Model predictions of CCN activity from functional group data

 

Authors

Markus D Petters — North Carolina State University
Paul Ziemann — University of California
Sonia Kreidenweis — Colorado State University
Sarah Suda — North Carolina State University
Geoffrey Yeh — University of California, Riverside
Aiko Matsunaga — Air Pollution Research Center
Christen Strollo — University of California, Riverside

Category

Secondary Organic Aerosol

Description

A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to concomitant changes in the contribution of the organics to cloud condensation nuclei (CCN). There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. Here we present a model that can be used to build organic aerosol CCN activity from inputs of carbon number and functional group composition. The model combines Köhler theory with semi-empirical group contribution methods to estimate activity coefficients and molecular volumes and predict the effective hygroscopicity kappa of single organic molecules. We evaluate this approach against laboratory measurements with model systems that explicitly probe changes in kappa upon the addition of one or more hydroxyl, nitrate, carboxyl, aldehyde, hydroperoxide, and methylene functional groups while otherwise maintaining the structure of the organic molecule. We anticipate that the model can be incorporated into scale-bridging testbeds such as the Master Chemical Mechanism or the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere to track the evolution of a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger scale models.

Lead PI

Markus D Petters — North Carolina State University