ILCD Handbook: Framework and requirements for LCIA models and ...

ILCD Handbook: Framework and requirements for LCIA models and indicators First edition
4.3.1.2 Framework for analysing the characterisation models
Potentially Affected
Fraction of Species
Ecosystem Damage
Emission of mass
Distribution of mass
Cumulative Exposure
(summed over time and space)
Likely Incidence in
Population
Human Health
Damage
Fate factor
Exposure
factor
Exposure -
Response
Consequences
Human Intake
Fraction
Human Health
Effect Factor
Human Damage
Factor (HDF)
Figure 4-4 Recommended framework for calculating characterisation factors for human toxicity
effects in LCA. (based on Pennington et al. 2006, Jolliet et al. 2006)
From Figure 4-4, it is clear that the model for human toxicity effects must account for the
environmental fate (F), exposure (X), dose-response (R) of a chemical for midpoint factors
and additionally severity (S) for endpoint factors (Udo de Haes et al. 2002, Pennington et al.
2006, Jolliet et al. 2006):
CF = S · R · X · F = S · R · iF
The fate factor above relates the emission flow to the change in mass in the environment.
The exposure factor links the change in mass in the environment to the change in intake
rate. The dose-response slope is the likelihood of an additional effect per unit additional
intake and the severity is the effect per case linked to mortality and morbidity.
In reality, these parameters vary depending on location (e.g. habitat characteristics, local
stressors, mixtures, background concentrations) and time (e.g. seasonal life stage
sensitivity). The implications of many of these assumptions in comparative applications such
as LCA, as well as in regulatory contexts, are only now beginning to be quantified. These
variations are therefore generally not adopted in default models and factors.
The fate and exposure factors can be combined into an Intake Fraction (iF). This
characterizes the fraction of the emission that is taken in by the overall population (Bennet et
al. 2002).
In estimating the comparative risk of a chemical in LCA, dose-response extrapolations are
based on toxicological benchmarks. Dose-response benchmarks can be estimated from
toxicity data on e.g. laboratory experiments, assuming a variety of models (e.g. Crettaz et al.,
2002)
Benchmarks are exposure measures associated with a consistent change in response,
such as the 10% or even the 50% effect level. Regulatory-based measures do not
necessarily provide a consistent risk basis for comparison, as they were often not developed
for use in such a comparative context or to facilitate low dose-response extrapolation. Other
differences in data use in LCA and regulatory/based risk assessments include the preferred
use of median, rather than extreme, data in the fate and exposure modelling, as well as the
4 Requirements for specific impact categories 39