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

Fanyuan Deng; Zhaofeng Lv; Lijuan Qi; Xiaotong Wang; Mengshuang Shi; Huan Liu

doi:10.1038/s41467-020-16579-w

Nature Communications (Jun 2020)

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

Fanyuan Deng,
Zhaofeng Lv,
Lijuan Qi,
Xiaotong Wang,
Mengshuang Shi,
Huan Liu

Affiliations

Fanyuan Deng: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University
Zhaofeng Lv: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University
Lijuan Qi: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University
Xiaotong Wang: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University
Mengshuang Shi: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University
Huan Liu: State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University

DOI: https://doi.org/10.1038/s41467-020-16579-w
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 12

Abstract

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There lacks a method to measure the rapid changes of vehicle emissions. Here the authors proposed a big data approach ‘TrackATruck’, and their estimates using the new approach show that the heavy-duty trucks (HDT) emissions of primary cargo routes/terminals were underestimated by 2–10 times in proxy-based emission inventories.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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