1Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada
2Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
Received: 10 Jul 2013 – Published in Atmos. Chem. Phys. Discuss.: 25 Jul 2013
Abstract. New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulfur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are tens of kilometres and larger. Based on the results of the System for Atmospheric Modelling (SAM), a large-eddy simulation/cloud-resolving model (LES/CRM) with online two-moment aerosol sectional (TOMAS) microphysics, we have developed a computationally efficient, but physically based, parameterization that predicts the characteristics of aerosol formed within sulfur-rich plumes based on parameters commonly available in global- and regional-scale models. Given large-scale mean meteorological parameters ((1) wind speed, (2) boundary-layer height and (3) downward shortwave radiative flux), (4) emissions of SO2 and (5) NOx from the source, (6) mean background condensation sink, (7) background SO2 and (8) NOx concentrations, and (9) the desired distance from the source, the parameterization will predict (1) the fraction of the emitted SO2 that is oxidized to H2SO4, (2) the fraction of that H2SO4 that forms new particles instead of condensing onto pre-existing particles, (3) the mean mass per particle of the newly formed particles, and (4) the number of newly formed particles per kilogram SO2 emitted. The parameterization we describe here should allow for more accurate predictions of aerosol size distributions and a greater confidence in the effects of aerosols in climate and health studies.
Revised: 28 Oct 2013 – Accepted: 07 Nov 2013 – Published: 13 Dec 2013
Stevens, R. G. and Pierce, J. R.: A parameterization of sub-grid particle formation in sulfur-rich plumes for global- and regional-scale models, Atmos. Chem. Phys., 13, 12117-12133, doi:10.5194/acp-13-12117-2013, 2013.