STATE and PRESSURES blocks will be emphasized in IMPACT with some more
uncertainties and robustness issues. The description of the population data and their
level of details will limit the potential of synergies among scales. As an example:
Local scale IAM on one city will not show the same impact values than a larger
scale IAM. Increasing coherence can be reached in computing a multiscale IAM
with re-distribution to each local city of their own data.
Uncertainty
As not everybody is affected in the same way by air quality exposure, the HIA
presents large uncertainties. Dose-response functions or concentration-response
functions are identified as the main source of uncertainty in IAM. Epidemiologists
often report an underestimation of causality. Therefore the literature recommends to
use the available most detailed exposure estimate in epidemiological studies (e.g.
for pollutants with high spatial variability this can be based on personal
activity-based modelling or personal dosimetry), to assess the health effects of air
pollution.
2.3.5 Responses
The RESPONSES block represent the Decision Framework, that is to say the set of
techniques/approaches that are used to take decisions on emission reduction measures, or on activity changes, or on direct concentration reductions.
Input
Input required for this block may be:
– Emissions. They constitute the block input in those cases that do not use an
explicit calculation of the STATE and of the IMPACT. Their spatial domain,
discretization, and composition detail must be coherent with the detail of the
possible actions;
– Air Quality Indexes (AQIs). Evolving pollutant concentration at different sites
(measured or produced by some model) can be summarized into one or more
AQIs. This often happens when an evaluation of the IMPACT is not performed.
These AQIs are directly compared and/or combined in the RESPONSES block.
– Impact. This is the case when the full chain is implemented. While AQIs and
impacts can be computed from measured data, to support decisions it is essential
to compute them through (deterministic or statistical) models, since their variation has to be linked to possible actions.
As external forcing of the RESPONSES block, one has mainly to consider the
decision setting in which the IAM will be used. This means that the range of actions
that the local/regional authority can consider is clearly defined and the connection
with other plans/regulations are explicit.
2 A Framework for Integrated Assessment Modelling
31
uncertainties and robustness issues. The description of the population data and their
level of details will limit the potential of synergies among scales. As an example:
Local scale IAM on one city will not show the same impact values than a larger
scale IAM. Increasing coherence can be reached in computing a multiscale IAM
with re-distribution to each local city of their own data.
Uncertainty
As not everybody is affected in the same way by air quality exposure, the HIA
presents large uncertainties. Dose-response functions or concentration-response
functions are identified as the main source of uncertainty in IAM. Epidemiologists
often report an underestimation of causality. Therefore the literature recommends to
use the available most detailed exposure estimate in epidemiological studies (e.g.
for pollutants with high spatial variability this can be based on personal
activity-based modelling or personal dosimetry), to assess the health effects of air
pollution.
2.3.5 Responses
The RESPONSES block represent the Decision Framework, that is to say the set of
techniques/approaches that are used to take decisions on emission reduction measures, or on activity changes, or on direct concentration reductions.
Input
Input required for this block may be:
– Emissions. They constitute the block input in those cases that do not use an
explicit calculation of the STATE and of the IMPACT. Their spatial domain,
discretization, and composition detail must be coherent with the detail of the
possible actions;
– Air Quality Indexes (AQIs). Evolving pollutant concentration at different sites
(measured or produced by some model) can be summarized into one or more
AQIs. This often happens when an evaluation of the IMPACT is not performed.
These AQIs are directly compared and/or combined in the RESPONSES block.
– Impact. This is the case when the full chain is implemented. While AQIs and
impacts can be computed from measured data, to support decisions it is essential
to compute them through (deterministic or statistical) models, since their variation has to be linked to possible actions.
As external forcing of the RESPONSES block, one has mainly to consider the
decision setting in which the IAM will be used. This means that the range of actions
that the local/regional authority can consider is clearly defined and the connection
with other plans/regulations are explicit.
2 A Framework for Integrated Assessment Modelling
31