A further key issue for future research is related to activity evolution. On the one
side, one would certainly like to improve the estimation of how local economic
sectors will develop and adapt in the future, taking into account both internal
factors, such as economic downturns, and external ones, as climate changes. This
means considering new land use policies (activity location) as part of the IAM
problem. On the other side, since a perfect prediction of activity evolution is out of
question, new methods to deal with uncertain predictions (ensemble modelling, risk
aversion, …) have to be developed and possibly become standard.
4.3.2 Pressures (Emissions)
In the IAM database collected by APPRAISAL, 70 % of the respondents identified
emission values as the main weakness of their modelling approach. Quantifying the
effectiveness of specific abatement measures within a zone presumes that the
emission inventory is disaggregated with sufficient details both spatially and per
categories to properly consider the emission abatement measures. This level of
detail is unfortunately lacking in most inventories leading to uncertain estimates of
the effect of measures. The official national and European (EMEP) emission
inventories only contain emission totals for the member state as a whole (or
alternatively, gridded data with only SNAP macro-sector detail). Almost all studies
focusing on local/urban scales identify, as a major issue, the lack of comprehensive,
accurate and up-to-date emission data from bottom-up emission estimation methods. Relevant information on desirable practice for compiling such local emission
inventories can be found in the guidelines of the FAIRMODE workgroup on
‘Urban emissions and Projections’ and the report on ‘Integrated Urban Emission
Inventories’ of the Citeair II INTERREG project (http://www.citeair.eu/).
There is a need for general methodologies for emission inventories that allow:
– Consistent harmonization of bottom-up and top-down emission inventories, to
allow “seamless” integration of measures from local to EU level, and vice versa;
– Development of approaches to improve the quality of emission inventories, to
‘validate’ them and to assess the emission level uncertainty (inverse modelling,
source-apportionment methods, new model chains to describe projections, …);
– Adaptation of disaggregation coefficients (in space and time) to regional and
local scales, especially for CO, PM and NH 3 emissions.
Additionally, emission projections need to improve data consistency: for
instance, the transport sector still lacks data regarding the real vehicle fleet composition (especially the split between different categories of vehicles age and
engines type). A finer description for biogenic emissions is also required, better
considering data on land use, meteorology and topography (slopes and orientation),
according to the species, which can effectively be taken into account, particularly in
mountainous and coastal areas.
74
C. Belis et al.
side, one would certainly like to improve the estimation of how local economic
sectors will develop and adapt in the future, taking into account both internal
factors, such as economic downturns, and external ones, as climate changes. This
means considering new land use policies (activity location) as part of the IAM
problem. On the other side, since a perfect prediction of activity evolution is out of
question, new methods to deal with uncertain predictions (ensemble modelling, risk
aversion, …) have to be developed and possibly become standard.
4.3.2 Pressures (Emissions)
In the IAM database collected by APPRAISAL, 70 % of the respondents identified
emission values as the main weakness of their modelling approach. Quantifying the
effectiveness of specific abatement measures within a zone presumes that the
emission inventory is disaggregated with sufficient details both spatially and per
categories to properly consider the emission abatement measures. This level of
detail is unfortunately lacking in most inventories leading to uncertain estimates of
the effect of measures. The official national and European (EMEP) emission
inventories only contain emission totals for the member state as a whole (or
alternatively, gridded data with only SNAP macro-sector detail). Almost all studies
focusing on local/urban scales identify, as a major issue, the lack of comprehensive,
accurate and up-to-date emission data from bottom-up emission estimation methods. Relevant information on desirable practice for compiling such local emission
inventories can be found in the guidelines of the FAIRMODE workgroup on
‘Urban emissions and Projections’ and the report on ‘Integrated Urban Emission
Inventories’ of the Citeair II INTERREG project (http://www.citeair.eu/).
There is a need for general methodologies for emission inventories that allow:
– Consistent harmonization of bottom-up and top-down emission inventories, to
allow “seamless” integration of measures from local to EU level, and vice versa;
– Development of approaches to improve the quality of emission inventories, to
‘validate’ them and to assess the emission level uncertainty (inverse modelling,
source-apportionment methods, new model chains to describe projections, …);
– Adaptation of disaggregation coefficients (in space and time) to regional and
local scales, especially for CO, PM and NH 3 emissions.
Additionally, emission projections need to improve data consistency: for
instance, the transport sector still lacks data regarding the real vehicle fleet composition (especially the split between different categories of vehicles age and
engines type). A finer description for biogenic emissions is also required, better
considering data on land use, meteorology and topography (slopes and orientation),
according to the species, which can effectively be taken into account, particularly in
mountainous and coastal areas.
74
C. Belis et al.