Uncertainty
When the AQ state is evaluated through measurements only, uncertainties are
related to the measurements themselves, to the geostatistical methods used to
interpolate point measurements and to the representativeness of measurement sites
to characterize the area under study.
Uncertainties related to AQ numerical modelling have been widely discussed in
the scientific literature. Intrinsic uncertainties of AQ modelling are mainly related to
errors in the physical formulation of the model, and to uncertainties in the input
data. An operational validation of the AQ model by comparison with measurements
is required, opening the question of the representativeness of the chosen measurement sites in relation to the model scale. Evaluating the indefiniteness of
prospective study is more challenging and would require the use of diagnostic
evaluation (e.g., sensitivity tests) or probabilistic evaluation (e.g., errors propagation). Furthermore, as mentioned earlier, for prospective IAMs, estimating the AQ
state over a relatively short temporal period (up to one year) introduces uncertainties on the representativeness of the estimated state itself.
2.3.4 Impact
The IMPACT block describes the consequences of any alterations or modifications
of environmental conditions, being either beneficial or adverse. Among the various
impacts, we could distinguish between impacts on human health, on environment
(vegetation and ecosystems), on social, economic aspects or on climate. Moreover
some impact could be derived from another, such as economic consequences of
human health or of ecosystem services changes.
The choice of IMPACT would primarily allow to support the selection of the
RESPONSES that would eventually influence the complete DPSIR chain.
Special attention will be paid in the following to health issues, that are important
for local and regional decision making and are, in many cases, the most relevant
impact from the economic viewpoint.
Input
Human health is a response to the exposure to a given air quality (STATE), and can
be calculated using data that describe the air quality (such as level of concentration
measured at a monitoring site, levels of concentration averaged for several monitoring stations or determined using an AQ model) and dose-response functions or
concentration-response functions when available. In some case, the health impact
can be calculated using data such as intake fractions computed after modelling the
emissions to take into consideration (PRESSURES).
The choice of a pollutant to perform HIA (Health Impact Assessment) is often
more restricted by the available knowledge on health effects and on the way to
measure those effects, than by the input provided by the STATE block. The
selection of input data depends in fact on the availability of a causal function to
2 A Framework for Integrated Assessment Modelling
29
When the AQ state is evaluated through measurements only, uncertainties are
related to the measurements themselves, to the geostatistical methods used to
interpolate point measurements and to the representativeness of measurement sites
to characterize the area under study.
Uncertainties related to AQ numerical modelling have been widely discussed in
the scientific literature. Intrinsic uncertainties of AQ modelling are mainly related to
errors in the physical formulation of the model, and to uncertainties in the input
data. An operational validation of the AQ model by comparison with measurements
is required, opening the question of the representativeness of the chosen measurement sites in relation to the model scale. Evaluating the indefiniteness of
prospective study is more challenging and would require the use of diagnostic
evaluation (e.g., sensitivity tests) or probabilistic evaluation (e.g., errors propagation). Furthermore, as mentioned earlier, for prospective IAMs, estimating the AQ
state over a relatively short temporal period (up to one year) introduces uncertainties on the representativeness of the estimated state itself.
2.3.4 Impact
The IMPACT block describes the consequences of any alterations or modifications
of environmental conditions, being either beneficial or adverse. Among the various
impacts, we could distinguish between impacts on human health, on environment
(vegetation and ecosystems), on social, economic aspects or on climate. Moreover
some impact could be derived from another, such as economic consequences of
human health or of ecosystem services changes.
The choice of IMPACT would primarily allow to support the selection of the
RESPONSES that would eventually influence the complete DPSIR chain.
Special attention will be paid in the following to health issues, that are important
for local and regional decision making and are, in many cases, the most relevant
impact from the economic viewpoint.
Input
Human health is a response to the exposure to a given air quality (STATE), and can
be calculated using data that describe the air quality (such as level of concentration
measured at a monitoring site, levels of concentration averaged for several monitoring stations or determined using an AQ model) and dose-response functions or
concentration-response functions when available. In some case, the health impact
can be calculated using data such as intake fractions computed after modelling the
emissions to take into consideration (PRESSURES).
The choice of a pollutant to perform HIA (Health Impact Assessment) is often
more restricted by the available knowledge on health effects and on the way to
measure those effects, than by the input provided by the STATE block. The
selection of input data depends in fact on the availability of a causal function to
2 A Framework for Integrated Assessment Modelling
29