Improving the representation of organic aerosol in atmospheric models
Authors
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Jeffrey Robert Pierce — Colorado State University
Chris Cappa — University of California, Davis
Category
Secondary organic aerosol
Description
Schematic describing the three objectives proposed in this work. In objective 1, we will develop a computationally efficient model that accounts for recent sources and pathways of organic aerosol formation and evolution. In objective 2, we will combine simpleSOM with MOSAIC to study the coupling of organic aerosol chemistry on the aerosol size distribution. In objective 3, we will evaluate the MOSAIC-simpleSOM model integrated in a regional climate model (WRF-Chem).
Organic aerosol (OA) is an important yet uncertain component of atmospheric aerosol and a better understanding of OA’s impact on climate will depend on the ability of large-scale models to represent the formation, growth, transformation and loss processes that eventually determine the atmospheric burden and properties of OA.
In this proposed work, we will develop and implement a computationally efficient, experimentally constrained, next-generation model called simpleSOM to represent the chemistry, thermodynamics, and microphysics of OA. The simpleSOM model will be parameterized to and tested against a variety of laboratory data. Parameterizations will be developed to account for (a) semi-volatile and reactive primary OA (POA), (b) secondary OA (SOA) formation from semi-volatile, intermediate-volatility and volatile organic compounds, (c) multi-phase, multi-generational aging that includes functionalization and fragmentation reactions, (d) low-volatility SOA formation from autoxidation and oligomerization reactions, (e) aqueous phase chemistry, (f) influence of vapor wall losses encountered in laboratory SOA formation experiments, and (g) phase state of OA. The simpleSOM model will be coupled to MOSAIC (particle dynamics model) and integrated into a three-dimensional regional climate model (WRF-Chem). A variety of box model and 3D model simulations will be carried out to develop insights into the sources and process-level information that govern the evolution of the size, mass, composition and properties of atmospheric OA and assess improvement in model predictions of OA when compared against routine and DOE-supported measurements (e.g., ARM sites, HI-SCALE).
The simpleSOM model, in terms of the processes included, will far exceed the detail and capability of OA models present in the current generation of atmospheric models. The scientific contributions from the proposed work will improve our understanding and model representation of aerosol processes, specifically those associated with the formation, growth, transformation, and loss of organic aerosols and help quantify the interactions among organic aerosols, clouds, precipitation and radiation.
