Agent-based life cycle assessment for switchgrass-based bioenergy systems
Authored by Ming Xu, Najet Bichraoui-Draper, Shelie A Miller, Bertrand Guillaume
Date Published: 2015
DOI: 10.1016/j.resconrec.2015.08.003
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Abstract
Switchgrass is a biomass crop with no established market. Its adoption
will involve a wide range of socio-economic factors, making it a
particularly difficult system to analyze for environmental impact
estimates. Life cycle assessment (LCA) provides a methodology to
quantify the environmental impacts of a product or process throughout
its entire supply chain. However, traditional LCA approaches fail to
account for the local variability in non-homogeneous systems. Because of
the time component and other realm dynamics it is essential to visualize
as the switchgrass adoption process as a Complex Adaptive System (CAS).
Agent-based modeling (ABM) can be used to supplement life cycle
information to account for these dynamics variances. Here, we present an
Agent-Based Life Cycle Analysis (AB-LCA) model of farmers' potential
adoption of switchgrass as a biomass. The chosen modeling approach aims
to understand the main factors influencing landowner decision-making and
how these adoption patterns can affect the LCA of switchgrass ethanol.
To help address these challenges, we developed an Agent-Based Model
aimed at: (1) understanding the main factors influencing landowner
decision-making and how these adoption patterns can affect the LCA of
switchgrass ethanol and (2) improving the LCA modeling methodology by
overcoming the issues involved with analyzing emerging technologies with
dynamic and evolving supply chains. Particularly, we built an
agent-based model using LCA data of switchgrass-based ethanol production
that simultaneously captures socioeconomic factors, such as age, level
of risk aversion, education level, and level of profit, of farmers that
lead to switchgrass adoption and the changes in environmental impact
that result from this particular behavior. The results show that the
most influential factors affecting farmers' decisions are their current
economic situation and crop prices. Age and their level of knowledge of
the new crop have some impact but with limited extent. (C) 2015 Elsevier
B.V. All rights reserved.
Tags
diffusion
Model
Ethanol