Literature DB >> 26844787

Quantification of vehicle fleet PM10 particulate matter emission factors from exhaust and non-exhaust sources using tunnel measurement techniques.

Samantha Lawrence1, Ranjeet Sokhi1, Khaiwal Ravindra2.   

Abstract

Road tunnels act like large laboratories; they provide an excellent environment to quantify atmospheric particles emission factors from exhaust and non-exhaust sources due to their known boundary conditions. Current work compares the High Volume, Dichotomous Stacked Filter Unit and Partisol Air Sampler for coarse, PM10 and PM2.5 particle concentration measurement and found that they do not differ significantly (p = 95%). PM2.5 fraction contributes 66% of PM10 proportions and significantly influenced by traffic (turbulence) and meteorological conditions. Mass emission factors for PM10 varies from 21.3 ± 1.9 to 28.8 ± 3.4 mg/vkm and composed of Motorcycle (0.0003-0.001 mg/vkm), Cars (26.1-33.4 mg/vkm), LDVs (2.4-3.0 mg/vkm), HDVs (2.2-2.8 mg/vkm) and Buses (0.1 mg/vkm). Based on Lawrence et al. (2013), source apportionment modelling, the PM10 emission of brake wear (3.8-4.4 mg/vkm), petrol exhaust (3.9-4.5 mg/vkm), diesel exhaust (7.2-8.3 mg/vkm), re-suspension (9-10.4 mg/vkm), road surface wear (3.9-4.5 mg/vkm), and unexplained (7.2 mg/vkm) were also calculated. The current study determined that the combined non-exhaust fleet PM10 emission factor (16.7-19.3 mg/vkm) are higher than the combined exhaust emission factor (11.1-12.8 mg/vkm). Thus, highlight the significance of non-exhaust emissions and the need for legislation and abatement strategies to reduce their contributions to ambient PM concentrations.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Brakewear; Emission factors; Non-exhaust; PM(10) and PM(2.5); Re-suspension; Road surface; Tukey mean-difference (Bland and Altman) plot

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Year:  2016        PMID: 26844787     DOI: 10.1016/j.envpol.2016.01.011

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


  2 in total

1.  Assessment of GHG mitigation and CDM technology in urban transport sector of Chandigarh, India.

Authors:  Nitin Bhargava; Bhola Ram Gurjar; Suman Mor; Khaiwal Ravindra
Journal:  Environ Sci Pollut Res Int       Date:  2017-10-16       Impact factor: 4.223

2.  Land Use Regression Modelling of Outdoor NO₂ and PM2.5 Concentrations in Three Low Income Areas in the Western Cape Province, South Africa.

Authors:  Apolline Saucy; Martin Röösli; Nino Künzli; Ming-Yi Tsai; Chloé Sieber; Toyib Olaniyan; Roslynn Baatjies; Mohamed Jeebhay; Mark Davey; Benjamin Flückiger; Rajen N Naidoo; Mohammed Aqiel Dalvie; Mahnaz Badpa; Kees de Hoogh
Journal:  Int J Environ Res Public Health       Date:  2018-07-10       Impact factor: 3.390

  2 in total

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