Literature DB >> 31146236

Characterisation of diesel vehicle emissions and determination of remote sensing cutpoints for diesel high-emitters.

Yuhan Huang1, Bruce Organ2, John L Zhou3, Nic C Surawski1, Yat-Shing Yam4, Edward F C Chan5.   

Abstract

Diesel vehicles are a major source of air pollutants in cities and have caused significant health risks to the public globally. This study used both on-road remote sensing and transient chassis dynamometer to characterise emissions of diesel light goods vehicles. A large sample size of 183 diesel vans were tested on a transient chassis dynamometer to evaluate the emission levels of in-service diesel vehicles and to determine a set of remote sensing cutpoints for diesel high-emitters. The results showed that 79% and 19% of the Euro 4 and Euro 5 diesel vehicles failed the transient cycle test, respectively. Most of the high-emitters failed the NO limits, while no vehicle failed the HC limits and only a few vehicles failed the CO limits. Vehicles that failed NO limits occurred in both old and new vehicles. NO/CO2 ratios of 57.30 and 22.85 ppm/% were chosen as the remote sensing cutpoints for Euro 4 and Euro 5 high-emitters, respectively. The cutpoints could capture a Euro 4 and Euro 5 high-emitter at a probability of 27% and 57% with one snapshot remote sensing measurement, while only producing 1% of false high-emitter detections. The probability of high-emitting events was generally evenly distributed over the test cycle, indicating that no particular driving condition produced a higher probability of high-emitting events. Analysis on the effect of cutpoints on real-driving diesel fleet was carried out using a three-year remote sensing program. Results showed that 36% of Euro 4 and 47% of Euro 5 remote sensing measurements would be detected as high-emitting using the proposed cutpoints.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Emission factors; High-emitters identification; Real driving emissions; Transient chassis dynamometer

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Year:  2019        PMID: 31146236     DOI: 10.1016/j.envpol.2019.04.130

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  2 in total

1.  Automatic and Fast Recognition of On-Road High-Emitting Vehicles Using an Optical Remote Sensing System.

Authors:  Hao Xie; Yujun Zhang; Ying He; Kun You; Boqiang Fan; Dongqi Yu; Mengqi Li
Journal:  Sensors (Basel)       Date:  2019-08-13       Impact factor: 3.576

2.  Rapid detection of high-emitting vehicles by on-road remote sensing technology improves urban air quality.

Authors:  Yuhan Huang; Casey K C Lee; Yat-Shing Yam; Wai-Chuen Mok; John L Zhou; Yuan Zhuang; Nic C Surawski; Bruce Organ; Edward F C Chan
Journal:  Sci Adv       Date:  2022-02-02       Impact factor: 14.136

  2 in total

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