Mulivariate receptor modeling of SCAQS VOC and airborne particle composition data. Final report
Abstract
USC used speciated Volatile Organic Carbon (VOC) gaseous phase and secondary particulate matter size fraction less than ten micron (PM10) data collected during the 1987 Southern California Air Quality Study (SCAQS) to determine the composition of gaseous and airborne particles. USC used the Source Apportionment by Factors with Explicit Restrictions (SAFER) and the Source Identification through Empirical Orthogonal Functions (SITEOF) source-receptor models that use basic physical constraints (source compositions) to narrow the types of solutions they provide. Roadway (tailpipe plus running evaporative) emissions, whole gasoline, and gasoline vapor, were found to be responsible for most of the ambient VOC; and higher proportion of evaporative emissions in the afternoons which is consistent with higher emissions from parked vehicles at higher afternoon temperatures. Roadway (direct tailpipe plus re-entrained road dust) emissions and soil defined as all crustal materials not directly associated with roadways, were found to be responsible for most of the non-PM10. The SAFER model was successfully applied; the SITEOF model was unsuccessful because it could not use the wind fields from the SCAQS data.
- Authors:
- Publication Date:
- Research Org.:
- Univ. of Southern California, Los Angeles, CA (US); California State Air Resources Board, Sacramento, CA (US)
- OSTI Identifier:
- 20005930
- Report Number(s):
- PB-99-163685/XAB
Contract ARB-A832-131; TRN: IM200006%%22
- Resource Type:
- Technical Report
- Resource Relation:
- Other Information: See also PB94-156700. Sponsored by California State Air Resources Board, Sacramento. Research Div.; PBD: Jan 1999
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; CALIFORNIA; PARTICULATES; VOLATILE MATTER; ORGANIC COMPOUNDS; ECOLOGICAL CONCENTRATION; AEROSOL MONITORING; AIR QUALITY; GASOLINE; EXHAUST GASES
Citation Formats
Henry, R C, Mi, Y, and Moran, W. Mulivariate receptor modeling of SCAQS VOC and airborne particle composition data. Final report. United States: N. p., 1999.
Web.
Henry, R C, Mi, Y, & Moran, W. Mulivariate receptor modeling of SCAQS VOC and airborne particle composition data. Final report. United States.
Henry, R C, Mi, Y, and Moran, W. 1999.
"Mulivariate receptor modeling of SCAQS VOC and airborne particle composition data. Final report". United States.
@article{osti_20005930,
title = {Mulivariate receptor modeling of SCAQS VOC and airborne particle composition data. Final report},
author = {Henry, R C and Mi, Y and Moran, W},
abstractNote = {USC used speciated Volatile Organic Carbon (VOC) gaseous phase and secondary particulate matter size fraction less than ten micron (PM10) data collected during the 1987 Southern California Air Quality Study (SCAQS) to determine the composition of gaseous and airborne particles. USC used the Source Apportionment by Factors with Explicit Restrictions (SAFER) and the Source Identification through Empirical Orthogonal Functions (SITEOF) source-receptor models that use basic physical constraints (source compositions) to narrow the types of solutions they provide. Roadway (tailpipe plus running evaporative) emissions, whole gasoline, and gasoline vapor, were found to be responsible for most of the ambient VOC; and higher proportion of evaporative emissions in the afternoons which is consistent with higher emissions from parked vehicles at higher afternoon temperatures. Roadway (direct tailpipe plus re-entrained road dust) emissions and soil defined as all crustal materials not directly associated with roadways, were found to be responsible for most of the non-PM10. The SAFER model was successfully applied; the SITEOF model was unsuccessful because it could not use the wind fields from the SCAQS data.},
doi = {},
url = {https://www.osti.gov/biblio/20005930},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jan 01 00:00:00 EST 1999},
month = {Fri Jan 01 00:00:00 EST 1999}
}