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Journal article
FORest Canopy Atmosphere Transfer (FORCAsT) 2.0: model updates and evaluation with observations at a mixed forest site
Geoscientific model development, v 14(10), pp 6309-6329
21 Oct 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The FORCAsT (FORest Canopy Atmosphere Transfer) model version 1.0 is updated to FORCAsT 2.0 by implementing five major changes, including (1) a change to the operator splitting, separating chemistry from emission and dry deposition, which reduces the run time of the gas-phase chemistry by 70% and produces a more realistic in-canopy profile for isoprene; (2) a modification of the eddy diffusivity parameterization to produce greater and more realistic vertical mixing in the boundary layer, which ameliorates the unrealistic simulated end-of-day peaks in isoprene under well-mixed conditions and improves daytime air temperature; (3) updates to dry deposition velocities with available measurements; (4) implementation of the Reduced Caltech Isoprene Mechanism (RCIM) to reflect the current knowledge of isoprene oxidation; and (5) extension of the aerosol module to include isoprene-derived secondary organic aerosol (iSOA) formation. Along with the operator splitting, modified vertical mixing, and dry deposition, RCIM improves the estimation of first-generation isoprene oxidation products (methyl vinyl ketone and methacrolein) and some second-generation products (such as isoprene epoxydiols). Inclusion of isoprene in the aerosol module in FORCAsT 2.0 leads to a 7% mass yield of iSOA. The most important iSOA precursors are IEPOX and tetrafunctionals, which together account for > 86% of total iSOA. The iSOA formed from organic nitrates is more important in the canopy, accounting for 11% of the total iSOA. The tetrafunctionals compose up to 23% of the total iSOA formation, highlighting the importance of the fate (i.e., dry deposition and gas-phase chemistry) of later-generation isoprene oxidation products in estimating iSOA formation.
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Details
- Title
- FORest Canopy Atmosphere Transfer (FORCAsT) 2.0: model updates and evaluation with observations at a mixed forest site
- Creators
- Dandan Wei - University of Michigan–Ann ArborHariprasad D. Alwe - University of MinnesotaDylan B. Millet - University of MinnesotaBrandon Bottorff - Indiana UniversityMichelle Lew - Indiana UniversityPhilip S. Stevens - Indiana UniversityJoshua D. Shutter - Harvard UniversityJoshua L. Cox - Harvard UniversityFrank N. Keutsch - Harvard UniversityQianwen Shi - University of TorontoSarah C. Kavassalis - University of TorontoJennifer G. Murphy - University of TorontoKrystal T. Vasquez - California Institute of TechnologyHannah M. Allen - California Institute of TechnologyEric Praske - California Institute of TechnologyJohn D. Crounse - California Institute of TechnologyPaul O. Wennberg - California Institute of TechnologyPaul B. Shepson - Purdue University West LafayetteAlexander A. T. Bui - Rice UniversityHenry W. Wallace - Rice UniversityRobert J. Griffin - Rice UniversityNathaniel W. May - University of Michigan–Ann ArborMegan Connor - University of Michigan–Ann ArborJonathan H. Slade - University of Michigan–Ann ArborKerri A. Pratt - University of Michigan–Ann ArborEzra C. Wood - Drexel UniversityMathew Rollings - University of Massachusetts AmherstBenjamin L. Deming - University of Massachusetts AmherstDaniel C. Anderson - Drexel UniversityAllison L. Steiner - University of Michigan–Ann Arbor
- Publication Details
- Geoscientific model development, v 14(10), pp 6309-6329
- Publisher
- Copernicus Gesellschaft Mbh
- Number of pages
- 21
- Grant note
- NA18OAR4310116 / National Oceanic and Atmospheric Administration; National Oceanic Atmospheric Admin (NOAA) - USA
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemistry
- Web of Science ID
- WOS:000710527200001
- Scopus ID
- 2-s2.0-85118240637
- Other Identifier
- 991019182772304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Geosciences, Multidisciplinary