52
3 Exploring Some Fundamentals of Environmental Footprints
Characterization
CF
CFref
GWP
Characterization
factors
IPOFs of the
investigated system
IPOFs of the
reference system
WF
WFref
WDP
LF
LFref
LOP
MF
MFref
ADP
etc.
etc.
etc.
Elementary flows
Normalization
wfCF
wCF
nCF
Normalized
footprint results
Weighting
factors
Weighted
footprint results
wfWF
wWF
nWF
wfLF
wLF
nLF
wfMF
wMF
nMF
etc.
etc.
etc.
Weighting
Composite footprint index
Fig. 3.2 Schematic representation of the calculation and integration of a set of impact-oriented footprints under the characterization-normalization-weighting framework. It builds on the premise that
all of the necessary data for inventory are sufficiently available. WDP—water depletion potential;
LOP—land occupation potential
3.4 Discussion
The investigation presented in this chapter offers new insights into the inventory
aspect and characterization aspect of various footprinting methods, an important
subject but being neglected by the majority of footprint practitioners and users. By
dividing the selected footprints into two broad categories, namely the IVOFs and
IPOFs, this chapter goes to lengths to show what distinguishes a footprint from
another that has the same name but a different logic. There is admittedly no sharp
boundary between a value-based inventory analysis and a science-based impact characterization due to gaps in scientific knowledge, and neither is there a sharp boundary
between an inventory weighting and a footprint weighting. But like there is no such
a boundary between dark and light, making the difference is still useful.
One reason for such ambiguity is the fact that subjective choices cannot be
completely avoided in shaping an IPOF. The CF clim which is subject to the time
horizon determined for GWP presents a typical example. Another reason is the
lack of internationally agreed characterization modeling in some of the identified
impact categories. For instance, it is found that even for the same abiotic resource
the ADP can differ up to several orders of magnitude depending on the model chosen
(Klinglmair et al. 2014). Moreover, resource depletion (including water depletion)
is not always seen as a true environmental impact (Finkbeiner et al. 2014), nor the
inherent characteristic of abiotic and biotic resources (Hauschild et al. 2013). Then
the question comes up: what are the inherent characteristics that should be modeled
for resource characterization? The reality is that in many cases resource flows do not
have clear input and output characteristics (Udo de Haes 2006).
In general, there is much more agreement on how to characterize emissions (e.g.,
GWP, ODP) than on how to characterize resource extractions. This is perhaps the
foremost reason why the IPOFs are more advanced for emissions than for other forms
of resources (e.g., land, water, material), for which the IVOFs have a considerably
wide range of applications. The IVOF category of footprints provides a more practical
way of measuring the pressure of resource use that is causing environmental impacts,
3 Exploring Some Fundamentals of Environmental Footprints
Characterization
CF
CFref
GWP
Characterization
factors
IPOFs of the
investigated system
IPOFs of the
reference system
WF
WFref
WDP
LF
LFref
LOP
MF
MFref
ADP
etc.
etc.
etc.
Elementary flows
Normalization
wfCF
wCF
nCF
Normalized
footprint results
Weighting
factors
Weighted
footprint results
wfWF
wWF
nWF
wfLF
wLF
nLF
wfMF
wMF
nMF
etc.
etc.
etc.
Weighting
Composite footprint index
Fig. 3.2 Schematic representation of the calculation and integration of a set of impact-oriented footprints under the characterization-normalization-weighting framework. It builds on the premise that
all of the necessary data for inventory are sufficiently available. WDP—water depletion potential;
LOP—land occupation potential
3.4 Discussion
The investigation presented in this chapter offers new insights into the inventory
aspect and characterization aspect of various footprinting methods, an important
subject but being neglected by the majority of footprint practitioners and users. By
dividing the selected footprints into two broad categories, namely the IVOFs and
IPOFs, this chapter goes to lengths to show what distinguishes a footprint from
another that has the same name but a different logic. There is admittedly no sharp
boundary between a value-based inventory analysis and a science-based impact characterization due to gaps in scientific knowledge, and neither is there a sharp boundary
between an inventory weighting and a footprint weighting. But like there is no such
a boundary between dark and light, making the difference is still useful.
One reason for such ambiguity is the fact that subjective choices cannot be
completely avoided in shaping an IPOF. The CF clim which is subject to the time
horizon determined for GWP presents a typical example. Another reason is the
lack of internationally agreed characterization modeling in some of the identified
impact categories. For instance, it is found that even for the same abiotic resource
the ADP can differ up to several orders of magnitude depending on the model chosen
(Klinglmair et al. 2014). Moreover, resource depletion (including water depletion)
is not always seen as a true environmental impact (Finkbeiner et al. 2014), nor the
inherent characteristic of abiotic and biotic resources (Hauschild et al. 2013). Then
the question comes up: what are the inherent characteristics that should be modeled
for resource characterization? The reality is that in many cases resource flows do not
have clear input and output characteristics (Udo de Haes 2006).
In general, there is much more agreement on how to characterize emissions (e.g.,
GWP, ODP) than on how to characterize resource extractions. This is perhaps the
foremost reason why the IPOFs are more advanced for emissions than for other forms
of resources (e.g., land, water, material), for which the IVOFs have a considerably
wide range of applications. The IVOF category of footprints provides a more practical
way of measuring the pressure of resource use that is causing environmental impacts,