Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-3153-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-3153-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
21 Dec 2014
Model description paper |
| 21 Dec 2014
ORACLE (v1.0): module to simulate the organic aerosol composition and evolution in the atmosphere
A. P. Tsimpidi
CORRESPONDING AUTHOR
Max Planck Institute for Chemistry, Mainz, Germany
V. A. Karydis
Max Planck Institute for Chemistry, Mainz, Germany
A. Pozzer
Max Planck Institute for Chemistry, Mainz, Germany
S. N. Pandis
Department of Chemical Engineering, University of Patras, Patras, Greece
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
J. Lelieveld
Max Planck Institute for Chemistry, Mainz, Germany
Energy, Environment and Water Research Center, Cyprus Institute, Nicosia, Cyprus
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- Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning B. Murphy et al. 10.5194/acp-17-11107-2017
- Measurement of Formation Rates of Secondary Aerosol in the Ambient Urban Atmosphere Using a Dual Smog Chamber System S. Jorga et al. 10.1021/acs.est.9b03479
- Diurnal and Seasonal Variations in the Phase State of Secondary Organic Aerosol Material over the Contiguous US Simulated in CMAQ Y. Li et al. 10.1021/acsearthspacechem.1c00094
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- Advecting Superspecies: Efficiently Modeling Transport of Organic Aerosol With a Mass‐Conserving Dimensionality Reduction Method P. Sturm et al. 10.1029/2022MS003235
- Global health burden of ambient PM2.5 and the contribution of anthropogenic black carbon and organic aerosols S. Chowdhury et al. 10.1016/j.envint.2021.107020
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- Review on recent progress in observations, source identifications and countermeasures of PM2.5 C. Liang et al. 10.1016/j.envint.2015.10.016
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Short summary
A computationally efficient module for the description of OA composition and evolution in the atmosphere has been developed. This module subdivides OA into several compounds based on their source of origin and volatility, allowing the quantification of POA vs. SOA as well as biogenic vs. anthropogenic contributions to OA concentrations. Such fundamental information can shed light on long-term changes in OA abundance, and hence project the effects of OA on future air quality and climate.
A computationally efficient module for the description of OA composition and evolution in the...
