ABSTRACT:The need to understand future trends in air quality is an issue that is frequently raised by air quality planners and managers. The potential for extreme events is of particular interest, but forecasts are difficult using traditional methods and further complicated by predictions of future climate change. This study aims to address this research need through a climate-based sensitivity study of ground-level ozone and particulate matter (PM) in the U.S. Southwest. Extreme value methods were used to examine ozone and PM in Tucson, Arizona, over the time period 1990-2001. A Statistical DownScaling Model (SDSM) was employed to build regression-based models between gridded meteorological data and point time series of ozone and PM. Following model calibration and verification, future climate-based ozone and PM scenarios were created for 2002-2050 and 2051-2099. Daily output of projected ozone and PM were then subjected to extreme value methods in order to estimate climate-based changes in ozone and PM extremes over the next century. Results indicate that monthly mean and extreme ozone values are sensitive to predicted increases in temperature, particularly in the summer months. PM results are less certain but suggest that PM may be sensitive to changing moisture conditions.