CN-121980426-A - High-rank road identification method, device, equipment and medium based on remote on-line monitoring data of heavy vehicles

CN121980426ACN 121980426 ACN121980426 ACN 121980426ACN-121980426-A

Abstract

The embodiment of the invention provides a high-emission road identification method, device, equipment and medium based on remote on-line monitoring data of a heavy vehicle, which relate to the technical field of environmental monitoring and atmospheric pollution, wherein the method comprises the steps of establishing a corresponding relation between the heavy vehicle and a road section; the method comprises the steps of determining the NOx instantaneous emission rate of each type of heavy vehicle in different time intervals of a road section, inputting the corrected pollutant diffusion model by combining with meteorological data, outputting the NOx concentration contribution quantity of each type of heavy vehicle in different time intervals of the road section to an environment monitoring station, further calculating the NOx concentration contribution quantity of the road to the environment monitoring station, calculating the NOx concentration contribution rate of each road to the environment monitoring station according to the ratio of the NOx concentration of the environment monitoring station to the NOx concentration contribution quantity of each road to the environment monitoring station, and determining a high-emission road according to the size of the contribution rate. The scheme can effectively identify the high-rank road based on the accurate contribution rate.

Inventors

FENG QIAN
YANG YANYAN
SHEN XIUE
LU YANG
WANG PENGRUI
ZHOU YANQING

Assignees

北京市生态环境监测中心

Dates

Publication Date: 20260505
Application Date: 20260401

Claims (10)

1. The high-ranking road identification method based on the remote on-line monitoring data of the heavy-duty vehicle is characterized by comprising the following steps of: dividing the roads around the environmental monitoring site into different road sections according to the space; According to the positioning information of the heavy vehicles of different types and the geographic information of the road section, establishing the corresponding relation between the heavy vehicles of different types and the road section where the heavy vehicles are positioned; Determining the NOx instantaneous emission rate of each type of heavy vehicle in different time intervals of each road section, wherein the NOx instantaneous emission rate of each type of heavy vehicle is obtained by superposition of the NOx instantaneous emission rates of each type of heavy vehicle, and the NOx instantaneous emission rate of each heavy vehicle is obtained by calculation according to the NOx emission concentration of each heavy vehicle monitored on line; Inputting the NOx instantaneous emission rate and the meteorological data of each type of heavy vehicle in different time periods of the road section into a corrected pollutant diffusion model, and outputting the NOx concentration contribution quantity of each type of heavy vehicle in different time periods of the road section to the environment monitoring station; calculating the NOx concentration contribution amount of each road to the environment monitoring site according to the NOx concentration contribution amount of all types of heavy vehicles of all road sections included in the road to the environment monitoring site in all time periods, wherein the corrected pollutant diffusion model is a pollutant diffusion model which is corrected by considering the influence of the topography factors on the pollutant diffusion; According to the ratio of the NOx concentration of the environment monitoring site to the NOx concentration contribution quantity of each road to the environment monitoring site, calculating the NOx concentration contribution rate of each road to the environment monitoring site, and determining the high-emission road according to the NOx concentration contribution rate of different roads to the environment monitoring site.
2. The method as recited in claim 1, further comprising: And correcting a diffusion term of the pollutant diffusion model by considering the influence of the terrain gradient on the thermal turbulence, and obtaining a first corrected pollutant diffusion model.
3. The method of claim 2, wherein the first modified contaminant diffusion model is formulated as follows: wherein C is the contribution quantity of each type of heavy vehicle in different time periods of the road section to the NOx concentration of the environment monitoring station, The rate of change over time of the NOx concentration contribution to the environmental monitoring site for each type of heavy vehicle at different time periods for the road segment, For the wind velocity vector to be a function of, For the convection term, the convection term is used to describe the transport process of the gas stream carrying NO x , alpha is the slope of the terrain, beta is the azimuth angle of the sun, As the coefficient of the light-emitting diode, For the NO x instantaneous emission rate of road segment j for heavy vehicles of vehicle type k during period i, In the form of a gradient, The concentration gradient of NO x , t is time, and D is diffusion coefficient.
4. A method as recited in claim 3, further comprising: And correcting a convection item of the pollutant diffusion model by considering the influence of the terrain height change on the wind speed, and obtaining a second corrected pollutant diffusion model.
5. The method of claim 4, wherein the second modified contaminant diffusion model is formulated as follows: Wherein, the As the coefficient of the light-emitting diode, The elevation differences of adjacent grids among grids divided for the terrain between the road and the environmental monitoring site, Is the distance between adjacent grids, Is the diffusion coefficient.
6. The method of any one of claims 1 to 5, further comprising: For each high-level road, adjusting the traffic flow adjustment coefficient of each road section included in each high-level road in different time periods to adjust the traffic flow of each high-level road, thereby achieving the purpose of reducing the NOx concentration of the environmental monitoring site, wherein the traffic flow adjustment coefficient of each road section in different time periods is adjusted by the following method: wherein x ij is the traffic flow adjustment coefficient of the road section j after adjustment in the period i, For the initial traffic flow adjustment coefficient for road segment j over period i, , The contribution rate of the NOx concentration of the environmental monitoring site for the section j in the period i, For the pollution sensitivity weight of road segment j in period i, For the traffic saturation of segment j in period i, In order to calibrate the constant of the device, In order to adjust the traffic flow adjustment coefficient, Meets the following constraint conditions: , for the minimum traffic flow of segment j during period i, The traffic flow of the road section j after the traffic flow adjustment coefficient is adjusted for the period i, For the original traffic flow of segment j in period i, The traffic flow is designed for the road section j, and the overall traffic flow adjustment range is as follows: T is a preset flow threshold.
7. The method of any one of claims 1 to 5, further comprising: For each high-level road, adjusting the proportion adjustment coefficient of the heavy vehicle type of each road section included in each high-level road in different time periods to adjust the proportion of the heavy vehicle of different types of each high-level road, thereby achieving the purpose of reducing the NOx concentration of an environment monitoring station, wherein the proportion adjustment coefficient of the heavy vehicle type of each road section in different time periods is adjusted by the following steps: the scaling factor for heavy vehicle type k for segment j during period i, For the original proportion of heavy vehicle type k for segment j during period i, For the minimum value of the proportion of heavy vehicle type k for road segment j during period i, For the maximum value of the proportion of heavy vehicle type k for road segment j during period i, Meets the following constraint conditions: , Is a preset proportional threshold.
8. High road recognition device based on long-range on-line monitoring data of heavy car, characterized in that includes: the dividing module is used for dividing the roads around the environment monitoring site into different road sections according to the space; the corresponding construction module is used for establishing the corresponding relation between the heavy vehicles of different types and the road section where the heavy vehicles are located according to the positioning information of the heavy vehicles of different types and the geographic information of the road section; The system comprises an instantaneous emission rate calculation module, a control module and a control module, wherein the instantaneous emission rate calculation module is used for determining the NOx instantaneous emission rate of each type of heavy vehicle in different time intervals of each road section, wherein the NOx instantaneous emission rate of each type of heavy vehicle is obtained by superposing the NOx instantaneous emission rates of the same type of heavy vehicles, and the NOx instantaneous emission rate of each heavy vehicle is calculated according to the NOx emission concentration of each heavy vehicle monitored on line; the concentration contribution amount calculation module is used for inputting the NOx instantaneous emission rate and the meteorological data of each type of heavy vehicle in different time periods of the road section into the corrected pollutant diffusion model and outputting the NOx concentration contribution amount of each type of heavy vehicle in different time periods of the road section to the environment monitoring station; calculating the NOx concentration contribution amount of each road to the environment monitoring site according to the NOx concentration contribution amount of all types of heavy vehicles of all road sections included in the road to the environment monitoring site in all time periods, wherein the corrected pollutant diffusion model is a pollutant diffusion model which is corrected by considering the influence of the topography factors on the pollutant diffusion; The high-emission road identification module is used for calculating the NOx concentration contribution rate of each road to the environment monitoring site according to the ratio of the NOx concentration of the environment monitoring site to the NOx concentration contribution quantity of each road to the environment monitoring site, and determining the high-emission road according to the NOx concentration contribution rate of different roads to the environment monitoring site.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the high-ranking road identification method based on heavy-duty vehicle remote on-line monitoring data according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the high-rank road recognition method based on the heavy-duty vehicle remote on-line monitoring data according to any one of claims 1 to 7.

Description

High-rank road identification method, device, equipment and medium based on remote on-line monitoring data of heavy vehicles Technical Field The invention relates to the technical field of mobile source environment monitoring and atmospheric pollution analysis, in particular to a high-emission road identification method, device, equipment and medium based on remote on-line monitoring data of a heavy truck. Background With the rapid advancement of urban progress and the rapid increase of the maintenance of motor vehicles, urban atmospheric pollution is increasingly serious, wherein nitrogen oxides (NOx) are one of main atmospheric pollutants, and have remarkable negative effects on air quality, human health and ecological environment. Among the numerous sources of NOx emissions, heavy vehicle exhaust emissions are of considerable importance. Heavy vehicles tend to emit significant amounts of NOx due to their relatively high engine power, high fuel consumption, and relatively late exhaust gas treatment technologies (partially older vehicles). Also, since the travel routes of heavy vehicles are relatively concentrated on major roads in cities, the NOx concentration monitored by environmental monitoring sites around these roads is likely to be significantly affected by heavy vehicle emissions. The contribution rate of heavy vehicle emission on different roads around the monitoring station to the NOx concentration of the monitoring station is accurately estimated, and the method has irreplaceable significance for formulating an accurate and effective atmospheric pollution control strategy. This assessment can help environmental authorities define the primary source route for pollution, thereby taking targeted actions such as traffic control for specific roads, optimizing the travel route of heavy vehicles, or improving emission standards for heavy vehicles. However, existing evaluation methods have various limitations. On the one hand, the data utilization is insufficient. The development of the remote on-line monitoring technology of the heavy-duty vehicle enables us to acquire a great deal of detailed data about the running state (such as the speed, the working condition of the engine and the like) of the heavy-duty vehicle and the exhaust emission (such as the real-time NOx emission concentration) and the like, but the current evaluation method mostly fails to fully mine the value of the data. For example, some existing methods may simply use an average emission factor to estimate the NOx emissions of a heavy vehicle without taking into account dynamic changes in the actual emissions of the heavy vehicle under different driving conditions. On the other hand, it is not accurate enough when considering a complex atmospheric diffusion relationship between the road and the monitoring site. The atmospheric diffusion process is affected by a combination of factors including meteorological conditions (e.g., wind speed, wind direction, temperature, humidity, atmospheric stability, etc.), topography (e.g., blockage and influence of different terrains such as mountainous regions, plain, valleys, etc., and buildings such as tall buildings in cities), and underlayment types (e.g., vegetation cover, water surface, concrete pavement, etc.), etc. When the existing evaluation method is used for constructing a model to describe the complex atmospheric diffusion relationship, a simplified assumption or general model parameters are often adopted, and the real relationship between the road emission source and the monitoring station in the specific area cannot be accurately reflected. For example, in some urban central areas, high-rise buildings stand up and wind directions are changeable, and an existing atmospheric diffusion model may not accurately simulate the diffusion process of NOx in heavy vehicle exhaust to a monitoring station in such a complex environment, so that larger deviation and inaccuracy occur in the evaluation of the contribution rate. Disclosure of Invention In view of the above, the embodiment of the invention provides a high-ranking road identification method based on remote on-line monitoring data of a heavy truck, which aims to solve the technical problem of inaccurate contribution rate assessment in the prior art. The method comprises the following steps: dividing the roads around the environmental monitoring site into different road sections according to the space; According to the positioning information of the heavy vehicles of different types and the geographic information of the road section, establishing the corresponding relation between the heavy vehicles of different types and the road section where the heavy vehicles are positioned; Determining the NOx instantaneous emission rate of each type of heavy vehicle in different time intervals of each road section, wherein the NOx instantaneous emission rate of each type of heavy vehicle is obtained by superposition of the NOx instantaneous emission r