CMAQv5.1 Aqueous Chemistry

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Chemistry updates – Optional aqueous chemistry with kinetic mass transfer and Rosenbrock solver: AQCHEM-KMT

Author/P.O.C.:, Kathleen Fahey, National Exposure Research Laboratory, U.S. EPA

Brief Description

AQCHEM-KMT: The "KMT" version of AQCHEM includes the treatment of kinetic mass transfer between the gas and aqueous phases (Schwartz, 1986) and the implementation of the Rodas3 solver to simultaneously integrate phase transfer, scavenging, deposition, dissociation, and chemical kinetic processes. The solver and associated files for "AQCHEM-KMT" were generated using the Kinetic PreProcessor (KPP), version 2.2.3 (Damian et al., 2002).

AQCHEM-KMTI: This version of AQCHEM-KMT includes an extension to simulate the aqueous phase formation of SOA from IEPOX, MAE, and HMML in cloud droplets (Pye et al., 2013).

Significance and Impact

The use of KPP to generate the solver allows for easier expansion of the chemical mechanism, reduces potential for coding errors, and facilitates the testing of different solvers and model assumptions. Relaxing equilibrium assumptions and calculating mass transfer coefficients to describe species transfer between and through the phases allows for a better representation of species affected by mass transfer limitations and provides a linkage between cloud droplet chemistry and cloud microphysical parameters (e.g., cloud droplet size).

Using the standard aqueous phase chemistry mechanism and an assumed droplet diameter of 16 micrometers, monthly average concentrations of most species are not significantly impacted by moving from AQCHEM to AQCHEM-KMT (with January average SO4 concentrations changing less than 0.2 micrograms/m3). However hourly concentrations can vary by more significant amounts (up to 10 micrograms/m3 SO4). The difference in predicted SO4 concentrations between standard AQCHEM and AQCHEM-KMT will vary spatially and temporally depending on cloud presence, SO2 and oxidant concentrations, as well as the assumed size of cloud droplets.

The addition of IEPOX/MPAN chemistry in cloud water (AQCHEM-KMTI) increases SOA from IEPOX/MPAN by ~5-10% in those areas with the highest IEPOX/MPAN SOA concentrations. It slightly improves the model comparison with observed methyltetrols and methylglyceric acid for Research Triangle Park, NC, during June 2013. During the same period, it increased average "cloud" SOA concentrations in the Eastern US at the surface by ~15%.

Model run time impacts are variable, but usually around a 15%-30% increase in CMAQ run time should be expected when running with AQCHEM-KMT as opposed to standard AQCHEM.

Affected files

Modified files:

  • /cloud/acm_ae6_kmt/*
  • /cloud/acm_ae6i_kmti/*
  • /MECHS/saprc07tic_ae6i_aqkmti/*

Additional options associated with AQCHEM-KMT(I)

New gas phase mechanism choice for use with AQCHEM-KMTI:

# set Mechanism = saprc07tic_ae6i_aqkmti

This new "mechanism" option requires the addition of the following lines to the build script:

if($Mechanism == "saprc07tic_ae6i_aqkmti") then
set ModGas    = gas/ebi_saprc07tic_ae6i_aq

Because the only changes in the mechanism directory between saprc07tic_ae6i_aqkmti and saprc07tic_ae6i_aq are minor changes to the GC/AE namelists regarding gas/aerosol to aqueous surrogate names, one can use the same ebi solver as for saprc07tic_ae6i_aq.

Also there are two new cloud chemistry options: AQCHEM-KMT and AQCHEM-KMTI.

# set ModCloud  = cloud/acm_ae6_kmt
# set ModCloud  = cloud/acm_ae6i_kmti

(Note these options are selected in the build script simply by "uncommenting" the preferred option.)


Damian, V., A. Sandu, M. Damian, F. Potra, and G.R. Carmichael, The Kinetic PreProcessor KPP -- A Software Environment for Solving Chemical Kinetics, Computers and Chemical Engineering, 26(11), 1567-1579, 2002.

Schwartz, S.E., Mass transport considerations pertinent to aqueous-phase reactions of gases in liquid water clouds. In Chemistry of multiphase atmospheric systems, NATO ASI Series, G6, 415-471, 1986.

Pye, H.O.T., R.W. Pinder, I.R. Piletic, Y. Xie, S.L. Capps, Y.H. Lin, J.D. Surratt, Z.F. Zhang, A. Gold, D.J. Luecken, W.T. Hutzell, M. Jaoui, J.H. Offenberg, T.E. Kleindienst, M. Lewandowski, E.O. Edney. Epoxide pathways improve model predictions of isoprene markers and reveal key role of acidity in aerosol formation, Environ. Sci. Technol., 47(19), 11056-11064, 2013.