MADE-in: a new aerosol microphysics submodel for global simulation of insoluble particles and their mixing state

Abstract

Black carbon (BC) and mineral dust are among the most abundant insoluble aerosol components in the atmosphere. When released, most BC and dust particles are externally mixed with other aerosol species. Through coagulation with particles containing soluble material and condensation of gases, the externally mixed particles may obtain a liquid coating and be transferred into an internal mixture. The mixing state of BC and dust aerosol particles influences their radiative and hygroscopic properties, as well as their ability of forming ice crystals. <br><br> We introduce the new aerosol microphysics submodel MADE-in, implemented within the ECHAM/MESSy Atmospheric Chemistry global model (EMAC). MADE-in is able to track mass and number concentrations of BC and dust particles in their different mixing states, as well as particles free of BC and dust. MADE-in describes these three classes of particles through a superposition of seven log-normally distributed modes, and predicts the evolution of their size distribution and chemical composition. Six out of the seven modes are mutually interacting, allowing for the transfer of mass and number among them. Separate modes for the different mixing states of BC and dust particles in EMAC/MADE-in allow for explicit simulations of the relevant aging processes, i.e. condensation, coagulation and cloud processing. EMAC/MADE-in has been evaluated with surface and airborne measurements and mostly performs well both in the planetary boundary layer and in the upper troposphere and lowermost stratosphere

Metrics to quantify the importance of mixing state for CCN activity

“…As a consequence, we conclude that the aerosol representation in global models should account for mixing state. The aerosol microphysics schemes in several current global climate models have been moving in this direction (Ghan and Schwartz, 2007;Bauer et al, 2008;Jacobson, 2002;Aquila et al, 2011;Kaiser et al, 2014;Mann et al, 2010;Liu et al, 2016;Stier et al, 2005) by separating the particles into interacting subpopulations, e.g., freshly emitted BC and aged BC. The central question is whether this degree of resolution of mixing state is sufficient to accurately predict CCN concentration and aerosol optical properties, and whether this framework allows for an accurate prediction of the mixing state evolution.…”

Development of a parameterization of black carbon aging for use in general circulation models

“…For example, GATOR-GCMM (Jacobson, 2001b), ECHAM5-HAM (Stier et al, 2005), ModelE-MATRIX (Bauer et al, 2008), WACCM/CARMA (Bardeen et al, 2008), EMAC/MADEin (Aquila et al, 2011), and CAM5-MAM7 provide detailed representations of the aging processes of BC through condensation and coagulation, and some of these models are used for global climate simulations. However, there are still many GCMs that treat the BC aging processes as a simple time scale conversion from hydrophobic to hydrophilic states using the bulk method, in which only mass concentrations of aerosol species are predicted with the prescribed aerosol size distributions.…”

Modal Bin Hybrid Model: A surface area consistent, triple‐moment sectional method for use in process‐oriented modeling of atmospheric aerosols

“…[44] There are similar discrepancies in surface area prediction with the double-moment modal method (DMM), which is widely used in global climate models [Stier et al, 2005;Wang et al, 2009;Aquila et al, 2011;Liu et al, 2012]. In DMM, the double moment is obtained with prescribed geometric standard deviation σ g , specific to each category of modes, and constant throughout the simulation.…”

“…Aerosol modeling approaches now range from the one-dimensional size-resolving modal or sectional approach (conventional internal mixture assumption in regional chemical transport models), the category approach (conventional external mixture assumption in global climate models), and the category approach with a few mixing state categories [Wilson et al, 2001;Vignati et al, 2004;Stier et al, 2005;Wang et al, 2009;Aquila et al, 2011;Kajino and Kondo, 2011;Liu et al, 2012;Kajino et al, 2012aKajino et al, , 2012b to the computationally expensive two-dimensional (size and mixing state) mixing state resolving approach [Russell and Seinfeld, 1998;Jacobson, 2001;Oshima et al, 2009;Matsui et al, 2013], the multiple category with mixing state resolving approach [Jacobson, 2001;Bauer et al, 2008;Bergman et al, 2012], and ultimately to the particleresolving approach [Riemer et al, 2009;Zaveri et al, 2010].…”