Abstract
Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources (n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series (r = 0.92-0.98) with their corresponding factors (n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated (r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (≥ 10 °C and ≤ 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations (r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations.
Highlights
EAxeprloosroeltSheoOuarcscseeoscaiaanntdioSHnsecabileetthwn(eDceAneSshHo)rts-ttuedrmy weaxsposure to individual PM2.5 components, sources and negative health effects (Vedal et al, 2009)
According to the G/P partitioning theory developed by Pankow (1994a, b), which has been applied to the predictions of particulate matter (PM) formation (Liang and Pankow, 1996; Liang et al, 1997; Mader and Pankow, 2002), the partitioning of each individual compound is governed by its absorptive G/P partitioning coefficient, Kp,organic material (OM), which can either be measured directly (Eq 1) or calculated from theory (Eq 2): Kp, OM
D, the light n alkane/PAH factor from the particle only-based PMF analysis was more poorly correlated (r = 0.41) between the cold period and the full data set solutions (Xie et al, 2013) than the light SVOC factor from the total SVOC-based PMF analysis (r = 0.96). These results suggested that the G/P partitioning influence was removed from PMF analysis by using the total SVOC data set as input
Summary
EAxeprloosroeltSheoOuarcscseeoscaiaanntdioSHnsecabileetthwn(eDceAneSshHo)rts-ttuedrmy weaxsposure to individual PM2.5 components, sources and negative health effects (Vedal et al, 2009). Kim et al (2012) have investigated the lag structure of the association between PM2.5 constituents and hospital admissions by disease using the 5 yr bulk speciation data set of DASH study (nitrate, sulfate, EC and OC). They found that the estimated short-term effects of PM2.5 bulk components, especially those of EC and OC, were more immediate for cardiovascular diseases and more delayed for respiratory diseases. The output factors of a receptor model are not necessarily emission sources, and could be affected by atmospheric processes like photochemical reaction or gas/particle (G/P) partitioning (May et al, 2012). Where it is assumed that particle-phase organic material (OM) is primarily responsible for the absorptive uptake
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