Abstract
Previous work successfully implemented a novel system that uses a single particle mass spectrometer to conditionally sample size-segregated, source-oriented particles from the ambient atmosphere in real-time. The underlying hypothesis is that the composition of individual particles is a metric of particle source and thus sampling particles based on composition should be synonymous with sampling based on source. System operation relies on real-time pattern recognition to control the actuation of different ChemVol samplers, where each ChemVol is associated with a unique composition signature. In the current work, a synthesis of data collected during these studies is used in retrospect to reconcile the actual source combinations contributing to the particles collected by each ChemVol. Source attribution is based on correlations between ChemVol sampling periods and coincident wind direction and temporal emissions patterns, coupled to knowledge of single particle composition and surrounding sources. Residential and commercial cooking, vehicular emissions, residential heating and highly processed regional background PM were identified as the major sources. Results show that real-time patterns in single particle mixing state correctly identified specific sources and that these sources were successfully separated into different ChemVols for both summer and winter seasons.
| Original language | English (US) |
|---|---|
| Article number | 14034 |
| Pages (from-to) | 228-239 |
| Number of pages | 12 |
| Journal | Atmospheric Environment |
| Volume | 119 |
| DOIs | |
| State | Published - Oct 1 2015 |
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Keywords
- Aerosol health effects
- Fresno air quality
- Single particle mass spectrometry
- Source attribution
- Source-oriented sampling
ASJC Scopus subject areas
- Atmospheric Science
- Environmental Science(all)
Cite this
Retrospective source attribution for source-oriented sampling. / Bein, K. J.; Zhao, Y.; Wexler, A. S.
In: Atmospheric Environment, Vol. 119, 14034, 01.10.2015, p. 228-239.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Retrospective source attribution for source-oriented sampling
AU - Bein, K. J.
AU - Zhao, Y.
AU - Wexler, A. S.
PY - 2015/10/1
Y1 - 2015/10/1
N2 - Previous work successfully implemented a novel system that uses a single particle mass spectrometer to conditionally sample size-segregated, source-oriented particles from the ambient atmosphere in real-time. The underlying hypothesis is that the composition of individual particles is a metric of particle source and thus sampling particles based on composition should be synonymous with sampling based on source. System operation relies on real-time pattern recognition to control the actuation of different ChemVol samplers, where each ChemVol is associated with a unique composition signature. In the current work, a synthesis of data collected during these studies is used in retrospect to reconcile the actual source combinations contributing to the particles collected by each ChemVol. Source attribution is based on correlations between ChemVol sampling periods and coincident wind direction and temporal emissions patterns, coupled to knowledge of single particle composition and surrounding sources. Residential and commercial cooking, vehicular emissions, residential heating and highly processed regional background PM were identified as the major sources. Results show that real-time patterns in single particle mixing state correctly identified specific sources and that these sources were successfully separated into different ChemVols for both summer and winter seasons.
AB - Previous work successfully implemented a novel system that uses a single particle mass spectrometer to conditionally sample size-segregated, source-oriented particles from the ambient atmosphere in real-time. The underlying hypothesis is that the composition of individual particles is a metric of particle source and thus sampling particles based on composition should be synonymous with sampling based on source. System operation relies on real-time pattern recognition to control the actuation of different ChemVol samplers, where each ChemVol is associated with a unique composition signature. In the current work, a synthesis of data collected during these studies is used in retrospect to reconcile the actual source combinations contributing to the particles collected by each ChemVol. Source attribution is based on correlations between ChemVol sampling periods and coincident wind direction and temporal emissions patterns, coupled to knowledge of single particle composition and surrounding sources. Residential and commercial cooking, vehicular emissions, residential heating and highly processed regional background PM were identified as the major sources. Results show that real-time patterns in single particle mixing state correctly identified specific sources and that these sources were successfully separated into different ChemVols for both summer and winter seasons.
KW - Aerosol health effects
KW - Fresno air quality
KW - Single particle mass spectrometry
KW - Source attribution
KW - Source-oriented sampling
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U2 - 10.1016/j.atmosenv.2015.08.051
DO - 10.1016/j.atmosenv.2015.08.051
M3 - Article
AN - SCOPUS:84939862767
VL - 119
SP - 228
EP - 239
JO - Atmospheric Environment
JF - Atmospheric Environment
SN - 1352-2310
M1 - 14034
ER -