AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
Effects of Near-Source Coagulation of Biomass Burning Aerosols on the Global Aerosol Size Distribution
EMILY RAMNARINE, Jeffrey R. Pierce, Colorado State University
Abstract Number: 732 Working Group: Regional and Global Air Quality and Climate Modeling
Abstract Biomass burning is a significant global source of aerosol number and mass. These aerosols can act as cloud condensation nuclei, affecting the cloud albedo and lifetime, causing an indirect forcing, and they directly scatter and absorb solar radiation. The size distribution of these particles greatly determines their direct and indirect climatic effects. Coagulation of particles is an important process in determining size distribution. As coagulation occurs, the number of particles is diminished and the distribution is shifted larger. Sakamoto et al. (2016) found that the rate of growth by coagulation can be approximated by fire area, mass flux of fire emissions, initial size distribution, plume mixing depth, and surrounding wind speed. In this work we explore the effects that coagulation has on the global aerosol size distribution, and therefore the aerosol radiative effects, in the global aerosol model, GEOS-Chem-TOMAS. In the default configuration of GEOS-Chem-TOMAS, the fire emissions are given a fixed size distribution, regardless of fire characteristics and meteorology. When adding the Sakamoto et al. (2016) parameterization for near-source coagulation, the peak in the number distribution of the particles moves to a higher mean diameter with a smaller number concentration for larger, boreal fires relative to smaller, tropical fires. Overall, the number of CCN-sized particles decreased globally relative to the previous fixed-size assumption in GEOS-Chem-TOMAS. The results are sensitive to the assumption of overlap of plumes of nearby fires. To constrain this and determine the effectiveness of the parameterization, we will be comparing our model results to observations.
Sakamoto, K. M. et al., Atmos. Chem. Phys., 16, 7709-7724, doi:10.5194/acp-16-7709-2016, 2016.