On the competition among aerosol number, size and composition in predicting CCN varability: a multi-annual field study in an urbanized desert

E. Crosbie, Jong-Sang Youn, B. Balch, Anna Wonaschütz, Taylor Shingler, Z. Wang, W.C. Conant, Eric A. Betterton, Armin Sorooshian

Veröffentlichungen: Working Paper

Abstract

A two-year dataset of measured CCN concentrations at 0.2% supersaturation is combined with aerosol size
distribution and aerosol chemistry data to probe the effects of aerosol number concentrations, size distribution and
composition on CCN patterns. Data have been collected over a period of two years (2012-2014) in central Tucson,
Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are
typically lowest in spring (233 cm-3), highest in winter (430 cm-3) and have a secondary peak during the North
American Monsoon season (July to September; 372 cm-3). There is significant variability outside of seasonal
patterns with extreme concentrations (1% and 99% levels) ranging from 56 cm-3 to 1945 cm-3 as measured during
the winter, the season with highest variability.
Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with
size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemistry
are typically aligned with changes in size and aerosol number, such that composition can be parameterized even
though it is still variable. In summer, models based on fixed chemical composition explain at best only 41%
(pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol
(SOA) production, the competition between new particle formation and condensational growth, and the complex
interaction of meteorology, regional and local emissions, and multi-phase chemistry during the North American
Monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on
longer timescales in winter.
Regimes where parameterized models exhibit improved predictive skill are typically explained by strong
relationships between CCN concentrations and the prevailing meteorology and dominant aerosol chemistry
mechanisms suggesting that similar findings could be possible in other locations with comparable climates and
geography.
OriginalspracheEnglisch
PublikationsstatusVeröffentlicht - 2015

ÖFOS 2012

  • 103039 Aerosolphysik
  • 105204 Klimatologie
  • 105206 Meteorologie
  • 105904 Umweltforschung

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