Mapping high-resolution urban road carbon and pollutant emissions using travel demand data

Jie Ma, Mengmeng Xu and Jiehui Jiang

Energy, 2023, vol. 263, issue PE

Abstract: Attributed to the residents’ increasing concern on the environment and urban life, urban road carbon and pollutant emissions have been receiving much attention recently. However, because of the diversity of urban road emission sources and the complexity of network topological structure, urban road emissions are hard to be quantitatively measured. This study provides a method that incorporating a traffic assignment problem that uses travel demand data and outputs traffic flow and average speed of different types of vehicles on the road. By using the proposed method, high-resolution, covering temporal and spatial resolution, emission resolution, and vehicle category resolution, vehicle carbon and pollutant emissions can be figured out. The proposed method can be extended to many regions and cities by using corresponding travel demand data. The travel demand data of the largest city in the U.S. state of South Dakota was used to test the method and to figure out the emissions. Numerical analyses were conducted to provide practical insights into traffic emission management, which indicate that network-level road emissions are strongly related to vehicle travel time and travel demand and that mitigating traffic congestion of the urban road network is an effective way to reduce the network-level emissions.

Keywords: Vehicle emissions; Transportation pollutant emissions; Urban road network; Traffic flow; Traffic assignment problem (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:263:y:2023:i:pe:s0360544222029450

DOI: 10.1016/j.energy.2022.126059

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