FORest Canopy Atmosphere Transfer (FORCAsT) 1.0: A 1-D model of biosphere-atmosphere chemical exchange

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Abstract

Biosphere-atmosphere interactions play a critical role in governing atmospheric composition, mediating the concentrations of key species such as ozone and aerosol, thereby influencing air quality and climate. The exchange of reactive trace gases and their oxidation products (both gas and particle phase) is of particular importance in this process. The FORCAsT (FORest Canopy Atmosphere Transfer) 1-D model is developed to study the emission, deposition, chemistry and transport of volatile organic compounds (VOCs) and their oxidation products in the atmosphere within and above the forest canopy. We include an equilibrium partitioning scheme, making FORCAsT one of the few canopy models currently capable of simulating the formation of secondary organic aerosols (SOAs) from VOC oxidation in a forest environment. We evaluate the capability of FORCAsT to reproduce observed concentrations of key gas-phase species and report modeled SOA concentrations within and above a mixed forest at the University of Michigan Biological Station (UMBS) during the Community Atmosphere-Biosphere Interactions Experiment (CABINEX) field campaign in the summer of 2009. We examine the impact of two different gas-phase chemical mechanisms on modelled concentrations of short-lived primary emissions, such as isoprene and monoterpenes, and their oxidation products. While the two chemistry schemes perform similarly under high-NOx conditions, they diverge at the low levels of NOx at UMBS. We identify peroxy radical and alkyl nitrate chemistry as the key causes of the differences, highlighting the importance of this chemistry in understanding the fate of biogenic VOCs (bVOCs) for both the modelling and measurement communities.

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Ashworth, K., Chung, S. H., Griffin, R. J., Chen, J., Forkel, R., Bryan, A. M., & Steiner, A. L. (2015). FORest Canopy Atmosphere Transfer (FORCAsT) 1.0: A 1-D model of biosphere-atmosphere chemical exchange. Geoscientific Model Development, 8(11), 3765–3784. https://doi.org/10.5194/gmd-8-3765-2015

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