Climate change is forecast to affect ambient temperatures, precipitation frequency and stagnation conditions, all of which impact regional air quality. An issue of primary importance for policy-makers is how well currently planned control strategies for improving air quality that are based on the current climate will work under future global climate change scenarios. The US EPA s Regional Air Quality Modeling System, CMAQ, with DDM-3D are used to investigate sensitivities of ozone and PM2.5 to emissions for current and future scenarios. Sensitivities are predicted to change slightly in response to climate change. In many cases, mass per ton sensitivities to NOx and SO2 controls are predicted to be greater in the future due to both the lower emissions as well as climate, suggesting that current control strategies based on reducing such emissions will continue to be effective in decreasing ozone and PM2.5 levels. Impacts of climate uncertainties on regional air quality predictions are investigated using multiple climate futures in order to evaluate the robustness of currently planned emission controls under impacts of climate change. The results show that planned controls for decreasing regional ozone and PM2.5 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. Furthermore, daily cross-responses of ozone and PM2.5 to emissions are investigated for current and future scenarios. Planned controls of NOx emissions are predicted to lead to more positive responses in reducing urban ozone and PM2.5 levels in the future. Based on present emission control technologies, cost optimized emission reductions for offsetting impacts of climate change on regional peak fourth-highest daily maximum 8-hr average ozone and yearly average PM2.5 are predicted to range from $27 million to $5.9 billion (1999$) per year in 2050s for the cities examined in this study.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/24822 |
| Date | 12 June 2008 |
| Creators | Liao, Kuo-Jen |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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