Page 338 - Biofuels for a More Sustainable Future

294 Biofuels for a More Sustainable Future

the objective function and collected economic data related to each life-cycle
stage such as grain cost, transportation cost, and production cost. Economic
data collected include costs of cultivating activities (i.e., weeding, sowing,
fertilization, pesticides, irrigation, and harvest), transportation, and produc-
tion (Ren et al., 2015). Another common economic indicator widely used
in BSC optimization is NPV (Alex Marvin et al., 2012; He-Lambert et al.,
2018; Dal-Mas et al., 2011). Alex Marvin et al. (2012) adopted the NPV as
the objective function to optimize the BSC for a biochemical pathway from
crop residues to ethanol, where the NPV was calculated from revenue, feed-
stock cost, transportation expense, and capital investment. As the revenue of
biorefineries is subject to fuel selling price, some studies took market equi-
librium into consideration (Wang et al., 2013). Wang et al. (2013) used
maximizing SC profit as the objective function and considered food market
and biofuel market equilibrium as constraints that need data of both food
market and blended fuel market. Their results showed that government
mandates (e.g., US Energy Independent and Security Act of 2007 could
boost biofuel production, while rigid mandates (e.g., mandates without
equilibrium constraints in this study) on blenders might depresse the biofuel
production in monopoly market (Wang et al., 2013).
As biofuel is considered as a sustainable alternative to fossil-based fuels,
environmental benefits and trade-offs with economic objectives are con-
sidered in many studies. Life Cycle Analysis (LCA) is one of the most
recognized tools to quantify environmental footprints of BSC (Lardon
et al., 2009; Gnansounou et al., 2009; Cherubini and Strømman, 2011;
Kim and Dale, 2005; Muench and Guenther, 2013; Wang et al., 2007; Singh
et al., 2010; Hill et al., 2006). The system boundary of common biofuel
LCAs is farm to wheel (adapted from “Well to Wheel,” the common system
boundary of fossil-based fuels), including biomass cultivation, transporta-
tion, production, and end use (in vehicle) (Muench and Guenther, 2013).
In previous studies, common LCA indicators include GHG emissions
(Hill et al., 2006; Tonini et al., 2016), environmental footprints [e.g., total
energy consumption (Wang et al., 2007) and water footprints (Yang et al.,
2011)], Life Cycle Environmental Impacts (LCIA) (e.g., eutrophication and
acidification) (Lardon et al., 2009; Cherubini and Strømman, 2011), or
normalized LCIA indicators such as Eco-indicator 99 (Santiban ˜ez-Aguilar
et al., 2014).
In literature, LCA has been integrated with BSC optimization either as
constraints or objective functions or both. In some studies (Bernardi et al.,
2013; Sammons Jr et al., 2007), the results of LCA were used as constraints