A methodology to relate black carbon particle number and mass emissions
File(s)
Supporting information
Accepted version
Author(s)
Type
Journal Article
Abstract
Black carbon (BC) particle number (PN) emissions from various sources contribute to the deterioration of air quality, adverse health effects, and anthropogenic climate change. This paper critically reviews different fractal aggregate theories to develop a new methodology that relates BC PN and mass concentrations (or emissions factors). The new methodology, named as the fractal aggregate (FA) model is validated with measurements from three different BC emission sources: an internal combustion engine, a soot generator, and two aircraft gas turbine engines at ground and cruise conditions. Validation results of the FA model show that R 2 values range from 0.44 to 0.95, while the Normalised Mean Bias is between −27.7% and +26.6%. The model estimates for aircraft gas turbines represent a significant improvement compared to previous methodologies used to estimate aviation BC PN emissions, which relied on simplified assumptions. Uncertainty and sensitivity analyses show that the FA model estimates have an asymmetrical uncertainty bound (−54%,+103%) at a 95% confidence interval for aircraft gas turbine engines and are most sensitive to uncertainties in the geometric standard deviation of the BC particle size distribution. Given the improved performance in estimating BC PN emissions from various sources, we recommend the implementation of the FA model in future health and climate assessments, where the impacts of PN are significant.
Date Issued
2019-06-01
Date Acceptance
2019-03-19
Citation
Journal of Aerosol Science, 2019, 132 (1), pp.44-59
ISSN
0021-8502
Publisher
Elsevier
Start Page
44
End Page
59
Journal / Book Title
Journal of Aerosol Science
Volume
132
Issue
1
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Lloyd's Register Foundation
Identifier
https://www.sciencedirect.com/science/article/pii/S0021850218304336?via%3Dihub
Grant Number
GA\100086
Subjects
Science & Technology
Technology
Life Sciences & Biomedicine
Physical Sciences
Engineering, Chemical
Engineering, Mechanical
Environmental Sciences
Meteorology & Atmospheric Sciences
Engineering
Environmental Sciences & Ecology
Black carbon
Particle number
Particle mass
Fractal aggregates
Combustion emissions
PARTICULATE MATTER EMISSIONS
EFFECTIVE DENSITY
AIR-POLLUTION
AIRCRAFT ENGINES
DIESEL-ENGINES
GAS-TURBINE
MOBILITY
SOOT
SIZE
AEROSOL
Meteorology & Atmospheric Sciences
0306 Physical Chemistry (incl. Structural)
0401 Atmospheric Sciences
0904 Chemical Engineering
Publication Status
Published
Date Publish Online
2019-03-22