Page 339 - Biofuels for a More Sustainable Future

Key issue, challenges, and status quo of models for biofuel supply chain design 295

(e.g., the emissions of several life-cycle stages are set to not to exceed a cer-
tain cap). For example, Bernardi et al. set a GHG cap as a constraint based on
the European Union’s goal of GHG reduction (Bernardi et al., 2013).
Sammons Jr et al. (2007) proposed a framework for biorefinery product allo-
cation where the environmental impacts were modeled as constraints after
the first stage optimization with an economic objective function. In some
studies, the results of LCA were used as one of the multiple objective func-
tions. For example, Akgul et al. (2012a) developed a multiobjective function
model for wheat, wheat straw, and miscanthus to bioethanol in the United
Kingdom, where two objective functions were minimizing GHG emissions
and the SC daily cost. You and Wang (2011) developed an optimal design of
the BSC with the economic and environmental criteria considering the var-
iability and seasonality in feedstocks, biomass degradation, and geographic
diversity (You and Wang, 2011). Some other studies used a single objective
function that integrates LCA with economic analysis or other criteria using
Multiple-Criteria Decision Analysis (MCDA) (Kanzian et al., 2013;
Bernardi et al., 2013; Eskandarpour et al., 2015). For example, Bernardi
et al. adopted the weighted summation of three objective functions,
namely, NPV, GHG emissions, and water footprints (Bernardi et al.,
2013; Eskandarpour et al., 2015).
As the development of biofuel has potential to create new jobs and thrive
the economy in rural areas, social impacts such as job creation have been
included in previous studies (Bamufleh et al., 2013; Lira-Barraga ´n et al.,
2013). Among different factors that have been used to quantify the social
impacts (e.g., indicators on diversity, physical working condition, job
creation, and local community acceptance) ( Jørgensen et al., 2008), job cre-
ation is one of the most common indicators considered in previous optimi-
zation studies. The U.S. National Renewable Energy Laboratory (NREL)
has developed the jobs and economic development impact (JEDI) models
that can quantify the job creations due to the construction and operation
of biofuels at local and state levels (NREL, 2012). JEDI was developed based
on IMPLAN (economic impact analysis for planning) that uses the input-
output method to evaluate three economic impacts of a specific activity,
including direct impact (e.g., on-site labor), local revenue and supply chains,
and induced effect (e.g., increasing local business due to the development
of BSC) (Taylor et al., 1993; Rickman and Schwer, 1995). Some studies
integrated JEDI and IMPLAN with optimization models in BSC design
to couple the job creation with other objective functions related to eco-
nomic and environmental benefits (Yue et al., 2014; Ayoub et al., 2009).