9701502 Frey This research program features several major activities: (1) the development of detailed engineering-economic models of clean technologies for the purpose of understanding trade-offs among process performance, emissions and cost; (2) the development of new methods for quantitative analysis of uncertainty and variability in environmental technologies; (3) the combination of probabilistic analysis with optimization capabilities to yield approaches for optimizing technologies in the face of uncertainties; and (4) detailed case studies to illustrate the use of systems models and the benefits of the probabilistic and optimization methodologies. The detailed case studies will focus on selected innovative gasification technologies. These technologies offer promise for low environmental discharges, waste utilization, and efficient use of fossil fuels. For example, coal gasification technologies represent a rich area of study regarding process optimization, uncertainty analysis, and pollution prevention because of the wide range of possible process configurations. These technologies are emerging as the preferred alternative for the next generation of coal-based power generation, with nearly a dozen demonstration plants underway in the U.S. and Europe. By failing to rigorously quantify the risks of new technology, traditional approaches to estimating their performance, emissions, and cost have been misleading, exposing decision makers to unnecessary costs and risks. The billions of dollars now being spent on the development of coal gasification technologies should be targeted to those systems that offer the greatest potential for emissions reduction and favorable costs. Therefore, there is a critical need for systems modeling of these technologies. Opportunities to extend the methodology to evaluation of other types of technologies will be considered as part of collaborative work. The educational program will include the development of modular inst ructional materials in air pollution control, air quality engineering, systems engineering, and related topics. These modules will be adaptable for use in courses in transportation engineering, chemical engineering, and textiles. Modular materials are amenable to systematic evaluation and targeted refinement through pre- and post-testing. Modular materials will also facilitate distance-learning course offerings. A key focus in the development of instructional materials will be the development of multi-media pedagogical computer models of major emission sources that transfer the research results into the classroom. Such models will enable students to explore the sensitivity of model predictions to different mechanistic assumptions regarding mass and energy balances, chemical equilibrium, chemical kinetics, and empirical approaches to estimating pollutant formation and control, and to deal with uncertainty in model structure and input parameters. ***
