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302 Biofuels for a More Sustainable Future

biomass feedstocks at different geospatial and temporal scales. The uncer-
tainty, or say the inconsistency, of biomass quality and quantity also has large
impacts on biorefinery operations. How to factor those uncertainties into
BSC design at an early stage needs to be carefully addressed (Kudakasseril
Kurian et al., 2013; Mafakheri and Nasiri, 2014).
Another challenge associated with BSC design is the coordination
among different components of BSC. Obtaining accurate information for
each BSC component is important to develop effective strategies for the
overall BSC. For example, logistic management is critical to link different
parts of BSC and is tightly related to strategic decisions and tactical decisions.
Inefficient design of transportation network due to limited information of
transportation routes and costs may greatly affect the overall performance
of BSC. Inventory planning is another critical part in BSC to link biomass
production and biomass conversion. Different strategies need to be devel-
oped based on the type and characterization of biomass. Otherwise, a signif-
icant amount of biomass could be lost during the storage stage, leading to
economic loss. Another example is the evolving technologies of biomass
conversion. Many emerging technologies have not been commercialized
yet, how to design effective BSC for those emerging technologies and
ensure reliable performance in the future is an open question (Rentizelas
et al., 2009b; Sims and Venturi, 2004).

5.2 Challenges and issues related to BSC modeling
and decision-making
How to effectively quantify and model uncertainty always present as a
challenge for BSC. In general, two types of uncertainties have been consid-
ered in previous studies, one is the parameter uncertainty, the other is the
methodological uncertainty. Parameters uncertainties are those related to
fluctuation and variations of specific parameters in BSC, such as biomass sup-
ply (Nagel, 2000), climate (An et al., 2011b), feedstock quality (Dautzenberg
and Hanf, 2008), feedstock cost (Bai et al., 2012), transportation (Ekşio glu
et al., 2009), biofuel demand and price (Markandya and Pemberton, 2010),
policy incentive (Parker et al., 2010), and regulatory changes (Palak et al.,
2014). The challenges of addressing parameter uncertainties are (1) limited
information on data ranges and probability density function and (2) long
computational time when solving problems with uncertainty. Many efforts
have been made on biomass data collection, especially on collecting data
with uncertainties. Examples are the U.S. Department of Energy (DOE)
Billion Ton Study that estimated future potential of supplying at least one