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Eulerian chemical transport models are extensively used to steer environmental policy, forecast air quality and study atmospheric processes. However, the ability of these models to simulate concentrated atmospheric plumes, including fire-related smoke, may be limited. Wildland fires are important sources of air pollutants and can significantly affect air quality. Emissions released in wildfires and prescribed burns have been known to substantially increase the air pollution burden at urban locations across large regions. Air quality forecasts generated with numerical models can provide valuable information to environmental regulators and land managers about the potential impacts of fires. Eulerian models present an attractive framework to simulate the transport and transformation of fire emissions. Still, the limitations inherent to chemical transport models when applied to replicate smoke plumes must be identified and well understood to adequately interpret results and further improve the models' predictive skills. Here, a modeling framework centered on the Community Multiscale Air Quality modeling system (CMAQ) is used to simulate several fire episodes that occurred in the Southeastern U.S. and investigate the sensitivity of fine particulate matter concentration predictions to various model inputs and parameters. Significant sources of uncertainty in the model are identified and discussed, including the spatiotemporal allocation of fire emissions and meteorological drivers. In addition, special attention is given to model grid resolution. Adaptive grid modeling is explored as a strategy to simulate fire-related plumes. An adaptive version of CMAQ, capable of dynamically restructuring the grid on which solution fields are estimated and providing refinement at the regions where accuracy is most dependent on resolution, is presented. The fully adaptive three-dimensional modeling technique can be applied to reach unprecedented levels of grid resolution and provide insight into plume dynamics unattainable with static grid models. Through this work the capability of current chemical transport models to replicate fire-related air quality impacts is evaluated, key research needs to achieve effective simulations are identified, and numerical tools designed to improve model performance are developed.

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.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1989. / Vita. Abstract. Includes bibliographical references (leaves 78-81). Also available via the Internet.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 261-267).

Thesis (M. Sc.)--University of Hong Kong, 1996. / Includes bibliographical references.

Thesis (M. Sc.)--University of Hong Kong, 1995. / Includes bibliographical references.

Thesis (M. Sc.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 82-88).

Thesis (M. Sc.)--University of Hong Kong, 1997. / Includes bibliographical references.

Thesis (M.Soc.Sc.)--University of Hong Kong, 1987. / Also available in print.