Open AccessImproving source identification of fine particles in a rural northeastern U.S. area utilizing temperature‐resolved carbon fractions
Author(s) -
Kim Eugene,
Hopke Philip K.
Publication year - 2004
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2003jd004199
Subject(s) - aerosol , sulfate , environmental science , sea salt , environmental chemistry , particulates , total organic carbon , carbon fibers , carbon black , dust storm , combustion , atmospheric sciences , chemistry , meteorology , materials science , geology , geography , natural rubber , organic chemistry , composite number , composite material
Integrated, 24‐hour, ambient PM 2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) samples were collected at a rural monitoring site in Brigantine, New Jersey, on Wednesdays and Saturdays using Interagency Monitoring of Protected Visual Environments (IMPROVE) samplers. Particulate carbon was analyzed using the thermal optical reflectance method, which divides carbon into four organic carbon (OC), pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions. A total of 910 samples and 36 variables collected between March 1992 and May 2001 were analyzed using positive matrix factorization, and 11 sources were identified: sulfate‐rich secondary aerosol I (48%), gasoline vehicle (13%), aged sea salt (8%), sulfate‐rich secondary aerosol II (7%), nitrate‐rich secondary aerosol (6%), sulfate‐rich secondary aerosol III (5%), sea salt (4%), airborne soil (4%), diesel emission (3%), incinerator (2%), and oil combustion (1%). Temperature‐resolved carbon fractions enhanced source separations including three sulfate‐rich secondary aerosols and two traffic‐related sources that had different abundances of carbon fractions different between sources. Conditional probability functions using surface wind data and deduced source contributions aid in the identification of local sources. Potential source contribution function (PSCF) analysis shows the regional influence of sulfate‐rich secondary aerosols. Backward trajectories indicate that the highly elevated airborne soil impacts at the monitoring site were likely caused by either Asian or Sahara dust storms.