Preprints
https://doi.org/10.5194/gmd-2024-48
https://doi.org/10.5194/gmd-2024-48
Submitted as: model description paper
 | 
11 Jun 2024
Submitted as: model description paper |  | 11 Jun 2024
Status: this preprint is currently under review for the journal GMD.

Comprehensive Air Quality Model With Extensions, v7.20: Formulation and Evaluation for Ozone and Particulate Matter Over the US

Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood

Abstract. The Comprehensive Air quality Model with extensions (CAMx) is an open-source, state-of-the-science photochemical grid model that addresses tropospheric air pollution (ozone, particulates, air toxics) over spatial scales ranging from neighborhoods to continents. CAMx has been in continuous development for over 25 years and used by numerous entities ranging from government to industry to academia to support regulatory actions and scientific research addressing a variety of air quality issues. Here we describe the technical formulation of CAMx v7.20, the current publicly available model version. To illustrate an example of regional and seasonal model performance for predicted ozone and fine particulate matter (PM2.5), we summarize a model evaluation from a recent 2016 national-scale CAMx application over nine climate zones contained within the conterminous US. From that evaluation, we find that statistical performance for warm season maximum 8-hour ozone is consistently within benchmark statistical criteria for bias, gross error, and correlation over all climate zones, and often near statistical goals. Statistical performance for 24-hour PM2.5 and constituents fluctuate around statistical criteria with more seasonal and regional variability that can be attributed to different sources of uncertainty among PM2.5 species (e.g., weather influences, chemical treatments and interactions, emissions uncertainty, and ammonia treatments). We close with a mention of new features and capabilities that will be included in upcoming public releases of the model.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood

Status: open (until 06 Aug 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2024-48', Juan Antonio Añel, 20 Jun 2024 reply
    • AC1: 'Reply on CEC1', Chris Emery, 21 Jun 2024 reply
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 21 Jun 2024 reply
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood

Data sets

The EPA 2016v Modeling Platform emissions, boundary conditions, and other ancillary CAMx inputs U.S. Environmental Protection Agency https://2016v3platform.s3.amazonaws.com/index.html#2016v3platform/

The EPA 2016v3 Modeling Platform meteorological input files U.S. Environmental Protection Agency https://views.cira.colostate.edu/iwdw/RequestData/Default.aspx?pid=NEIC_2016_V1

Model code and software

The CAMx v7.20 code, open-source user license, release notes, and user guide documentation Ramboll https://www.camx.com/download/source/

CAMx pre- and post-processing software Ramboll https://www.camx.com/download/support-software/

The CAMx model run script for both the baseline and sensitivity simulation as well as model output files Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood https://gaftp.epa.gov/aqmg/baker/emery2024/

Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood

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Short summary
We describe the Comprehensive Air quality Model with extensions (CAMx) and evaluate a model simulation during 2016 over nine U.S. climate zones. For ozone, the model statistically replicates measured concentrations better than most other past models and applications. For small inhalable particulates, the model replicates concentrations consistent with most other past models and applications subject to common uncertainties associated with sources, weather, and chemical interactions.