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Aerosol Particle Measurements: Strategies for Health-Relevant Data Collection and Analysis


Grantz Pansing, Amanda (2019) Aerosol Particle Measurements: Strategies for Health-Relevant Data Collection and Analysis. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Y730-W245.


Particulate matter (PM) is an important component of outdoor and indoor air pollution that can cause significant harm to human health. The present work, organized into two parts, introduces strategies for optimizing the collection and analysis of airborne particle measurements to inform PM health-effect research.

Part I focuses on the fundamental aerosol data analysis task of interpreting indirect measurements of particle size to reveal the distribution of sizes of particles in a sampled aerosol. An approach to this aerosol data inversion problem is developed that shows improved particle size distribution recovery compared to other common approaches described in the literature. This inverse solution method incorporates cubic spline interpolation to represent the particle size distribution within a discrete linear model of the inverse problem while placing no constraints on the number or spacing of solution points. The inverse problem setup can then interface with three established numerical methods for solution computation. The accuracy of this procedure is demonstrated through analysis of test-case data for differential mobility analyzer systems. Source code and supporting documentation are also provided to encourage researchers to use and adapt this inversion algorithm for analyzing data collected from existing as well as potential future measurement systems.

Part II of this work focuses on the retrieval of health-relevant information from aerosol particle measurement data. The inversion analysis introduced in Part I is incorporated into an extended analysis procedure for evaluating the metrics of PM exposure and respiratory dose that can be obtained from different measurement systems. Applying this evaluation procedure to a range of existing and potential future measurement techniques reveals that full characterization of particle size distributions need not be time and resource intensive and should be pursued for the great benefits this information would provide to health studies. Not only can size distribution information permit lung tissue dose estimates through a set of relatively simple calculations, but a single set of size distribution data can be analyzed and reanalyzed to provide dose estimates for human populations of interest by applying the appropriate respiratory tract deposition profiles. The measurement evaluation procedure developed here reveals target criteria for the particle characterization necessary to provide sufficient exposure and dose information for health studies. The intent is not to eliminate the current measurements and standards, but to help direct future developments in health-related aerosol particle measurement design.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Aerosol Particle Measurements, Data Inversion, PM Health Effects
Degree Grantor:California Institute of Technology
Division:Chemistry and Chemical Engineering
Major Option:Chemical Engineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Flagan, Richard C.
Thesis Committee:
  • Seinfeld, John H. (chair)
  • Wennberg, Paul O.
  • Davis, Mark E.
  • Flagan, Richard C.
Defense Date:23 May 2019
Record Number:CaltechTHESIS:06072019-161940566
Persistent URL:
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11720
Deposited By: Amanda Grantz
Deposited On:10 Jun 2019 22:22
Last Modified:04 Oct 2019 00:26

Thesis Files

PDF (full thesis) - Final Version
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[img] Archive (ZIP) (Data inversion code prepared in Igor Pro (Wavemetrics)) - Supplemental Material
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