SPATIOTEMPORAL EMISSION CHARACTERISTICS ANALYSIS IN BOTTLENECK NODES OF HIGHWAY FREIGHT

DUAN Kaixin; SONG Guohua; ZHAI Zhiqiang; LU Miao

doi:10.13205/j.hjgc.202410011

Volume 42 Issue 10

Oct. 2024

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2024 > 42(10): 83-91

DUAN Kaixin, SONG Guohua, ZHAI Zhiqiang, LU Miao. SPATIOTEMPORAL EMISSION CHARACTERISTICS ANALYSIS IN BOTTLENECK NODES OF HIGHWAY FREIGHT[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(10): 83-91. doi: 10.13205/j.hjgc.202410011

Citation:

DUAN Kaixin, SONG Guohua, ZHAI Zhiqiang, LU Miao. SPATIOTEMPORAL EMISSION CHARACTERISTICS ANALYSIS IN BOTTLENECK NODES OF HIGHWAY FREIGHT[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(10): 83-91. doi: 10.13205/j.hjgc.202410011

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SPATIOTEMPORAL EMISSION CHARACTERISTICS ANALYSIS IN BOTTLENECK NODES OF HIGHWAY FREIGHT

doi: 10.13205/j.hjgc.202410011

Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of Transport, Beijing Jiaotong University, Beijing 100044, China

Received Date: 2023-12-03
Available Online: 2024-11-30

Abstract

Abstract

Studying the emission generation mechanism and dispersion features in the bottleneck nodes of highway freight can provide a theoretical basis for pollution joint prevention and control in highway emission hotspots. To achieve the dynamic portrayal of spatial-temporal emissions, second-by-second driving data, and heavy-duty diesel vehicle emission test data were collected from Beijing’s key freight road network, then, based on the characterization of congestion formation and dissipation, a quantification index of emission intensity in different driving conditions (deceleration, acceleration, and idling) was designed. Furthermore, an emission spatial-temporal distribution model based on the vehicle specific power was built. Finally, taking the Xiji Comprehensive Inspection Station in Tongzhou District Beijing as a case, we compared the changes in the spatial-temporal emissions(CO₂, CO, THC, NO_x) before and after the establishment of the station, and the adoption of two emission reduction measures(sampling and enhancing service efficiency). The results showed that the total emissions at the bottleneck nodes were 2.2 to 2.5 times higher than the conventional ones. The queuing area in front of the bottleneck and 0~10 m behind it had the maximum emission intensity, which was 2.1 to 2.9 times higher than the decelerated and bottleneck operating areas. To a certain extent, sampling and enhancing service efficiency can reduce polution emissions. Moreover, both of the emission reduction strategies significantly improve NO_x emission reduction effect.
- highway freight,
- traffic bottleneck,
- spatial-temporal distribution model of emission,
- heavy-duty vehicles,
- emission intensity,
- driving conditions

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References(27)

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