Literature DB >> 19557449

Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments.

Diane U Keogh1, Joe Kelly, Kerrie Mengersen, Rohan Jayaratne, Luis Ferreira, Lidia Morawska.   

Abstract

BACKGROUND, AIM AND SCOPE: Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 microm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore, the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions.
MATERIALS AND METHODS: A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions.
RESULTS: This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM(1), PM(2.5) and PM(10), respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes and the explanatory model variables, which were vehicle type (all particle metrics), instrumentation (particle number and PM(2.5)), road type (PM(10)) and size range measured and speed limit on the road (particle volume). DISCUSSION: A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries.
CONCLUSIONS: The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. RECOMMENDATIONS AND PERSPECTIVES: In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for transport modelling and health impact assessments.

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Year:  2009        PMID: 19557449     DOI: 10.1007/s11356-009-0210-9

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  11 in total

1.  A model for determination of motor vehicle emission factors from on-road measurements with a focus on submicrometer particles.

Authors:  M Jamriska; L Morawska
Journal:  Sci Total Environ       Date:  2001-01-17       Impact factor: 7.963

2.  In-use light-duty gasoline vehicle particulate matter emissions on three driving cycles.

Authors:  S H Cadle; P Mulawa; P Groblicki; C Laroo; R A Ragazzi; K Nelson; G Gallagher; B Zielinska
Journal:  Environ Sci Technol       Date:  2001-01-01       Impact factor: 9.028

3.  On-road vehicle particulate matter and gaseous emission distributions in Las Vegas, Nevada, compared with other areas.

Authors:  Claudio Mazzoleni; Hampden D Kuhns; Hans Moosmüller; Robert E Keislar; Peter W Barber; Norman F Robinson; John G Watson; Djordje Nikolic
Journal:  J Air Waste Manag Assoc       Date:  2004-06       Impact factor: 2.235

4.  Diesel bus emissions measured in a tunnel study.

Authors:  Milan Jamriska; Lidia Morawska; Steven Thomas; Congrong He
Journal:  Environ Sci Technol       Date:  2004-12-15       Impact factor: 9.028

5.  Model simulations of NOx and ultrafine particles close to a Swedish highway.

Authors:  L Gidhagen; C Johansson; G Omstedt; J Langner; G Olivares
Journal:  Environ Sci Technol       Date:  2004-12-15       Impact factor: 9.028

6.  Real-world emission factors of fine and ultrafine aerosol particles for different traffic situations in Switzerland.

Authors:  David Imhof; Ernest Weingartner; Carlos Ordónez; Robert Gehrig; Matz Hill; Brigitte Buchmann; Urs Baltensperger
Journal:  Environ Sci Technol       Date:  2005-11-01       Impact factor: 9.028

7.  Quantification of particle number emission factors for motor vehicles from on-road measurements.

Authors:  Lidia Morawska; Milan Jamriska; Stephen Thomas; Luis Ferreira; Kerrie Mengersen; Darren Wraith; Fraser McGregor
Journal:  Environ Sci Technol       Date:  2005-12-01       Impact factor: 9.028

8.  Real-world particulate matter and gaseous emissions from motor vehicles in a highway tunnel.

Authors:  Alan W Gertler; John A Gillies; William R Pierson; C Fred Rogers; John C Sagebiel; Mahmoud Abu-Allaban; William Coulombe; Leland Tarnay; Thomas A Cahill
Journal:  Res Rep Health Eff Inst       Date:  2002-01

9.  On-road particulate matter (PM2.5 and PM10) emissions in the Sepulveda Tunnel, Los Angeles, California.

Authors:  J A Gillies; A W Gertler; J C Sagebiel; W A Dippel
Journal:  Environ Sci Technol       Date:  2001-03-15       Impact factor: 9.028

10.  Emission rates of particulate matter and elemental and organic carbon from in-use diesel engines.

Authors:  Sandip D Shah; David R Cocker; J Wayne Miller; Joseph M Norbeck
Journal:  Environ Sci Technol       Date:  2004-05-01       Impact factor: 9.028

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Journal:  Environ Sci Pollut Res Int       Date:  2015-12-12       Impact factor: 4.223

2.  Modeling particle number concentrations along Interstate 10 in El Paso, Texas.

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Journal:  Atmos Environ (1994)       Date:  2014-12-01       Impact factor: 4.798

3.  Roadside Air Quality Forecasting in Shanghai with a Novel Sequence-to-Sequence Model.

Authors:  Dongsheng Wang; Hong-Wei Wang; Chao Li; Kai-Fa Lu; Zhong-Ren Peng; Juanhao Zhao; Qingyan Fu; Jun Pan
Journal:  Int J Environ Res Public Health       Date:  2020-12-17       Impact factor: 3.390

  3 in total

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