CMAQ: The Community Multiscale Air Quality Modeling System

Latest Release: CMAQv5.3.2
- CMAQv5.3.2 is a minor update to version 5.3
- New features include:
  - Simplified emissions scaling
  - Improved representation of natural aerosols
  - Expanded capability for ecological applications
  - Enhanced scientific complexity with faster run times
  - Additional details available in our Fact Sheet
- CMAQ source code and User's Guide available on GitHub
- Watch the CMAQv5.3 webinar on Enhanced Capabilities to Analyze Emissions Scenarios
Research Highlight: Using Near-Field Exposure Modeling to Inform Ambient Air Emissions and Models
- In recent work by Qin et al., the SHEDS-HT model was used to estimate emissions from volatile chemical products (VCPs).
- Using observational constraints, CMAQ was used to bound the role of VCP emissions in ozone and SOA formation.
- Learn more about this study and other research highlights related to the CMAQ system.
Expanded analysis capabilities with AMETv1.4
The Atmospheric Model Evaluation Tool (AMET) is a suite of software for evaluation of meteorological and air quality models.
- Version 1.4 includes:
  - New interactive evaluation plots
  - Support for global air quality networks
  - Improved error checking and increased speed
- AMET version 1.4 GitHub Repository
VERDI v2.0 Beta Released
The Visualization Environment for Rich Data Interpretation (VERDI) is a Java-based visual analysis tool for evaluating and plotting multivariate gridded results from air quality and meteorological models. This new release supports visualizing data on the variable mesh of the MPAS-A model.
- Learn more about VERDI, including download instructions and documentation, by visiting the CMAS Center website. Exit

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CMAQ: The Community Multiscale Air Quality Modeling System

CMAQ (see-mak): an active open-source development project of the U.S. EPA that consists of a suite of programs for conducting air quality model simulations. CMAQ combines current knowledge in atmospheric science and air quality modeling, multi-processor computing techniques, and an open-source framework to deliver fast, technically sound estimates of ozone, particulates, toxics and acid deposition.