Potential of big data approach for remote sensing of vehicle exhaust emissions.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
09 03 2021
Historique:
received: 05 11 2020
accepted: 22 02 2021
entrez: 22 3 2021
pubmed: 23 3 2021
medline: 23 3 2021
Statut: epublish

Résumé

At present, remote sensing (RS) is applied in detecting vehicle exhaust emissions, and usually the RS emission results in a definite vehicle specific power (VSP) range are used to evaluate vehicle emissions and identify high-emitting vehicles. When the VSP exceeds this range, the corresponding vehicle emission RS data will not be used to assess vehicle emissions. This method is equivalent to setting only one VSP Bin qualified for vehicle emission evaluation, and generally only one threshold limit is given for each emission pollutant without considering the fluctuation characteristics of vehicle emissions with VSP. Therefore, it is easy to cause misjudgment in identifying high-emitting vehicles and is not conducive to scientific management of vehicle emissions. In addition, the vehicle emissions outside the selected VSP Bin are more serious and should be included in the scope of supervision. This research proposed the methods of vehicle classifications and VSP Binning in order to categorize the driving conditions of each kind of vehicles, and a big data approach was proposed to analyze the vehicle emission RS data in each VSP Bin for vehicle emission evaluation.

Identifiants

pubmed: 33750845
doi: 10.1038/s41598-021-84890-7
pii: 10.1038/s41598-021-84890-7
pmc: PMC7970906
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5472

Références

Environ Sci Technol. 1995 Sep 1;29(9):2286-94
pubmed: 22280268
Anal Chem. 1989 May 15;61(10):671A-677A
pubmed: 2473669
J Air Waste Manag Assoc. 1999 Dec;49(12):1463-1468
pubmed: 28060639
Environ Pollut. 2018 Dec;243(Pt B):1177-1185
pubmed: 30266007

Auteurs

Lijun Hao (L)

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China. haolijun@bit.edu.cn.

Hang Yin (H)

State Environmental Protection Key Laboratory of Vehicles Being Driven on the Road Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.

Junfang Wang (J)

State Environmental Protection Key Laboratory of Vehicles Being Driven on the Road Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.

Xiaohu Wang (X)

Anhui Baolong Environmental Protection Technology Co., Ltd., Hefei, 230031, China.

Yunshan Ge (Y)

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China.

Classifications MeSH