Emissions Scenarios - IPCC

206 An Overview of Scenarios
turnover rates (GDP growth of 1.6% per year between 1990
and 2100). The final energy demand across regions is
determined by the product of regional GDP growth and energy
intensity improvements. For example, the higher energy
intenshies in ASIA compared to the ALM region lead to a
higher absolute final energy demand in the former in spite of a
lower GDP. This is explained by differences in initial
conditions and by delayed diffusion of more efficient energy
end-use technologies, because of lower GDP per capita growth.
4.4.5.4. Harmonized and Other A2 Scenarios
The global primary energy use and final energy use in the A2
scenarios created with the AIM, MESSAGE, and MiniCAM
models are quite close to those of the marker scenario, while
A2-IMAGE scenario projects lower primary and final energy
use compared to the A2 marker. As mentioned above, the A2-
Al-MiniCAM scenario explores a very different unfolding of
driving forces in terms of population and GDP growth,
combined with an assumption about saturating energy demand
at current Western European levels. Combined, these
assumptions translate into the lowest energy intensity
improvement rates across the SRES scenario set. Global
primary energy use per unit of GDP (intensities) improves
from 14.7 MJ/US$90 in 1990 to 8.9 MJ/US$90 in 2100. This
reflects mainly the low per capita GDP (productivity) growth
of this scenario which (other factors being equal) translates
into low rates of energy intensity improvement. Nonetheless,
the resultant energy intensities are comparable to current
Westem European levels, as are income and energy use per
capita. In other words, the scenario describes a global picture
by 2100 quite similar to that of Westem Europe of today, 100
years earlier.
4.4.5.5. Bl Scenarios
Energy intensity improvements in the В1 marker result from
energy efficiency investments brought about by increases in
fuel and electricity prices and technological innovations
(including assumptions on taxes and perceived premium values
for clean fuels). The rather high rates in energy intensity
reduction in В1 stem also from the explicit assumption that less
industrialized regions catch-up. Another factor is the
assumption that monetary economic growth in less developed
regions initially largely replaces activities in the informal
economy, which leads to a replacement of traditional noncommercial
energy forms by high-efficiency modern
applications and fuels - and hence substantial energy intensity
improvements. In the developed regions the high economic
growth in the В1 scenario may, for instance, be in the form of
increasing monetization of human activities previously not
included in GDP accounts (e.g., childcare, household work).
Such monetary GDP growth does not result in additional
demands for energy services, and hence again results in
significant energy intensity improvements. The demand for
electricity is assumed to rise faster than that for non-electricity
energy, and may pose one of the capital availability constraints
in this scenario.
4.4.5.6. Harmonized and Other Bl Scenarios
Various altemative scenario quantifications were developed for
В1 by the modeling teams. For the fhst four to five decades
most model runs show a global final energy use within the
proposed bounds of the Bl marker, except Bl-ASF which is
higher. By 2100 most scenarios assume higher final energy use
than the marker run, except ВI-MESSAGE which reproduces
closely the final energy use of the Bl marker (and is
correspondingly classified as a "fully harmonized" scenario).
In parficular, BI-MARlA, BlHigh-MiniCAM, and BlHigh-
MESSAGE show a global final energy use in 2100 nearly twice
that of the marker. These scenarios explored the implications
for energy demand of less rapid "dematerialization" tendencies
of the economy, especially for developing countries, with
trends in line with historical energy intensity experiences in the
OECD countries. Regional trends differ most dramatically for
the MiniCAM and MARIA runs for ASIA and ALM, with the
MiniCAM simulations assuming a saturating (converging)
energy use on a per capita basis at 125 GJ/capita. However,
current knowledge about rates and direction of dematerialization
of economic activities is limited. Therefore, both
historical OECD trends and their applicability to the future
economies of currently developing countries may not
necessarily reflect future developments. The use of altemative
modeling approaches in the quantification of the Bl scenario
storyline has helped to shed light on this important area of
uncertainty of the future.
4.4.5.7. B2 Scenarios
Final energy demand for the B2 marker was derived by
applying efficiencies of end-use technologies to the demand of
electric and non-electric energy services. These in tum depend
on the economic development rates, income levels, and
sectoral economic stmcture of each region. The evolution of
the final energy demand levels and structure in the developing
regions follows patterns that are similar to the historical
development in the now-industriafized regions of the world.
This again is consistent with the "dynamics-as-usual"
interpretation of the B2 storyline. By successive iterations with
a macro-economic model, marginal cost increases are taken
into account in the energy demand projections of the
MESSAGE model for the B2 marker (see Appendix IV). The
resuh is an aggregate energy-intensity improvement rate at the
global level of about 1% per year until 2100, about the same as
has prevailed over the past 100 years in countries for which
such long-term time series data are available (see Chapter 3).
This aggregate global improvement rate masks important
differences in the temporal and spatial evolution of energy
intensities. Improvements are generally higher in regions far
away from the energy-intensity frontier and also faster in those
for which the capital turnover rate (i.e., GDP growth) is higher.
Consistent with the more imperfect realization of future trends
characteristic of the B2 scenario, energy intensity
improvements are slower than in the Al or ВI scenario
families, but higher than in the A2 scenario family.