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Details van artikel 6 van 9 gevonden artikelen
| Titel: |
Factor Analysis of Seattle Fine Particles |
| Auteur: |
Kim, Eugene Hopke, Philip K. Larson, Timothy V. Maykut, Naydene N. Lewtas, Joellen |
| Verschenen in: |
Aerosol science and technology |
| Paginering: | Jaargang 38 (2004) nr. 7 pagina's 724-738 |
| Jaar: |
2004 |
| Inhoud: |
Ambient particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5) samples were collected at a centrally located urban monitoring site in Seattle, WA on Wednesdays and Saturdays using Interagency Monitoring of Protected Visual Environments (IMPROVE) samplers. Particulate carbon was analyzed using the thermal optical reflectance method that divides carbon into four organic carbon (OC), pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions. A total of 384 samples that were analyzed for 36 species were collected between March 1996 and February 2000. These data were analyzed with the standard factor analysis model using the Multilinear Engine (ME). Eleven sources were identified: sulfate-rich secondary aerosol (26%), diesel emissions (22%), wood smoke (16%), gasoline vehicle (10%), aged sea salt (8%), airborne soil (7%), nitrate-rich secondary aerosol (5%), sea salt (4%), oil combustion (3%), paper mill (2%), and ferrous metal processing (1%). The use of ME provided enhanced source separations, including the nitrate-rich aerosol source and two industrial sources that were not deduced in a previous PMF2 solution. Conditional probability functions using surface wind data and resolved source contributions aid in the identifications of local sources. Potential source contribution function analysis tentatively shows southern Washington State, along the Canadian border, and southwestern British Colombia, Canada as the possible source areas and pathways that give rise to the high contribution of the sulfate-rich secondary aerosol. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 6 van 9 gevonden artikelen
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