Document Detail


Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments.
MedLine Citation:
PMID:  19557449     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Diane U Keogh; Joe Kelly; Kerrie Mengersen; Rohan Jayaratne; Luis Ferreira; Lidia Morawska
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-06-26
Journal Detail:
Title:  Environmental science and pollution research international     Volume:  17     ISSN:  1614-7499     ISO Abbreviation:  Environ Sci Pollut Res Int     Publication Date:  2010 Mar 
Date Detail:
Created Date:  2010-02-17     Completed Date:  2010-03-31     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9441769     Medline TA:  Environ Sci Pollut Res Int     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  724-39     Citation Subset:  IM    
Affiliation:
International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Queensland, 4000, Australia.
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MeSH Terms
Descriptor/Qualifier:
Air Pollutants / analysis,  chemistry*,  classification
Air Pollution / statistics & numerical data
Cities
Environmental Monitoring / methods
Models, Chemical
Models, Statistical
Particle Size
Particulate Matter / analysis,  chemistry*,  classification
Vehicle Emissions / analysis*
Chemical
Reg. No./Substance:
0/Air Pollutants; 0/Particulate Matter; 0/Vehicle Emissions

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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