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 ordinary differential equations (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 US 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 Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in "cloud" SOA at the surface in the eastern United States for June 2013.
Highlights
Clouds and fogs impact the amount, composition, and spatial distribution of trace atmospheric species through a complex interplay of chemistry and physics
We have developed a framework for extending Community Multiscale Air Quality (CMAQ) cloud chemistry and have implemented two additional cloud chemistry options, AQCHEM − KMT and AQCHEM − KMTI, in CMAQv5.1
Kinetic PreProcessor (KPP) was used to generate a Rosenbrock solver to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds
Summary
Clouds and fogs impact the amount, composition, and spatial distribution of trace atmospheric species through a complex interplay of chemistry and physics. As computational capabilities expand and field and laboratory studies continue to elucidate additional potentially important atmospheric aqueous chemistry pathways, it is increasingly important to maintain a modeling framework that allows for ready expansion to and investigation of that chemistry With these motivations, the Kinetic PreProcessor (KPP) version 2.2.3 (Damian et al, 2002) has been applied to generate a Rosenbrock solver for the CMAQ cloud chemistry mechanism (AQCHEM − KMT) as well as an expanded mechanism that includes additional aqueous secondary organic aerosol formation from biogenic-derived epoxides (Pye et al, 2013) in cloud (AQCHEM − KMTI). Some of the benefits and drawbacks of these newly implemented cloud chemistry options are discussed in Sect. 4, along with some directions for future development work and applications
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