Air Quality Modeling for the Twenty-First Century

Three-dimensional numerical air quality simulation models have been evolving since the early 1970's as tools for air quality planning and management, and more recently, air quality forecasting. The earliest models were applicable to simulation of urban photochemistry within a single airshed. Models were later developed to cover larger scales in space and time and also to treat additional pollutants of interest. Current air quality models are able to treat urban through continental scale pollutant issues in a “one-atmosphere” manner including interactions among a number of present-day pollutants of interest, such as ozone, fine and coarse particulate matter, acid and nutrient deposition, mercury, and various urban air toxics. The atmospheric chemistry within air quality models has grown in complexity, extending from the gas phase to include aqueous cloud chemistry and heterogeneous chemistry. Fast, efficient numerical solution procedures have been developed to accommodate the increase in chemical complexity. Simulation of particulate matter has posed many challenges, including the addition of processes for phase transitioning, and the physics and thermodynamics of aerosols. Further, as model domains have increased in size and simulation lengths have also increased, the need for interfacing regional air quality models with hemispheric and global models to provide chemical boundary conditions has arisen. Integrated models of atmospheric physics and chemistry are now emerging where meteorological, emissions, and chemistry processes are solved concurrently.

This expansion in model development has been accompanied by new diagnostic procedures for model probing and evaluation. Tools for source apportionment, process analysis, and sensitivity/uncertainty analysis are being developed and tested to help interpret the results of air quality model simulations. Methods of using monitoring and other observational data together with the results of model simulations are emerging to define present day “surfaces” of air quality for assessments. Use of model ensembles are being studied as one method of characterizing air quality model results in a probabilistic manner, rather than using the results in an absolute deterministic way. New modeling applications are also emerging. Some of these include modeling to forecast short-term air quality, modeling to assess potential climate change impacts on regional air quality, multimedia modeling to include deposition to water and terrestrial surfaces, and modeling to link with human exposure assessments. Air quality model development and applications continue to evolve into new challenging areas to meet the needs of the twenty-first century research and policy communities.

Notice: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.