Abstract Number: 958 Working Group: Aerosol Modeling
Abstract Low-volatility vapours in the atmosphere lead to new particle formation (NPF). The change in particle concentrations over the industrial period that results from changing rates of NPF can lead to a radiative forcing of the climate [1]. The most important gases involved in NPF are probably sulphuric acid, ammonia, and highly oxidised organic molecules (HOMs) [2].
Radiative forcing via changes in cloud albedo can be estimated using a global aerosol model. These models are based on parametrisations of ambient and laboratory measurements, and tested against observations of particles in the atmosphere [3]. NPF leads to over half of particle number concentrations at the level of low clouds [4] and is therefore an important variable to constrain.
The CLOUD collaboration has published studies of the nucleation rate J1.7nm for the pure biogenic system with HOMs [5] and for H2SO4+NH3 [2]. Within these reports, parametrisations were presented, that are implemented in the GLOMAP aerosol model. However, ambient data show that there are locations where HOMs, H2SO4 as well as NH3 are present in significant quantities [6]. In addition, recent (unpublished) CLOUD measurements suggest that the interaction of sulphuric acid, ammonia and HOMs leads to different NPF rates compared to a sum of the individual contributions of these molecules to NPF. To study J1.7nm for the multi-component system (HOMs, H2SO4 and NH3), CLOUD has also measured this system for different temperatures, ionisation states and relative humidities between 2015 and 2017. In this contribution, we will present a parametrisation of this multi-component system and compare the results of GLOMAP including this new mechanism to older model versions.
We thank CERN for supporting CLOUD with important technical and financial resources and the PS beam. This research has received additional funding from numerous sources.
References [1] Wang and Penner, (2009) Atmos. Chem. Phys., 9, 239. [2] Dunne, E. et al, (2016) Science, 354, 1119. [3] Mann, G. W. et al, (2010) Geosci. Model Dev., 3, 519. [4] Gordon, H. et al, (2017) J. Geophys. Res., 122, 8739. [5] Kirkby, J. et al, (2016) Nature, 533, 521. [6] Bianchi, F. et al, (2016) Science, 352, 1109.