Quantification of the impact of climate uncertainty on regional air quality

Uncertainties in calculated impacts of climate forecasts on future regional air quality are investigated using downscaled MM5 meteorological fields from the NASA GISS and MIT IGSM global models and the CMAQ model in 2050 in the continental US. Differences between three future scenarios: high-extreme, low-extreme and base case, are used for quantifying effects of climate uncertainty on regional air quality. GISS, with the IPCC A1B scenario, is used for the base case simulations. IGSM results, in the form of probabilistic distributions, are used to perturb the base case climate to provide the high-and low-extreme scenarios. Impacts of the extreme climate scenarios on concentrations of summertime fourth-highest daily maximum 8-h average ozone are predicted to be up to 10 ppbV (about one-seventh of the current US ozone standard of 75 ppbV) in urban areas of the Northeast, Midwest and Texas due to impacts of meteorological changes, especially temperature and humidity, on the photochemistry of tropospheric ozone formation and increases in biogenic VOC emissions, though the differences in average peak ozone concentrations are about 1-2 ppbV on a regional basis. Differences between the extreme and base scenarios in annualized PM2.5 levels are very location dependent and predicted to range between -1.0 and +1.5 mu gm(-3). Future annualized PM2.5 is less sensitive to the extreme climate scenarios than summertime peak ozone since precipitation scavenging is only slightly affected by the extreme climate scenarios examined. Relative abundances of biogenic VOC and anthropogenic NOx lead to the areas that are most responsive to climate change. Overall, planned controls for decreasing regional ozone and PM2.5 levels will continue to be effective in the future under the extreme climate scenarios. However, the impact of climate uncertainties may be substantial in some urban areas and should be included in assessing future regional air quality and emission control requirements.