A methodology to relate black carbon particle number and mass emissions. (June 2019)
- Record Type:
- Journal Article
- Title:
- A methodology to relate black carbon particle number and mass emissions. (June 2019)
- Main Title:
- A methodology to relate black carbon particle number and mass emissions
- Authors:
- Teoh, Roger
Stettler, Marc E.J.
Majumdar, Arnab
Schumann, Ulrich
Graves, Brian
Boies, Adam M. - Abstract:
- 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. Graphical abstract: Image 1Abstract: 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. Graphical abstract: Image 1 Highlights: Critical review of fractal aggregate theory. New method to relate black carbon (BC) particle number and mass emissions. Validation of the new methodology with measurements from four BC emission sources. Uncertainty and sensitivity analyses identifies parameters contributing to variance. Applications of the new model include particle number emissions for aviation. … (more)
- Is Part Of:
- Journal of aerosol science. Volume 132(2019)
- Journal:
- Journal of aerosol science
- Issue:
- Volume 132(2019)
- Issue Display:
- Volume 132, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 132
- Issue:
- 2019
- Issue Sort Value:
- 2019-0132-2019-0000
- Page Start:
- 44
- Page End:
- 59
- Publication Date:
- 2019-06
- Subjects:
- Black carbon -- Particle number -- Particle mass -- Fractal aggregates -- Combustion emissions
Aerosols -- Periodicals
Aerosols -- Periodicals
Aérosols -- Périodiques
541.34515 - Journal URLs:
- http://www.journals.elsevier.com/journal-of-aerosol-science/ ↗
http://www.sciencedirect.com/science/journal/00218502 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jaerosci.2019.03.006 ↗
- Languages:
- English
- ISSNs:
- 0021-8502
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4919.060000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9834.xml