Page 125 - Materials Chemistry, Second Edition

110 A. Bjørn et al.

with geographical representativeness. The influence of a low time-related repre-
sentativeness on the conclusions of the study must be evaluated in the interpretation
of the LCA results (see Chap. 12).
In comparative studies it is important to investigate whether there is a risk that
differences in time-related representativeness for the compared alternatives can lead
to a bias that favours one product system over the others. This could, for example,
be the case in a comparison of two technologies if the data of one technology is
older (in terms of the year they are valid for) than the data of the other technology.
Just as some LCIA methods are spatially differentiated, there are also LCIA
methods that are temporarily differentiated, meaning that their results are affected
by the timing of elementary flows (see Chap. 10). So far, this LCIA practice has
been limited to mainly distinguishing between “short-term” and “long-term”
emissions, which is, for example, relevant when including landfilling processes,
from which some emissions are projected to occur hundreds or even thousands of
years after the landfilling of a given material. In addition, some climate change
indicators consider when an emission occurs, which, for example, enables quan-
tification of the benefits of temporary carbon storage. In specific cases, the differ-
ence of inventory data in the course of the year (especially hot and cold season) and
the day (daytime/night) are relevant for a study. It is to be checked along the goal of
the study whether such intra-annual or intra-day specific data might be needed (e.g.
on night-time electricity base-load data for charging electric car batteries overnight).
In all cases, the time-related information for elementary flows required by the LCIA
methods chosen in the previous step of the scope definition should guide the data
collection and output format of the inventory analysis.

8.7.3 Technological Representativeness

Two identical products can be produced using two different technologies and
thereby be associated with different (sets of) unit processes and related flows. For
example, crude steel can be produced using an electric arc furnace (EAF) or a basic
oxygen furnace (BOF), which are two very different technologies involving dif-
ferent inventory flows. Technological representativeness reflects how well the
inventory data represents the actual technologies involved in the studied product
system. Technological representativeness is interlinked with geographical and
temporal representativeness. For example, the technology mix involved in the
production of electricity (coal power, natural gas, nuclear power, windmills, etc.)
varies in space (e.g. from country to country) and over time. The LCA practitioner
must use his or her knowledge about the product system to ensure (to the highest
degree possible) that it is modelled using unit processes that reflect the actual
technologies involved. It is important to ensure that the unit processes modelled in
the system are in fact internally technologically compatible, meaning that the
product output of one process should meet the quality requirements for input
materials of the next process in the system. For example, if a unit process requires