technologies). Therefore the assessment of future developments of the DRIVERS
block typically requires a more sophisticated framework than what would be
needed for the base year inventory.
In the following, the main emission source sectors are discussed in addition to
the general three-level approach presented above.
Road traffic activities and projections are typically relatively well known at city
level because these data are of interest also for other bodies than environmental
assessment. In addition to factors affecting tail-pipe emissions, non-exhaust road
dust emissions are an important impairer of air quality. Important parameters for
non-exhaust emission factors, in addition to vehicle types, are tire type, road surface
type and climate conditions. Transport demand based modelling approaches enable
also assessment of spatial changes.
The three tiers classification presented above may be represented, for instance,
by:
1. Allocation of traffic activity data from national level (top-down). The allocation
may be based on population data (in relation to national total);
2. Activities based on city level traffic counts or other estimate (bottom-up), and
allocation of vehicle categories and technologies based on national average
(top-down);
3. Activities based on city level traffic counts or other estimate, distinguished for
each vehicle category and technology using city level survey data (bottom-up)
or other local data (e.g. city level traffic model).
Availability of activity data for off-road traffic and machinery is variable. For
sea vessels, trains and airplanes, activities often are relatively well known. On the
other hand, activity data can be much more uncertain for construction and maintenance machinery activities derived from national level because of the lack of
appropriate weighting surrogates. However, reliable estimate on the changes in
vehicle stock age structure is essential especially for traffic and machinery because
of remarkable differences in emissions factors of various EURO standard levels.
The level of complexity might be similar to that of road traffic taking into account
that for each specific category (rail traffic, aviation, marine, harbours, military,
agriculture machinery, industry, construction, maintenance, etc.…) different proxy
variables must be used.
Residential combustion activities are often relatively uncertain. Especially for
residential wood combustion, which is a major concern from air quality perspective
in many European cities because of its high fine particle emissions, bottom-up
approaches can rarely be based on sale statistics because a lot of wood fuel is used
privately. For future changes, several factors should be taken into account: competitiveness of different heating systems, prospects of citizens’ preferences, renewal
of heating appliance stock and its effect on emission factors, changes in fuel
qualities, legal requirements (e.g. Eco-Design Directive). The use of detailed
housing and/or zoning models could enable the assessment of spatial changes in the
future.
2 A Framework for Integrated Assessment Modelling
15
block typically requires a more sophisticated framework than what would be
needed for the base year inventory.
In the following, the main emission source sectors are discussed in addition to
the general three-level approach presented above.
Road traffic activities and projections are typically relatively well known at city
level because these data are of interest also for other bodies than environmental
assessment. In addition to factors affecting tail-pipe emissions, non-exhaust road
dust emissions are an important impairer of air quality. Important parameters for
non-exhaust emission factors, in addition to vehicle types, are tire type, road surface
type and climate conditions. Transport demand based modelling approaches enable
also assessment of spatial changes.
The three tiers classification presented above may be represented, for instance,
by:
1. Allocation of traffic activity data from national level (top-down). The allocation
may be based on population data (in relation to national total);
2. Activities based on city level traffic counts or other estimate (bottom-up), and
allocation of vehicle categories and technologies based on national average
(top-down);
3. Activities based on city level traffic counts or other estimate, distinguished for
each vehicle category and technology using city level survey data (bottom-up)
or other local data (e.g. city level traffic model).
Availability of activity data for off-road traffic and machinery is variable. For
sea vessels, trains and airplanes, activities often are relatively well known. On the
other hand, activity data can be much more uncertain for construction and maintenance machinery activities derived from national level because of the lack of
appropriate weighting surrogates. However, reliable estimate on the changes in
vehicle stock age structure is essential especially for traffic and machinery because
of remarkable differences in emissions factors of various EURO standard levels.
The level of complexity might be similar to that of road traffic taking into account
that for each specific category (rail traffic, aviation, marine, harbours, military,
agriculture machinery, industry, construction, maintenance, etc.…) different proxy
variables must be used.
Residential combustion activities are often relatively uncertain. Especially for
residential wood combustion, which is a major concern from air quality perspective
in many European cities because of its high fine particle emissions, bottom-up
approaches can rarely be based on sale statistics because a lot of wood fuel is used
privately. For future changes, several factors should be taken into account: competitiveness of different heating systems, prospects of citizens’ preferences, renewal
of heating appliance stock and its effect on emission factors, changes in fuel
qualities, legal requirements (e.g. Eco-Design Directive). The use of detailed
housing and/or zoning models could enable the assessment of spatial changes in the
future.
2 A Framework for Integrated Assessment Modelling
15