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Introduction to the Community Multiscale Air Quality Model (CMAQ)

Availability | About the Course | Meet the Trainers | Payment Info | Registration | Hotels | Prerequisites | Contact info

Availability

The table below lists the dates of the upcoming Introduction to CMAQ classes along with the enrollment status in each class. When enrollment is full (15 registered students) we will no longer accept applications for the class and the status column in the table will display that the class is full.

The class is subject to cancellation if there are not enough registered students. A minimum of 6 trainees must be registered to conduct a training.

The Introduction to CMAQ course can also be conducted off site, provided that appropriate facilities are available and there are an adequate number of interested students. Email cmas@unc.edu to inquire about off-site trainings.

About the Course

Introduction to CMAQ is a 2-day course that uses lectures and hands-on computer exercises to teach students how to run the CMAQ programs and examine input and output files from the software. The class covers topics including CMAQ terminology, how to set up and reconfigure different modeling domains, nested simulations, and multi-day simulations. Problem-solving exercises challenge the students to integrate the lessons that they had previously learned in the class to complete more advanced modeling tasks.

The syllabus is shown below to highlight the range of topics covered during the course. The course starts with a lecture on the basics of CMAQ, including an overview of air quality modeling, an introduction to the CMAQ programs, and a description of the course structure. The Hands-on laboratories have each student working on a computer pre-loaded with the course training materials. The labs focus on configuring and building the CMAQ programs, examining the input and output files, and running the programs to give students practical experience using CMAQ. The advanced topics lecture during day 2 of the training provides an overview of modeling diagnostic and evaluation topics, such as sensitivity modeling and statistical performance evaluation. The class concludes with a problem solving lab that emulates a real-world modeling task. The students are presented with a set of modeling data and a brief description of the modeling task. Where the previous labs included step-by-step instructions on how to set up and run the different CMAQ programs, in the Problem Solving Case Study each student is challenged to run CMAQ with help from the lessons learned in the previous labs, the instructor, and their fellow students.

At the completion of this course, students will be able to download, configure, compile, and run the CMAQ programs. They will possess the knowledge and practical experience needed to prepare input files for CMAQ and to produce CMAQ output.

Meet the Trainers

Sarav Arunachalam, PhD Research Professor and Deputy Director, Institute for the Environment

Dr. Arunachalam, Research Professor and Deputy Director of the Institute for the Environment at the University of North Carolina at Chapel Hill (UNC-CH) is acting Director of the Community Modeling and Analysis System (CMAS) Center, an EPA-funded center hosted at UNC-CH since 2003. Dr. Arunachalam has over 25 years of experience with multiple generations of local and regional-scale air quality models, with focus on developing and applying them for understanding atmospheric chemistry and source attribution. His recent research interests are at the intersection of emissions, air quality and public health with a strong emphasis on providing the scientific basis for air quality management, through developing both reduced-form and comprehensive modeling systems. Dr. Arunachalam leads the air quality modeling activities for the CMAS Center since 2003, and has developed and taught the CMAQ training class for a global audience. Dr. Arunachalam is also an Adjunct Professor at the UNC's Gillings School of Global Public Health's Department of Environmental Sciences and Engineering.

Liz Adams, MS Research Associate, Center for Environmental Modeling for Policy Development

Ms. Adams has over 10 years of experience in model applications, model evaluation, and debugging support to developers of air quality modeling systems. Ms. Adams prepares model documentation, and performs web-based software management, software installation and testing across multiple platforms (Linux, Mac OS X, and Windows) to support public release of the Visualization Environment for Rich Data Interpretation (VERDI) tool. Ms. Adams has installed the Sparse Matrix Operator Kernel Emissions (SMOKE) training software, data and ancillary software tools to a compute server on the Amazon Web Services (AWS) Elastic Compute Cloud (EC2) for an online SMOKE training course. Ms. Adams is experienced with using Python, QGIS, Panoply, IDV, VERDI, the Atmospheric Model Evaluation Tool (AMET), and Ncview to visualize and analyze NetCDF data from the CMAQ modeling system and comparing the results to data from the observational networks. She supports the CMAS Statistical and Graphical Analysis Tools training course by preparing, testing and porting input data and scripts for VERDI and AMET to the Virtual Computing Laboratory environment, preparing and delivering classroom lectures, and providing hands-on training support to students.

Payment Info

The 2-day course includes all training materials, the current CMAQ Training Manual, access to experienced CMAQ modelers, snacks, and beverages. Payment is accepted with check, credit card, or purchase order. Note that you are asked to make the payment or initiate the payment process (e.g. by providing the purchase order number) at the time of registration. We will send you a receipt by email to confirm the receipt of the registration and payment. If you find later that you are unable to attend to the class after registration, notify the CMAS Center as soon as possible. Please see our Payment Info page for our refund policy.

Registration

Register online to sign up for a CMAS training classes.

Prerequisites

A basic knowledge of air quality modeling concepts will help students to get the most out of this course. The course covers air quality terminology and very basic general air quality concepts, but the focus is mostly on the operational details of CMAQ. A background in air quality will provide context for the need for gridded air quality models.

Knowledge of the Linux command line language and the C-shell are also prerequisites for this course. Students with a working understanding of navigating Linux directory structures, viewing/editing text files, and executing commands from a Linux command prompt will benefit more from this class than students with no Linux experience.

Contact Information

For more information on the CMAQ training, please contact Brian Naess at 919-966-9925 or email cmas@unc.edu.