Air quality computer models are widely used investigation tools in environmental research; many physical and chemical processes are modeled and their integrated impacts on atmospheric pollutant concentrations studied. These models are also important tools for regulatory and policy communities, and are used to develop optimal emission control strategies for atmospheric pollutants, as required by the National Ambient Air Quality Standards.
The level of confidence in modeling results depends critically on the accuracy of numerical methods employed, as well as on the robustness of the underlying implementation. This research will develop state-of-the-art computational methods and software techniques for use in air quality modeling work on time stepping methods. Special purpose algorithms will be developed for simultaneous treatment of box model processes, including aerosol dynamics, gas and liquid phase chemistry and interphase mass transfer. Higher accuracies and lower computational times are targeted.
Particulate matter (aerosol) processes have recently became a priority focus area in environmental science. Incorporating aerosol processes in the models leads to an order of magnitude increase in the overall computational time. The research will extend into the area of solving the integro-differential equations that govern particle evolution; specifically, the proposed work will improve the theoretical framework and will build fast and reliable numerical techniques for aerosol dynamics-chemistry simulations.
Together with the physical/chemical process understanding and numerical algorithm design, software tech- nology is an important component of these models. Another objective of the project is to explore software design techniques and tools that will make the modeling software easier to use, to maintain and to develop. The resulting object-oriented version of a generic Eulerian model will illustrate the new approach to soft- ware construction and will constitute an ideal environment for developing and testing specialized numerical methods.
The educational goal is to enhance interdisciplinary education in computationally-oriented disciplines. Since much of the science and technology of the future and many of the new industries will cross the boundaries of traditional disciplines, interdisciplinary education becomes increasingly important. Some of the newest high demand areas involve computing and information technology together with other fields: teaching and research will support the development of cutting-edge computationally-involved B.S. programs at Michigan Technological University, and continue to contribute to the Ph.D. program in Computational Science and Engineering.
