CMAQ: Celebrating 25 Years of Air Quality Modeling Excellence
Published June 21, 2023
EPA develops software models and tools to address a range of environmental issues. These developments have exploded with the advent of technology since the turn of the century. The Community Multiscale Air Quality (CMAQ) modeling system is one of EPA’s models that has withstood the test of time. This month, EPA proudly celebrates the 25th anniversary of CMAQ’s initial release, which occurred June 30, 1998. Read about what has made the CMAQ model so successful over the years and why it is still relevant today.
What is CMAQ?
CMAQ is EPA’s premier modeling system for studying air pollution from global to local scales and is a powerful computational tool for translating fundamental atmospheric science principles to policy scenarios. 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. EPA and states nationwide have used CMAQ to support air quality management. Over the years, CMAQ has been continually updated to incorporate new state-of-the-science knowledge and use high-performance computing power to characterize air quality more accurately and efficiently to protect human health and the environment. CMAQ boasts a community of thousands of users across six continents who use the modeling system for air quality management, forecasting, and research.
CMAQ’s development was initiated in the early 1990s to advance air quality science used in regulatory models by leveraging computational advancements. Regulatory models previously had been developed to address pollutants individually. However, CMAQ was designed as a “third-generation” modeling system that incorporates meteorological, emissions, and atmospheric chemistry models to simultaneously predict the concentrations of multiple linked harmful air pollutants. CMAQ was thoughtfully built for endurance and to meet the needs of both regulatory analysts and scientists using these principles: modular, extensible, one-atmosphere.
“Generalized formulation of CMAQ’s governing equations and modular code structure are key attributes that have enabled its continuous scientific evolution over the past two decades to address emerging and increasingly complex air pollution problems,” affirmed Rohit Mathur, senior EPA research physical scientist and current scientific lead for CMAQ development.
After several years of development, CMAQ made its public debut in 1998, and shortly thereafter it was accompanied by ample EPA documentation of the science in CMAQ and how to use it. Although most of the science in those technical notes has been updated, the fundamental equations remain intact in today’s CMAQ.
CMAQ as a Backbone for National Air Quality Forecasts
A few years after CMAQ’s initial release, the development team embarked on an aggressive and ambitious extension to use CMAQ to develop air quality forecast guidance in partnership with the National Oceanic and Atmospheric Administration’s National Weather Service (NWS). This process included several scientific and logistical challenges, such as using weather data from NWS forecast models in CMAQ, creating pathways for near-real-time emissions estimates to be included in CMAQ, and meeting NWS computational timelines. “One challenge unique to the air quality forecasting system was to create a simplified and sufficiently accurate method to predict future roadway emissions using the forecasted regional temperature fields,” recalled George Pouliot, an EPA research physical scientist who was among the original developers of that system. Pouliot added that the team creatively used “mathematical and numerical techniques” to provide the emissions data that were required by CMAQ in the forecasting system.
The first ozone air quality forecasts with CMAQ were launched for the northeastern United States in 2004. Within a few years, the forecast guidance was expanded to include the lower 48 states for pollution from ozone, airborne particulate matter (PM), and regional haze. CMAQ is now used to generate twice-daily air quality forecast guidance across the nation, including Alaska and Hawaii.
From Research Tool to Informing Air Quality Management
The Clean Air Act requires EPA to set National Ambient Air Quality Standards (NAAQS) for six atmospheric pollutants that have been found to be harmful to human health and the environment. CMAQ is designed to describe the fate and transport of several of those pollutants as part of the suite of modeled chemical species. Although CMAQ was developed as a state-of-the-science modeling tool, there were several criteria that needed to be satisfied to establish CMAQ as a regulatory tool.
“Before CMAQ could be used by EPA for regulatory decision making, it was necessary to demonstrate that CMAQ model predictions agreed with observed air quality data (such as sulfate and nitrate aerosols) better than other air quality models to build confidence in CMAQ as the best available tool,” said Alice Gilliland, who was a branch chief during that period and is now Acting Director of EPA’s Center for Environmental Measurement and Modeling.
CMAQ was used by EPA to inform air quality management rules, such as the Clean Air Interstate Rule and the Clean Air Mercury Rule. CMAQ is also among the viable modeling tools endorsed by EPA for use in State Implementation Plans (SIPs) used by states to meet NAAQS regulations, and for demonstrating attainment of NAAQS by states, specifically for ozone, PM, and regional haze.
“The CMAQ model has provided air quality predictions as part of assessments underlying EPA rulemakings such as the 2015 revisions to the ozone NAAQS and the recent 2023 proposal to revise the PM NAAQS. The CMAQ model also provides data as part of multiple EPA efforts to characterize health impacts of air pollution such as EPA’s AirToxScreen, which provides data on air toxics risk across the U.S., and the Centers for Disease Control and Prevention (CDC) Public Health Air Surveillance Evaluation project, a collaborative effort between EPA and the CDC to explore the association between environmental exposures and health impacts,” remarked Richard “Chet” Wayland, Director of EPA’s Air Quality Assessment Division.
Evaluation as a Driver for Model Development
EPA’s use of CMAQ motivated innovative evaluation techniques and standardized evaluation approaches. These new techniques were designed to both bolster confidence and quantify uncertainty in modeling results. Evaluation methods addressed whether the model results were attained for the right reasons, as well as whether CMAQ responded appropriately to year-to-year changes in weather and emissions loading. Another key objective of model evaluation was to guide improvement to CMAQ. EPA research statistician and lead for CMAQ evaluation activities, Kristen Foley, explained, “We evaluate specific updates to the CMAQ system in order to see if improvements to the underlying science of the model lead to more accurate estimates or uncover compensating errors in other model components that need further investigation.”
Though evaluation against observed weather and air quality data is conducted for all CMAQ development, it has become standard practice for major updates to CMAQ (about every three years) to undergo a rigorous and formal evaluation. These exercises are documented in peer-reviewed publications, promoting quality assurance, transparency, and scientific integrity. Over the years, the evaluation activities have revealed physical and chemical processes that have systematic biases in certain regions and seasons, focusing follow-on development activities that later strengthened CMAQ.
Read more stories about CMAQ:
- CMAQ: Demonstrating Skill Across Media and Around the World
- CMAQ: Tackling Emerging Concerns and Building for the Future
Follow @EPAresearch on Twitter throughout 2023 as we highlight some of the accomplishments, milestones, and notable elements from CMAQ’s 25-year history, and search for #CMAQ25th.
This series was written by Tanya Spero, a research physical scientist in EPA’s Office of Research and Development. She joined the CMAQ Team just prior to the initial release of the model in 1998, and she remains active on the team today.