Advances in Air Quality Modeling

EM—October 2018: A look at recent advances in air quality modeling, from air dispersion models to next-generation chemical transport models.

by Leiran Biton and Golam Sarwar

Air quality modeling is of critical importance to inform regulatory and planning activities under the U.S. Clean Air Act (CAA). Due to limitations in spatial and temporal coverage of ambient monitoring networks, air quality models are better able to characterize the ambient impacts of individual
sources or demonstrate the adequacy of emissions limits for an existing source. In addition, the impacts of new sources that do not yet exist, and modifications to existing sources that have yet to be constructed, can best be determined through air quality modeling. Therefore, air quality models are relied upon by federal, state, local, and tribal air agencies across a variety of pollutants and CAA programs. For example, dispersion models are used by regulatory agencies to issue permits for new facility operations while ensuring that ambient air quality is protected. Similarly, air quality planners rely on chemical transport models (CTMs) for developing policies to address regional pollutants while still accounting for other factors, such as population growth and economic development.

To effectively serve these purposes, air quality models must continually characterize complex environmental systems that necessitate advances in their science and capabilities. This issue of EM is dedicated to better understanding some of the policy-relevant advances in air quality modeling techniques that are currently being developed or proposed.

In the United States, air quality models are applied for regulatory and planning purposes in accordance with the U.S. Environmental Protection Agency's (EPA) Guideline on Air Quality Models, published as Appendix W to 40 CFR Part 51. Better known among air modelers as “the Guideline,” this regulation guides air quality management agencies in using approaches that are based on best practices and demonstrated to be scientifically credible. On January 17, 2017, EPA updated the Guideline, as previewed in EM's October 2016 issue and detailed in depth in EM's July 2017
. Among the most discussed element of the 2017 revision of the Guideline is that, for the first time, it addresses the use of models to assess formation of secondary pollutants, such as ozone and secondarily-formed fine particulate matter. As such, tools developed based on information from CTMs are increasingly used to inform permitting of individual sources for the assessment of secondary pollutant formation.

This issue of EM is focused on various aspects of the advances in air quality modeling, from science improvements in the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD), EPA's preferred near-field dispersion model, to planning the next generation of CTMs. The issue dives deep into new thinking about incorporating information from wind tunnels into dispersion models, accounting for moisture in plume rise, use of plume-following models to account for chemical transformation, air quality models for forecasting, and estimating lightning generated oxides of nitrogen. ....