Hygroscopic growth of atmospheric and model humic-like substances

Dinar, E.; Rudich, Y.; Graber, E. R.; Taraniuk, I.; Mentel, T. F.; Anttila, T.

doi:10.1029/2006JD007442

Journal Article

PreJuSER-52885

Hygroscopic growth of atmospheric and model humic-like substances

Dinar, E. ; Taraniuk, I. ; Graber, E. R. ; Anttila, T.FZJ* ; Mentel, T. F.FZJ* ; Rudich, Y.

2007
Union Washington, DC

Journal of Geophysical Research 112, D05211 (2007) [10.1029/2006JD007442]

This record in other databases:

Please use a persistent id in citations: http://hdl.handle.net/2128/20426 doi:10.1029/2006JD007442

Abstract: The hygroscopic growth (HG) of humic-like substances (HULIS) extracted from smoke and pollution aerosol particles and of Suwannee River fulvic acid (SRFA, bulk and fractions of different molecular weight) was measured by humidity tandem differential mobility analyzer (H-TDMA). By characterizing physical and chemical parameters such as molecular weight, elemental composition, and surface tension, we test the effect of these parameters on particle interactions with water vapor. For molecular weight-fractionated SRFA fractions, the growth factor at 90% relative humidity was generally inversely proportional to the molecular weight. HULIS extracts from ambient particles are more hygroscopic than all the SRFA fractions and exhibit different hygroscopic properties depending on their origin and residence time in the atmosphere. The results point out some dissimilarities between SRFA and aerosol- derived HULIS. The cloud condensation nuclei (CCN) behavior of the studied materials was predicted on the basis of hygroscopic growth using a recently introduced approach of Kreidenweis et al. (2005) and compared to CCN activity measurements on the same samples (Dinar et al., 2006). It is found that the computational approach (Kreidenweis et al., 2005) works reasonably well for SRFA fractions but is limited in use for the HULIS extracts from aerosol particles. The difficulties arise from uncertainties associated with HG measurements at high relative humidity, which leads to large errors in the predicted CCN activity.

Keyword(s): J

Classification: