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Aerosol Science and Technology Volume 45, 2011 - Issue 11
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Original Articles

Comparison of the Chemical and Oxidative Characteristics of Particulate Matter (PM) Collected by Different Methods: Filters, Impactors, and BioSamplers

Nancy Daher Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, California, USA
,
Zhi Ning Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, California, USA
,
Arthur K. Cho Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA
,
Martin Shafer Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
,
James J. Schauer Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
&
Constantinos Sioutas Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, California, USA
Pages 1294-1304 | Received 11 Jan 2011, Accepted 09 May 2011, Published online: 04 Jul 2011

Figures & data

FIG. 1 Schematic of experimental setup.

FIG. 1 Schematic of experimental setup.

FIG. 2 Gravimetric PM2.5 mass concentrations of the filter sample, Nano-MOUDI substrate, and BioSampler slurry (unfiltered). The mass concentration of the BioSampler suspension was determined as the difference in the mass gains of the Teflon filter and the BioSampler “after-filter.”

FIG. 2 Gravimetric PM2.5 mass concentrations of the filter sample, Nano-MOUDI substrate, and BioSampler slurry (unfiltered). The mass concentration of the BioSampler suspension was determined as the difference in the mass gains of the Teflon filter and the BioSampler “after-filter.”

FIG. 3 Average mass fractions of ions in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry). The mass fraction is defined as the mass ratio of a given species to PM2.5. Error bars represent one standard error.

FIG. 3 Average mass fractions of ions in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry). The mass fraction is defined as the mass ratio of a given species to PM2.5. Error bars represent one standard error.

FIG. 4 Average mass fractions of OC and WSOC in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry). Error bars represent one standard error.

FIG. 4 Average mass fractions of OC and WSOC in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry). Error bars represent one standard error.

FIG. 5 (a) Linear regression analysis between the average mass fractions of water-soluble elements in PM2.5 samples from the filter and Nano-MOUDI. Standard errors are shown in parentheses. Plot is presented on a log-log scale. (b) Linear regression analyses between the average mass fractions of water-soluble and recoverable elements in PM2.5 samples from the filter–BioSampler (unfiltered slurry) and Nano-MOUDI–BioSampler (unfiltered slurry). Standard errors are shown in parentheses. Plots are presented on a log-log scale.

FIG. 5 (a) Linear regression analysis between the average mass fractions of water-soluble elements in PM2.5 samples from the filter and Nano-MOUDI. Standard errors are shown in parentheses. Plot is presented on a log-log scale. (b) Linear regression analyses between the average mass fractions of water-soluble and recoverable elements in PM2.5 samples from the filter–BioSampler (unfiltered slurry) and Nano-MOUDI–BioSampler (unfiltered slurry). Standard errors are shown in parentheses. Plots are presented on a log-log scale.

FIG. 6 Average mass fractions of total and recoverable elements in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry; on primary axis in log scale) in addition to the water-solubility fraction of elements as computed from filter measurements (on secondary axis).

FIG. 6 Average mass fractions of total and recoverable elements in PM2.5 samples from the filter, Nano-MOUDI, and BioSampler (unfiltered slurry; on primary axis in log scale) in addition to the water-solubility fraction of elements as computed from filter measurements (on secondary axis).

FIG. 7 ROS response (in μg of Zymosan units per mg of PM analyzed per sample) of the water extracts of the filter and Nano-MOUDI PM2.5 samples as well as the unfiltered and filtered BioSampler PM2.5 slurry. Error bars represent one standard error.

FIG. 7 ROS response (in μg of Zymosan units per mg of PM analyzed per sample) of the water extracts of the filter and Nano-MOUDI PM2.5 samples as well as the unfiltered and filtered BioSampler PM2.5 slurry. Error bars represent one standard error.

FIG. 8 DTT consumption and DHBA formation rates (in nmol/min/mg of PM analyzed per sample) of the water extracts of the filter and Nano-MOUDI PM2.5 samples and the unfiltered BioSampler PM2.5 slurry. Error bars represent one standard error.

FIG. 8 DTT consumption and DHBA formation rates (in nmol/min/mg of PM analyzed per sample) of the water extracts of the filter and Nano-MOUDI PM2.5 samples and the unfiltered BioSampler PM2.5 slurry. Error bars represent one standard error.

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Related Research Data

Development of a Two-Stage Virtual Impactor System for High Concentration Enrichment of Ultrafine, PM2.5, and Coarse Particulate Matter
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