156 Introduction to Renewable Biomaterials
Table 5.1Three common LCA software package options.
Software Licensing Data sets Software features Website
openLCA Open source
and free
Ecoinvent, Gabi,
USLCI, CML,
and others
Fast calculation engine, easily
shares models, no yearly
subscription, process based on
transparent data, used for
USDA digital commons LCA
data development
http://www.openlca
.org
SimaPro Paid
licensing
Ecoinvent,
USLCI, CML,
and others
Process based on transparent
data, good customer support,
robust uncertainty analysis
http://www.pre-
sustainability
.com/simapro
Gabi Paid
licensing
Gabi Dataset,
Ecoinvent,
USLCI
Robust data set, visual process
flow-based modeling, ease of
use, data frequently updated
http://www.gabi-
software.com
A mass balance should equal zero when adding all of the material inputs to a system
subtracted by all the materials exiting in the system. In reality and especially in
complicated production processes, the difference of the in–out flows may not be zero.
The percent mass closure can be calculated by
%Mass Closure=
(massin−mass out)
massin
× 100
Providing mass balances and listing percent closure is a good practice that leads to data
transparency. Ideally, the percent closure system should be 100%; however, in reality this
is often not the case due to measurement errors, fugitive emissions, and other modeling
errors. In practice, mass balances above 95% can often provide meaningful data suitable
for use.
Similar to a total mass balance a component balance can be performed to ensure
proper tracking of an element within a system. For instance, carbon balances track
the mass of carbon flowing into and out of a process. The in and out should be equal
or the percent closure should be near 100%. If this is not the case, the data should be
reexamined to find the error or missing data.
When using secondary data from LCI databases or literature, it is also important
to perform data quality checks. Mass balance is also a valid approach to checking
secondary data surrounding unit processes. Further analysis should examine the
spatial data surrounding the secondary data. For instance, a material produced in
China using an average electrical grid that relies heavily on coal power will have
different environmental impacts than a product produced in the Northwest United
States where hydroelectric power is more dominant in the average electrical grid.
One way to overcome these regional differences is to change the electricity type used
for the secondary data and recalculate the overall impacts. Doing this can provide
a better representation of the impacts of the product under study. Technology is
another important factor. Often, secondary data are out of date and are based on
older technology than what is currently employed in the industry. The record date for
thesecondarydatacangivesomeindicationofwhetherthetechnologyiscurrentor
not, but further analysis of the documentation should be performed to determine if
