Targets IMage Energy Regional (TIMER) Model, Technical ...

RIVM report 461502024 page 27 of 188
general, the differences can be given a sensible interpretation and can be linked to similar
analyses done by others (E.g. Sorensen, 1998).
0.25
Isolines (UE/cap)
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0.20
0.15
0.10
0.05
0.00
0 5000 10000 15000 20000 25000
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A more advanced approach would be to use intermediate explaining variables such as office
floor space, number and size of trucks etc. We hope to do this in future work, bridging
monetary top-down with process-based bottom-up approaches (Price, 1999; Groenenberg,
1999). Still, one may miss important explaining variables in this way, for instance a supply
push in the case of electric power overcapacity or heavily subsidised pricing. On top of this is
the (un)reliability of the sectoral data, including changes in sectoral definition.
It should be reiterated that UED frozen is a non-observable quantity. The parameterisation is done
by gauging the curve to the 1971-1995 historical data, entering reasonable estimates from the
literature on conversion efficiencies and the role of autonomous and price-induced efficiency
improvements. We have constructed a new and consistent database from IEA and other sources
to this purpose (see Appendix A). For the scenario part, we assume regional per capita
saturation level trying to account for differences in:
• industry: the product/process mix and the state of technology;
• transport: population density, mobility patterns, and the state of infrastructure and
technology;
• residences: climate, building practices and cooking and heating/cooling habits;
• services: climate, building practices, heating/cooling habits and the nature of the
service/commercial sector;
• other: no special considerations have been applied; the main activity in this category is
agriculture. This category is often small and/or a statistical artefact which tends to diminish
as the energy statistics are improving.
An additional consideration is that the demand for useful energy is not always met - there may
be an unmet, or latent, demand that cannot be satisfied due to lack of purchasing power or
supply capacity. For the calibration, this phenomenon is not accounted for.