Comparison and evaluation of chemically speciated mobile source PM2.5 particulate matter profiles

Citation
Ja. Gillies et Aw. Gertler, Comparison and evaluation of chemically speciated mobile source PM2.5 particulate matter profiles, J AIR WASTE, 50(8), 2000, pp. 1459-1480
Citations number
26
Categorie Soggetti
Environment/Ecology,"Environmental Engineering & Energy
Journal title
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION
ISSN journal
10962247 → ACNP
Volume
50
Issue
8
Year of publication
2000
Pages
1459 - 1480
Database
ISI
SICI code
1096-2247(200008)50:8<1459:CAEOCS>2.0.ZU;2-W
Abstract
Mobile sources are significant contributors to ambient PM2.5, accounting fo r 50% or more of the total observed levels in some locations. One of the im portant methods for resolving the mobile source contribution is through che mical mass balance (CMB) receptor modeling. CMB requires chemically speciat ed source profiles with known uncertainty to ensure accurate source contrib ution estimates. Mobile source PM profiles are available from various sourc es and are generally in the form of weight fraction by chemical species. Th e weight fraction format is commonly used, since it is required for input i nto the CMB receptor model. This paper examines the similarities and differ ences in mobile source PM2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources. Notable characteristics of the mass fraction data include variability (rela tive contributions of elements and ions) among supposedly similar sources a nd a wide range of average EC:OC ratios (0.60 +/- 0.53 to 1.42 +/- 2.99) fo r light-duty gasoline vehicles (LDGVs), indicating significant EC emissions horn LDGVs in some cases, For diesel vehicles, average EC:OC ratios range from 1.09 +/- 2.66 to 3.54 +/- 3.07. That different populations of the same class of emitters can show considerable variability suggests caution shoul d be exercised when selecting and using profiles in source apportionment st udies.