Submitted as: model description paper | 18 Dec 2020
Review status: this preprint is currently under review for the journal GMD.
The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID)
module in the Community Multiscale Air Quality (CMAQ) Modeling
System version 5.3
Benjamin N. Murphy1,Christopher G. Nolte1,Fahim Sidi1,Jesse O. Bash1,K. Wyat Appel1,Carey Jang2,Daiwen Kang1,James Kelly2,Rohit Mathur1,Sergey Napelenok1,George Pouliot1,and Havala O. T. Pye1Benjamin N. Murphy et al.Benjamin N. Murphy1,Christopher G. Nolte1,Fahim Sidi1,Jesse O. Bash1,K. Wyat Appel1,Carey Jang2,Daiwen Kang1,James Kelly2,Rohit Mathur1,Sergey Napelenok1,George Pouliot1,and Havala O. T. Pye1
Received: 28 Oct 2020 – Accepted for review: 09 Dec 2020 – Discussion started: 18 Dec 2020
Abstract. Air quality modeling for research and regulatory applications often involves executing many emissions sensitivity cases to quantify impacts of hypothetical scenarios, estimate source contributions or quantify uncertainties. Despite the prevalence of this task, conventional approaches for perturbing emissions in chemical transport models like the Community Multiscale Air Quality (CMAQ) model require extensive offline creation and finalization of alternative emissions input files. This workflow tends to be time-consuming, error-prone, inconsistent among model users and difficult to document while consuming increased computer storage space. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module, a component of CMAQv5.3 and beyond, addresses these limitations by performing these modifications online during the air quality simulation. Further, the model contains an Emission Control Interface which allows users to prescribe both simple and highly complex emissions scaling operations with control over individual or multiple chemical species, emissions sources, and spatial areas of interest. DESID further enhances the transparency of its operations with extensive error-checking and optional gridded output of processed emission fields. These new features are of high value to many air quality applications including routine perturbation studies, atmospheric chemistry research, and coupling with external models (e.g. energy system models, reduced-form models).
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical of atmospheric modeling.
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality...