With the rapidly growing level of the degradation of our natural capitals, there are strong needs for analyzing the biocomplexity of our current systems in economic, social, and environmental aspects. Biocomplexity is the dynamic web of often surprising interrelationship that arises when components of various disciplines interact in multiple temporal, spatial scales. There are various modeling techniques available for the analysis of engineering, environmental, and economic systems however most of the methodologies usually ignore the multiscale aspect of different disciplines and the importance of the synthesis of each methodology. The goal of this research is to develop a systematic framework for assessing the biocomplexity of material use and modeling the lifecycle of industrial material in multiple aspects in order to utilize the framework for improving decision making in various disciplines. Special emphasis will be placed on the importance of the multiscale modeling of the complex systems by comparing the result of single scale modeling. And the broader implication of the expanding the system boundary of the study to the ecosystem goods and services will be discussed.

A framework is developed for the integration of the different scales of modeling scheme in the context of economic input-output (IO) modeling and engineering optimization problem in order to provide a broader implication of the life cycle aspect of our current industrial system. The major benefit of input-output analysis is that it provides a snap-shot of an economy at specific period with readily available empirical data and many researchers still rely on the monetary transaction. However, such a procedure may introduce inconsistencies in the resultant accounting of physical consumption of commodities, necessitating adjustments in the procedure to insure reasonable results. Physical accounts become more important in the study of the biocomplexity of material use and there are strong needs for enhancing the current states of the physical accounting in the IO context. In addition, fuller incorporation of the demand side is vital for analyzing alternative scenarios such as the interaction of consumer behavior, commodity price, and technology alternatives. The proposed framework use both physical and monetary input output tables in every step of modeling process to provide the insight of the significant difference of using both accountings. Leontief price model and cost-push system (Dietzenbacher 1997) are used to capture the change of the price caused by the certain shock (such as carbon tax) in the economy (coarser scale). Ghosh model (Miller and Blair 1985) has been used to balance out the monetary and physical change at the short period time after the disturbance to the system. And then engineering (finer scale) optimization problem should be solved to cope with the price change of resource inputs to the industry production process. In the little longer period time, change of price of industry production (outputs) will affect the consumer behavior in purchasing the necessary goods and services. Therefore, the concept of the price elasticity of demand is integrated in the input-output framework to capture the amount of the physical demand change accrued by the commodity price change. Finally, Leontief physical model and demand-pull system (Wei, et al. 1979; Leontief 1986) is used to capture the total amount of change in production (outputs) of each sector after consumer demand change. Different environmental policy scenarios are tested for the analysis of different level of the economy wide pollution reduction and the enhancement of the use of natural capital as a raw material for the engineering process is analyzed through the proposed framework.

As a case study, the effect of carbon tax will be illustrated in the economic, environmental, and social aspect of the use of material in the electricity generation process. Different level of disaggregated level electricity generation sectors are embedded to the readily available detailed level of economic transaction data from the U.S. Bureau of Economic Analysis. As the period of projection gets longer, the consideration of the changes in production technology and consumer demand have to be incorporated. Therefore, we analyze both short-run and long-run effect of economic, ecological disruption to the current system in the IO framework. The short-run impact analysis is employed when the exogenous changes occur in the short term or the changes occur because of the actions of only a small number of agents. While the long-run forecasting is used when longer-term and broader changes are examined.

Reference

[1] Dietzenbacher, E. (1997). "In Vindication of the Ghosh Model: A Reinterpretation as a Price Model." Journal of Regional Science 37(4): 629.

[2] Leontief, W. (1986). Input-Output Economics. Oxford, Oxford University Press.

[3] Miller, R. E. and P. D. Blair (1985). Input-Output Analysis: Foundations and Extensions. NJ, Prentice-Hall.

[4] Wei, J., T. W. F. Russel, et al. (1979). The Structure of the Chemical Industries: Function and Economics. New York, McGraw Hill.