Abstract
The volatility distribution of secondary organic aerosols that formed and
had undergone aging – i.e., the particle mass fractions of semi-volatile,
low-volatility and extremely low volatility organic compounds in the
particle phase – was characterized in a boreal forest environment of
Hyytiälä, southern Finland. This was done by interpreting field
measurements using a volatility tandem differential mobility analyzer
(VTDMA) with a kinetic evaporation model. The field measurements were
performed during April and May 2014. On average, 40 % of the organics in
particles were semi-volatile, 34 % were low-volatility organics and
26 % were extremely low volatility organics. The model was, however, very sensitive
to the vaporization enthalpies assumed for the organics (ΔHVAP). The best agreement between the observed and modeled
temperature dependence of the evaporation was obtained when effective
vaporization enthalpy values of 80 kJ mol−1 were assumed. There are several potential reasons for the low effective
enthalpy value, including
molecular decomposition or dissociation that might occur in the particle
phase upon heating, mixture effects and compound-dependent uncertainties in
the mass accommodation coefficient. In addition to the VTDMA-based analysis,
semi-volatile and low-volatility organic mass fractions were independently
determined by applying positive matrix factorization (PMF) to
high-resolution aerosol mass spectrometer (HR-AMS) data. The factor
separation was based on the oxygenation levels of organics, specifically the
relative abundance of mass ions at m∕z 43 (f43) and m∕z 44 (f44). The mass fractions of
these two organic groups were compared against the VTDMA-based results. In
general, the best agreement between the VTDMA results and the PMF-derived
mass fractions of organics was obtained when ΔHVAP = 80 kJ mol−1 was set for all organic groups in the model, with a linear
correlation coefficient of around 0.4. However, this still indicates that
only about 16 % (R2) of the variation can be explained by the linear
regression between the results from these two methods. The prospect of
determining of extremely low volatility organic aerosols (ELVOAs) from AMS data
using the PMF analysis should be assessed in future studies.
Citation
ID:
199269
Ref Key:
hong2017atmosphericestimates