Emissions Scenarios - IPCC

An Ovei-view of Scenarios 203
The bottom-up, systems engineering (optimization) model MESSAGE does not compute energy prices. Instead, the model is
entirely based on cost information, but such costs are treated as dynamic. Their overall treatment follows the lines outlined
above for the MARIA model, except that greater technology-specific detail is contained m the model. Altogether 19 different
fossil resource grades are differentiated, based on the estimates of Rogner (1997). The resultant (levelized) extraction costs for
the B2 marker are in the range US$1.1 to US$5.4 per GJ for coal, US$1.2 to US$5.3 per GJ for oil, and US$1.2 to US$5.7 per
GJ for gas (range indicates costs variations between lowest and highest costs of the four SRES regions for 2020,2050, and 2100
respectively, see Appendix IV). Technology-specific cost assumptions cannot be summarized here as MESSAGE contains
literally hundreds of energy supply and end-use technologies. Examples of cost assumptions are given in Section 4.4.7 and more
detail is reported in Riahi and Roehrl (2000). However, as in MARIA, MESSAGE also calculates shadow prices for
mtemationally traded primary energy forms and therefore these two indicators can be compared (Table 4-8).
Table 4-8: International price (MARIA) and calculated shadow price (MESSAGE) of internationally traded energy
(I990US$IGJ) by 2020,2050, 2100for the SRES B2 scenario.
Coal Oil Gas Biofuels Synfuels
MARIA MESSAGE» MARIA MESSAGE" MARIA MESSAGE-^ MARIA MESSAGE"
2020 0.5 3.4 3.5 3.9-4.4 2.9 2.8-4.4 4.8 n.a.
2050 0.8 2.5 4.9 7.5-8.2 4.3 5.1-6.4 6.5 10.4-16.2
2100 1.4 8.1 6.3 17.3-18.2 5.4 5.2-11.4 6.3 17.1-20.7
" Costs include export and/or import infrastructure and transport.
Range between crude oil and light and heavy oil products.
Range between liquid natural gas and direct pipeline imports to North America, Europe, Japan, and North Africa.
Range between methanol, ethanol, and liquid hydrogen.
To achieve consistency between model-calculated energy cost dynamics and energy demand assumptions an iterative modeling
procedure between MESSAGE and MACRO (a macro-economic production function model based on Manne and Richels,
1992) was used, on the basis of model-calculated shadow prices as indicators of fuhjre price dynamics. The methodology is
described in more detail in Wene (1996). This approach requires time-intensive model iterations, but has the advantage that the
impact of price increases can be separated from efficiency improvements through fuel substitution (e.g., a gas-fired cook stove
energy end-use efficiency is up to 10 times higher than a traditional cook stove fired with fuelwood) as well as from "everything
else," i.e., the AEEI in the traditional sense). Aggregated, the impact of (shadow) price increases in MESSAGE'S B2 scenario
accounts for 8% of global primary energy demand by 2020, 23% by 2050, and 30% by 2100. This impact is calculated as a
reduction in energy demand compared to a hypothetical scenario with constant 1990 prices (and correspondingly higher energy
demand). The impact of price increases on future energy demand in the B2 scenario is thus relatively small compared to that of
other factors, although far from negligible. This also explains why the two B2 scenario quantifications by MARIA and
MESSAGE have quite similar energy demand figures,even if intemational trade prices may differ. First, trade prices are only
one compœient of the cost-price mechanism treated in the models (which also includes domestic energy production,
conversion, and end-use costs). Second, models differ in their parametrizations of the "everything else" (AEEI) model
parameters, for which a wide range of views on applicable ranges exists. Therefore it is one of the model calibration parameters
frequently used to replicate existing scenarios or to standardize inter-model comparison projects such as EMF-14 (Weyant,
1995).
(Box 4.7 commues)