@article{23035,
  author = {George A Ban-Weiss and Melissa M Lunden and Thomas W Kirchstetter and Robert A Harley},
  title = {Measurement of Black Carbon and Particle Number Emission Factors from Individual Heavy-Duty Trucks},
  abstract = {<p>Emission factors for black carbon (BC) and particle number (PN) were measured from 226 individual heavy-duty (HD) diesel trucks driving through a 1-km-long California highway tunnel in August 2006. Emission factors were based on concurrent increases in BC, PN, and CO<sub>2</sub> concentrations (measured at 1 Hz) that corresponded to the passage of individual HD trucks. The distributions of BC and PN emission factors from individual HD trucks are skewed, meaning that a large fraction of pollution comes from a small fraction of the in-use vehicle fleet. The highest-emitting 10% of trucks were responsible for ∼40% of total BC and PN emissions from all HD trucks. BC emissions were log-normally distributed with a mean emission factor of 1.7 g kg<sup>−1</sup> and maximum values of ∼10 g kg<sup>−1</sup>. Corresponding values for PN emission factors were 4.7 × 10<sup>15</sup> and 4 × 10<sup>16</sup> # kg<sup>−1</sup>. There was minimal overlap among high-emitters of these two pollutants: only 1 of the 226 HD trucks measured was found to be among the highest 10% for both BC and PN. Monte Carlo resampling of the distribution of BC emission factors observed in this study revealed that uncertainties (1σ) in extrapolating from a random sample of <em>n</em> HD trucks to a population mean emission factor ranged from ± 43% for <em>n</em> = 10 to ± 8% for <em>n</em> = 300, illustrating the importance of vehicle sample sizes in emissions studies. When <em>n</em> = 10, sample means are more likely to be biased due to misrepresentation of high-emitters. As vehicles become cleaner on average in the future, skewness of the emissions distributions will increase, and thus sample sizes needed to extrapolate reliably from a subset of vehicles to the entire in-use vehicle fleet will become more of a challenge.</p>},
  year = {2009},
  journal = {Environmental Science and Technology},
  volume = {43},
  pages = {1419-1424},
  month = {03/2009},
  doi = {10.1021/es8021039},
}