Page 289 - Materials Chemistry, Second Edition

280 D. Rathore et al.

4.4 Data Source and Quality

The use of fixed databases such as ecoinvent, Edu DB, Xergi, NOVAOL srl for
conducting an LCA study of bioenergy is not enough because the available dat-
abases do not have all processes required for LCA study of bioenergy. Monti et al.
(2009) also realized that available databases were generic for specific agricultural
problems during conducting the LCA of four potential energy crops (i.e., giant
reed, miscanthus, switchgrass, and Cynara cardunculus or Artichoke thistle)in
comparison with conventional wheat/maize rotation and clarify that external data
from scientific literature should be obtained for life cycle inventory (LCI)
enhancement and accurate representation of the system.
In a survey of approaches to improve reliability Björklund (2002) identifies the
main types of uncertainty due to data quality, e.g., badly measured data/inaccurate
data, data gaps, unrepresentative (proxy) data, model uncertainty, and uncertainty
about LCA methodological choices. Standardized LCA databases are sought to
reduce the burdens of data collection (UNEP 2003). There are few established,
standardized, or consistent ways to assess and maintain data quality (Vigon and
Jensen 1995). Data can become outdated, compiled at different times corre-
sponding to different materials produced over broadly different time periods
(Jensen et al. 1997), could be due to technology shift, new invention, etc. LCI data
may be unrepresentative because it could be taken from similar but not identical
processes (Björklund 2002). In general, the literature tends to agree that data for
life cycle inventories are not widely available nor of high quality (Ayres 1995;
Ehrenfeld 1997; Owens 1997), due to that during inventory analysis data with gaps
are sometimes ignored, assumed, or estimated (Graedel 1998; Lent 2003), and
LCA practitioners may extrapolate data based on limited data sets (Owens 1997).
Such assumptions and/or extrapolation resulted inappropriate interpretation and/or
huge uncertainty for decision makers.

4.5 Allocation

Allocation is the process of assigning to each of the functions of a multiple-
function system only those environmental burdens associated with that function
(Azapagic and Clift 1999). Allocation can be done on the basis of mass, volume,
energy or carbon content or economic value of the coproducts if the inputs and
outputs of the system should be partitioned between different products or functions
based on physical relationships, i.e., they shall reflect the way in which the inputs
and outputs are changed by quantitative changes in the products or functions
delivered by the system (SAIC 2006). It is recommended that allocation, if pos-
sible, should be avoided (ISO 14044 2006) through subdivision of processes, if
possible, or system expansion. Allocation on a mass basis relates products and
coproducts using a physical property that is easy to interpret (Singh et al. 2010),