Preprints
https://doi.org/10.5194/acp-2021-533
https://doi.org/10.5194/acp-2021-533

  13 Aug 2021

13 Aug 2021

Review status: a revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Hyperfine-Resolution Mapping of On-Road Vehicle Emissions with Comprehensive Traffic Monitoring and Intelligent Transportation System

Linhui Jiang1, Yan Xia1, Lu Wang1, Xue Chen1, Jianjie Ye5, Tangyan Hou1, Liqiang Wang1, Yibo Zhang1, Mengying Li1, Zhen Li1, Zhe Song1, Yaping Jiang1, Weiping Liu1, Pengfei Li3, Daniel Rosenfeld4, John H. Seinfeld2, and Shaocai Yu1,2 Linhui Jiang et al.
  • 1Research Center for Air Pollution and Health; Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
  • 2Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
  • 3College of Science and Technology, Hebei Agricultural University, Baoding, Hebei 071000, P.R. China
  • 4Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
  • 5Bytedance Inc., Hangzhou, Zhejiang 310058, China

Abstract. Urban on-road vehicle emissions affect air quality and human health locally and globally. Such emissions typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m ~ 1 km). However, all-around observational constraints on the emission sources are limited in much of the world. Consequently, traditional emission inventories lack the spatial resolution that can characterize on-road vehicle emission hotspots. Here we establish a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at 1 ~ 3 orders of magnitude higher spatial resolution than current inventories. We interconnect all-around traffic monitoring (including traffic fluxes, vehicle-specific categories, and speeds) via an intelligent transportation system (ITS) over the Xiaoshan District in the Yangtze River Delta (YRD) region. This enables us to calculate single-vehicle-specific emissions over each fine-scale (10 m ~ 1 km) road segment. Thus, a hyperfine emission dataset is achieved, and on-road emission hotspots appear. The resulting map shows that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74.01 kg, 40.35 kg, 8.13 kg, and 1.68 kg, respectively. More importantly, widespread and persistent emission hotspots emerge, of significantly sharp small-scale variability, up to 8 ~ 15 times, attributable to distinct traffic fluxes, road conditions, and vehicle categories. On this basis, we investigate the effectiveness of routine traffic control strategies on the on-road vehicle emission mitigation. Our results have important implications for how the strategies should be designed and optimized. Integrating our traffic-monitoring-based approach with urban air quality measurements, we could address major data gaps between urban air pollutant emissions and concentrations.

Linhui Jiang et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-533', Shunxiang Huang, 30 Aug 2021
    • AC1: 'Reply on RC1', Shaocai Yu, 14 Sep 2021
      • AC3: 'Reply on AC1', Shaocai Yu, 14 Sep 2021
  • RC2: 'Comment on acp-2021-533', Anonymous Referee #2, 02 Sep 2021
    • AC2: 'Reply on RC2', Shaocai Yu, 14 Sep 2021
      • AC4: 'Reply on AC2', Shaocai Yu, 14 Sep 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-533', Shunxiang Huang, 30 Aug 2021
    • AC1: 'Reply on RC1', Shaocai Yu, 14 Sep 2021
      • AC3: 'Reply on AC1', Shaocai Yu, 14 Sep 2021
  • RC2: 'Comment on acp-2021-533', Anonymous Referee #2, 02 Sep 2021
    • AC2: 'Reply on RC2', Shaocai Yu, 14 Sep 2021
      • AC4: 'Reply on AC2', Shaocai Yu, 14 Sep 2021

Linhui Jiang et al.

Linhui Jiang et al.

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Short summary
This paper establishes a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at 1 ~ 3 orders of magnitude higher spatial resolution than current inventories. The results show that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74 kg, 40 kg, 8 kg, and 2 kg, respectively. Integrating our traffic-monitoring-based approach with urban measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
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