– LEVEL 3: emissions are calculated with the finest space and time resolution
available, with the bottom-up method with all the SNAP-NAPFUE classifications details. Emission factors and activity data have to correspond to the
specific activities of the studied area. The processes have to be detailed so that it
is possible to attribute the most representative emissions. In case of lack of data,
the top-down approach can be used but with the help of complementary data to
take into account the regional specificities. The uncertainties may be quantitatively calculated, e.g. by a Monte Carlo method, whenever possible. This level
is the best one to allow the generation of all kinds of scenarios provided that the
emission changes are higher enough compared to the uncertainties of the SEI
emission values.
Emission scenarios may be built directly from the SEIs by reducing the total
emissions per grid box. These scenarios are then used in the STATE block to give
general indications of the possible evolution of the air quality, or identify simplified
equations that represent the links between emissions and concentrations in a
complex IAM.
EMEP/EEA (2009a, b) classifies the methodologies to compute the emission
projections:
– LEVEL 1 projection methods can be applied to non-key categories and sources
not expected to be modified by future measures. Level 1 projections will only
assume generic or zero growth rates and simply projected or latest year’s historic emission factors.
– LEVEL 2 projections would be expected to take account of future activity
changes for the sector, based on national activity projections and, where
appropriate, take into account future changes in emission factors. It is necessary
to have a detailed description of the source category in order to apply the
appropriate new technologies or control factors to sub-sectors.
– LEVEL 3 projections use detailed models to provide emission projections,
considering additional variables and parameters. However, these models have to
use input data that are consistent with national economic, energy and activity
projections used elsewhere in the projected emissions estimates.
Output
A first output is an emission inventory that gives the total amount of different
pollutants released into the atmosphere by all the different sources. These sources
are classified using the processes producing the pollution (biogenic, industrial,
transport-related, agricultural, etc.) and their type and spatial characteristics and
distribution: point sources (industries, power plants, etc.), line sources (road
transport) and area sources (biogenic, diffuse industries, residential areas, and small
road sources).
A second output is a SEI that represents the amount of different pollutants
released in each cell of a mesh. To get this SEI, the spatial information about the
distribution of the sources (point, line and area) has to be projected on the mesh
(normally a matrix of square cells). Then, the contribution of each source category
2 A Framework for Integrated Assessment Modelling
23
available, with the bottom-up method with all the SNAP-NAPFUE classifications details. Emission factors and activity data have to correspond to the
specific activities of the studied area. The processes have to be detailed so that it
is possible to attribute the most representative emissions. In case of lack of data,
the top-down approach can be used but with the help of complementary data to
take into account the regional specificities. The uncertainties may be quantitatively calculated, e.g. by a Monte Carlo method, whenever possible. This level
is the best one to allow the generation of all kinds of scenarios provided that the
emission changes are higher enough compared to the uncertainties of the SEI
emission values.
Emission scenarios may be built directly from the SEIs by reducing the total
emissions per grid box. These scenarios are then used in the STATE block to give
general indications of the possible evolution of the air quality, or identify simplified
equations that represent the links between emissions and concentrations in a
complex IAM.
EMEP/EEA (2009a, b) classifies the methodologies to compute the emission
projections:
– LEVEL 1 projection methods can be applied to non-key categories and sources
not expected to be modified by future measures. Level 1 projections will only
assume generic or zero growth rates and simply projected or latest year’s historic emission factors.
– LEVEL 2 projections would be expected to take account of future activity
changes for the sector, based on national activity projections and, where
appropriate, take into account future changes in emission factors. It is necessary
to have a detailed description of the source category in order to apply the
appropriate new technologies or control factors to sub-sectors.
– LEVEL 3 projections use detailed models to provide emission projections,
considering additional variables and parameters. However, these models have to
use input data that are consistent with national economic, energy and activity
projections used elsewhere in the projected emissions estimates.
Output
A first output is an emission inventory that gives the total amount of different
pollutants released into the atmosphere by all the different sources. These sources
are classified using the processes producing the pollution (biogenic, industrial,
transport-related, agricultural, etc.) and their type and spatial characteristics and
distribution: point sources (industries, power plants, etc.), line sources (road
transport) and area sources (biogenic, diffuse industries, residential areas, and small
road sources).
A second output is a SEI that represents the amount of different pollutants
released in each cell of a mesh. To get this SEI, the spatial information about the
distribution of the sources (point, line and area) has to be projected on the mesh
(normally a matrix of square cells). Then, the contribution of each source category
2 A Framework for Integrated Assessment Modelling
23