IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-16579-w.html
   My bibliography  Save this article

A big data approach to improving the vehicle emission inventory in China

Author

Listed:
  • Fanyuan Deng

    (Tsinghua University)

  • Zhaofeng Lv

    (Tsinghua University)

  • Lijuan Qi

    (Tsinghua University)

  • Xiaotong Wang

    (Tsinghua University)

  • Mengshuang Shi

    (Tsinghua University)

  • Huan Liu

    (Tsinghua University)

Abstract

Estimating truck emissions accurately would benefit atmospheric research and public health protection. Here, we developed a full-sample enumeration approach TrackATruck to bridge low-frequency but full-size vehicles driving big data to high-resolution emission inventories. Based on 19 billion trajectories, we show how big the emission difference could be using different approaches: 99% variation coefficients on regional total (including 31% emissions from non-local trucks), and ± as large as 15 times on individual counties. Even if total amounts are set the same, the emissions on primary cargo routes were underestimated in the former by a multiple of 2–10 using aggregated approaches. Time allocation proxies are generated, indicating the importance of day-to-day estimation because the variation reached 26-fold. Low emission zone policy reduced emissions in the zone, but raised emissions in upwind areas in Beijing's case. Comprehensive measures should be considered, e.g. the demand-side optimization.

Suggested Citation

  • Fanyuan Deng & Zhaofeng Lv & Lijuan Qi & Xiaotong Wang & Mengshuang Shi & Huan Liu, 2020. "A big data approach to improving the vehicle emission inventory in China," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16579-w
    DOI: 10.1038/s41467-020-16579-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-16579-w
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-16579-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mengru Shao & Chao Chen & Qingchang Lu & Xinyu Zuo & Xueling Liu & Xiaoning Gu, 2023. "The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    2. Liu, Geng & Sun, Shida & Zou, Chao & Wang, Bo & Wu, Lin & Mao, Hongjun, 2022. "Air pollutant emissions from on-road vehicles and their control in Inner Mongolia, China," Energy, Elsevier, vol. 238(PB).
    3. Lu Wang & Xue Chen & Yan Xia & Linhui Jiang & Jianjie Ye & Tangyan Hou & Liqiang Wang & Yibo Zhang & Mengying Li & Zhen Li & Zhe Song & Yaping Jiang & Weiping Liu & Pengfei Li & Xiaoye Zhang & Shaocai, 2022. "Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
    4. Xiaoyu Long & Luyao Wang & Weipeng Li, 2023. "Geographical Influences on Job–Housing Balance: A Study of Coastal Urban Areas in Boston," Sustainability, MDPI, vol. 15(22), pages 1-21, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16579-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.