts) are distinguished by different colors, and the vehicles 1, 2, and 3 travel different paths in the target area, respectively, the gridded emission amounts of the vehicles 1, 2, and 3 are calculated by the above method, respectively, and then the pollutant emission amounts of the three vehicles in each grid are summed up, resulting in a gridded pollutant emission list on the right side in fig. 8.

The obtained gridded emission list is an emission list with high spatial resolution, and if statistics is performed on each grid according to a set time length (for example, one hour), the emission list with high spatial resolution can be obtained, so that a data base is provided for the emission characteristic research of the target area.

The emission manifest construction method in the embodiments of the present invention is described above in general and in detail, and may include carbon monoxide (CO), hydrocarbons (CH), nitrogen oxides (NOx) and Particulate Matter (PM) for pollutants that may be involved in the emission manifest_2.5) And the like. The emission list construction method according to the embodiment of the present invention will be described in detail with reference to the pollutant emission list of diesel vehicles in a certain area.

Diesel vehicles, particularly diesel trucks, are a significant source of emissions of nitrogen oxides (NOx) and Particulate Matter (PM). The current diesel vehicle is equipped with an OBD device that can upload vehicle travel information, engine information, global positioning information (GPS), and the like. The OBD device data is periodically transmitted to the data center, the uploading frequency is typically 1 second, and the period of partial OBD device uploading is 30 seconds or other times. Therefore, the device can be used for monitoring the emission condition of the diesel truck so as to calculate and obtain a pollutant emission list about the diesel truck.

First, to obtain a grid-based emission list, an administrative region of a certain area is divided into 1km × 1km grids, and 174 × 168 grids are obtained, and the division results are shown in fig. 9, and each grid is assigned with a unique ID.

Then, the position of the diesel vehicle at the starting time of the sampling period is used as the distribution position of the emission amount in the grids, so as to determine the sampling period of the corresponding diesel vehicle in each grid. Specifically, a sampling period may be set to 1 second, and the grid in which the point is located is determined by comparing whether the grid intersects with the latitude and longitude at the start time of each sampling period. In order to simplify the analysis process, in this embodiment, the sampling period corresponding to the grid is determined by directly comparing the latitude and longitude at the starting time of the sampling period with the latitude and longitude at the four corners of the grid.

Then, the pollutant emission amount per sampling period needs to be calculated. The OBD equipment can be used for acquiring the speed information, the positioning information and the like of the diesel vehicle, so that the pollutant discharge amount of the diesel vehicle in different sampling periods can be calculated according to the information. Specifically, the emission factor correction method can be used to calculate the corresponding pollutant emission factor. The corrected NOx and PM corresponding to the different speeds of diesel vehicles in a certain area and a certain year are shown in the following Table 1_2.5Emission factor:

table 1:

besides the calculation of the emission factor, the running distance in the sampling period also needs to be calculated according to the vehicle running information uploaded by the diesel vehicle OBD device. In the foregoing embodiment, a manner of calculating the travel distance between the start time and the end time of the sampling period by using latitude and longitude is described, and therefore, details thereof are not described herein. By using the pollutant emission factor and the driving distance obtained by the calculation, the emission amount of the corresponding pollutant in the sampling period can be calculated.

And then, overlapping the pollutant discharge amount of a plurality of corresponding sampling periods in each grid obtained by the calculation, so as to obtain the pollutant discharge amount condition in each grid. The process realizes calculation of the pollutant emission by taking the grid as a unit to obtain an emission list, and effectively improves the spatial resolution.

Finally, the pollutant emissions of all vehicles in each grid are aggregated so as to obtain a grid emission list of all diesel vehicles in a certain area. As shown in fig. 10, by aggregating the pollutant emissions of all vehicles in the area to the corresponding grid, a pollutant emission list for the area is obtained (only the emission list of nitrogen oxides is shown in fig. 10). The pollutant emission list of the diesel vehicle obtained by the method of the present invention has a high resolution, so that the main section can be viewed in detail by enlarging the emission list, and an emission list diagram of the partial main section such as that shown in fig. 11 is obtained, so as to facilitate in-depth analysis of the emission characteristics in each section or area. Can use and discharge the characteristic for deep understanding diesel vehicle through this emission manifest and provide the data basis to pollution management and control for diesel vehicle provides research thinking and technical support.

The method of the present invention is explained in detail above, and according to another aspect of the present invention, the present invention further provides an emission list building system 100 as shown in fig. 12, which includes a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus, and the processor executes the steps of the emission list building method. Further, the system 100 may further include a display connected to the processor for displaying the obtained pollutant emission list. The method implemented by the system is not described in detail since it has been described in detail in the foregoing.

According to yet another aspect of the invention, there is also provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements an emissions manifest construction method as described above.

In the present invention, the aforementioned readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, the computer readable storage medium may be any suitable magnetic or magneto-optical storage medium, such as resistive Random Access Memory (rram), Dynamic Random Access Memory (dram), Static Random Access Memory (SRAM), enhanced Dynamic Random Access Memory (edram), High-Bandwidth Memory (HBM), hybrid Memory cubic (hmc), hybrid Memory cube (HBM), etc., or any other medium that can be used to store the desired information and that can be accessed by an application, a module, or both. Any such computer storage media may be part of, or accessible or connectable to, a device. Any applications or modules described herein may be implemented using computer-readable/executable instructions that may be stored or otherwise maintained by such computer-readable media.

It should be understood that the terms "first" or "second," etc. in the claims, description, and drawings of the present disclosure are used for distinguishing between different objects and not for describing a particular order. The terms "comprises" and "comprising," when used in the specification and claims of the present disclosure, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the invention disclosed. As used in the specification and claims of this disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the term "and/or" as used in this disclosure and in the claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.

Although the embodiments of the present invention are described above, the descriptions are only examples for facilitating understanding of the present invention, and are not intended to limit the scope and application scenarios of the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.