A framework for expanding aqueous chemistry in the Community
Multiscale Air Quality (CMAQ) model version 5.1
Kathleen M. Fahey1, Annmarie G. Carlton2, Havala O. T. Pye1, Jaemeen Baeka, William T. Hutzell1, Charles Stanier3, Kirk R. Baker4, K. Wyat Appel1, Mohammed Jaoui5, and John H. Offenberg51Computational Exposure Division, National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 2Department of Chemistry, University of California, Irvine, Irvine, CA 3Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 4Air Quality Assessment Division, Office of Air Quality Planning and Standards, Office of Air and Radiation, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 5Exposure Methods and Measurements Division, National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina aformerly at: Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA
Received: 29 Nov 2016 – Accepted for review: 07 Dec 2016 – Discussion started: 08 Dec 2016
Abstract. This paper describes the development and implementation of an extendable aqueous phase chemistry option (AQCHEM-KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ODEs that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry.
Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the U.S. reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM-KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM-KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the SOAS field campaign period. The added in-cloud chemistry leads to a monthly-average increase of 11–18 % in "cloud" SOA at the surface in the eastern U.S. for June 2013.
Fahey, K. M., Carlton, A. G., Pye, H. O. T., Baek, J., Hutzell, W. T., Stanier, C., Baker, K. R., Appel, K. W., Jaoui, M., and Offenberg, J. H.: A framework for expanding aqueous chemistry in the Community
Multiscale Air Quality (CMAQ) model version 5.1, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-293, in review, 2016.