1235684 (Ghadimi). The transition to a sustainable clean energy future is one of the greatest challenges of this new century. Major economies are competing to dominate the emerging energy economy and governments, regardless of their position on the plan-market spectrum, play a critical and distinctive role in driving technology development and adoption. In an increasingly interdependent world, the technology-energy-environment-economy (TEEE) interplay has profound implications for the world economy and presents very distinct analytical challenges both to engineers and social scientists. A thorough understanding of this complex system is vital for sustainable development at regional, national and global levels, and there is an urgent need for a comprehensive integrated framework for analyzing such engineering-economic systems. The proposed TEEE framework analyzes technology, energy, environment, and the economy in two important energy rich regions (ERRs) - West Virginia and Shanxi Province, China - and is targeted to provide a comprehensive set of analytical tools for understanding the national and global consequences of interactions among these complex systems. Both of these ERRs are key coal-producing regions, representing very different economic and social governance systems and states of development. The goal of this research is to establish an engineering-based economic framework for an integrated analysis of the TEEE system by a multidisciplinary research team. The specific objectives of the project are (1) to develop the existing engineering-based micro-level structural decomposition analysis (SDA) and input-output process model (IOPM) along with the macro-level optimal depletion computable general equilibrium (CGE) model into a unified and comprehensive framework to analyze the TEEE chain; (2) to calibrate the model for two ERRs and simulate a range of technology-energy-environment-economy policy scenarios in these regions, each case representing a quite distinctive economic structure; (3) to conduct two regional online surveys of key stakeholders and use a non-market valuation method (i.e., a choice experiment) to assess the broader economic and environmental implications of transitioning to a diversified and clean energy economy in these energy rich regions; and (4) to identify critical characteristics for generalizing the integrated model to make it applicable in other ERRs. Implementation of the model will involve the participation of graduate research assistants, and descriptions and demonstrations of the model will be offered to interested and cognate disciplines as teaching modules in a range of multidisciplinary undergraduate and graduate level courses.
