An evaluation of air quality forecast tools for the Eastern U.S.: is there room for improvement?

Operational air quality forecasts of ground-level ozone and particle pollution to protect public health have become routine in the United States. Various tools such as regression, photochemical models, and phenomenological rules have been developed to provide guidance for enhancing the accuracy of air quality forecasts. However, the accuracy of these forecast tools is often not uniformly or consistently evaluated. This paper provides an in-depth and objective assessment of human forecasts, regression equations, and the NOAA-EPA and Canadian CHRONOS forecast models for six selected East Coast cities during the 2004 and 2005 summer smog seasons (May – September). It compares the accuracy of air quality forecasts with forecasts of other meteorological phenomena, such as precipitation and severe weather. It also discusses the challenges faced by air quality forecasters in making more accurate and specific forecasts and the future direction and advancement of air quality forecasts nationwide.