• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 2
  • Tagged with
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The Characterization of Fine Particulate Matter in Toronto Using Single Particle Mass Spectrometry

Rehbein, Peter J. G. 13 January 2011 (has links)
An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was used to obtain mass spectra of individual aerosol particles in the 0.5 – 2 µm size range in downtown Toronto, Canada for one to two month periods during each season of 2007. A modified version of the Adaptive Resonance Theory (ART-2a) clustering algorithm, which clusters particles based on the similarity of their mass spectra, was shown to be more accurate than the existing algorithm and was used to cluster the ambient data. A total of 21 unique particle types were identified and were characterized based on their chemical composition, their size, and their temporal trends and seasonal variations. Potential sources are also discussed. Particles containing trimethylamine (TMA) were also observed and a more detailed investigation of ambient trends in conjunction with a laboratory experiment was performed in order to elucidate conditions for which TMA will be observed in the particle phase in Southern Ontario.
2

The Characterization of Fine Particulate Matter in Toronto Using Single Particle Mass Spectrometry

Rehbein, Peter J. G. 13 January 2011 (has links)
An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was used to obtain mass spectra of individual aerosol particles in the 0.5 – 2 µm size range in downtown Toronto, Canada for one to two month periods during each season of 2007. A modified version of the Adaptive Resonance Theory (ART-2a) clustering algorithm, which clusters particles based on the similarity of their mass spectra, was shown to be more accurate than the existing algorithm and was used to cluster the ambient data. A total of 21 unique particle types were identified and were characterized based on their chemical composition, their size, and their temporal trends and seasonal variations. Potential sources are also discussed. Particles containing trimethylamine (TMA) were also observed and a more detailed investigation of ambient trends in conjunction with a laboratory experiment was performed in order to elucidate conditions for which TMA will be observed in the particle phase in Southern Ontario.

Page generated in 0.1102 seconds