Systems Informatics and Analysis - Engineering and Science of Biomass Feedstock Production and Provision - page 216

factors. They concluded that the GHG intensity was at least 80 % lower than that for
gasoline. However, their analysis ignored the indirect land use change.
The ERG Biofuel Analysis Meta-Model (EBAMM) was developed in order to
review the current state of ethanol energy analyses ( http://rael.berkeley.edu/
EBAMM/ ) [ 122 ]. It also enables the modeling of a number of biofuel pathways,
such as the Brazilian sugar cane ethanol and “advanced” corn. Different biodiesel
life-cycle analyses can also be compared with EBAMM. The model is developed as
a Microsoft Excel ® spreadsheet and is easy to use and modify. EBAMM can be used
for the consideration of different energy types, the calculation of policy-relevant
metrics, the addition of coproduct credit when this is required, and the application
of a consistent system boundary through the addition of missing parameters and the
removal of insignifi cant data.
Direct and indirect land use change is perhaps one of the most intensely debated
topics on the life-cycle impacts of biofuels in recent years [ 116 ]. There are model-
based conclusions on both sides of the argument. There are two major reasons for
this disagreement that highlight some of the challenges in systems modeling. First,
there is a disagreement over the system boundary (i.e., what is the correct spatial
scale to use for such an analysis). Second, the input data that are entered into these
models, such as the emissions associated with fertilizer production and use, have
not been standardized. Farrel et al. [ 122 ] summarized the results obtained from vari-
ous studies and the variability in results reported by different studies.

8.4 Summary and Discussion

The goal of this chapter was to review literature on the application of SIA tech-
niques for BFPP systems. Some important basics of SIA were discussed followed
by reviewing applications relative to four different classes. We have made notes of
important conclusions drawn by these studies at various places in the chapter.
Summarized below are some general conclusions about the work reviewed:

• The focus on addressing the system-level issues has increased considerably in
recent years. This is possibly due to the realization that there are a number of
complex interactions between different feedstock production and provision tasks.
The initial focus for such studies was mostly on performing a case-specifi c anal-
ysis without the development of a generic model. However, greater interest has
been generated in developing a generic model that can be used to study multiple
crops in multiple regions. These model-based studies have led to valuable insights
into the optimal design, management, and operational strategies for this sector.
• The applications at the crop growth and management level as well as the local
production and provision level are numerous. For crop growth modeling, many
models already developed for conventional agricultural crops have been modi-
fi ed to include bioenergy crops.
• For local production and provision levels, the interest in using optimization as a
tool has recently increased signifi cantly, as evident from the citations in Table 8.2 .
Optimizing the transportation logistics, including the locations of the farms,