Currently, a lack of accurate emission data exits for particulate matter (PM) in
agricultural air quality studies (USDA-AAQTF, 2000). PM samplers, however, tend to
over estimate the concentration of most agricultural dusts because of the interaction of
the particle size distribution (PSD) and performance characteristics of the sampler
(Buser, 2004). This research attempts to find a practical method to characterize and
correct this error for the Federal Reference Method (FRM) PM10 sampler. First, a new
dust wind tunnel testing facility that satisfies the USEPA’s requirement of testing PM10
samplers was designed, built, and evaluated. Second, the wind tunnel testing protocol
using poly-dispersed aerosol as the test dust was proved to be able to provide results
consistent with mono-dispersed dusts. Third, this study quantified the variation of over
sampling ratios for the various cut point and slopes of FRM PM10 samplers and proposed
an averaged over sampling ratio as a correction factor for various ranges of PSD. Finally,
a method of using total suspended particle (TSP) samplers as a field reference for
determining PM10 concentrations and aerosol PSD was explored computationally. Overall, this dissertation developed successfully the methodology to correct the
sampling error associated with the FRM PM10 sampler: (1) wind tunnel testing facilities
and protocol for experimental evaluation of samplers; (2) the variation of the oversampling
ratios of FRM PM10 samplers for computational evaluation of samplers; (3) the
evaluation of TSP sampler effectiveness as a potential field reference for field evaluation
of samplers.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1424 |
| Date | 15 May 2009 |
| Creators | Chen, Jing |
| Contributors | Bryan, Shaw W |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
Page generated in 0.0032 seconds