Emissions Scenarios - IPCC

Six Modeling Approaches
Table IV-3: IMAGE 2 regions (see also Table
IV-l).
Canada
USA
Latin America (Central and South)
Africa
OECD Europe
Eastem Europe
CIS (former Soviet Union)
Middle East
India (including Bangladesh, Bhutan, India, Myanmar,
Nepal, Pakistan, Sri Lanka)
China (including China, Korea (DPR), Kampuchea, Laos,
Mongolia, Vietnam)
East Asia South (Indonesia, Republic of Korea, Malaysia,
Philippines, Thailand)
Oceania
Japan
EIS computes the emissions of GHGs in 13 world regions
(Tables IV-l and IV-3). The energy-related emissions are based
on the Targets Image Energy Regional (TIMER) simulation
model (Figure IV-2). TIMER is a systems dynamics model
with investment decisions in energy efficiency, electricity
generation, and energy supply based on anticipated demand,
relative costs or prices, and institutional and informational
delays. The model uses five economic sectors. Technological
change and fuel price dynamics influence energy intensity, fuel
substitution, and the penetration of non-fossil options such as
solar electricity and biomass-based fuels.
The objective of TES is to simulate global land-use and landcover
changes and then effect on emissions of GHGs and ozone
precursors, and on carbon fluxes between the biosphere and the
atmosphere (Figure IV-3). This subsystem can be used to:
• Evaluate the effectiveness of land-use policies to
control the build-up of GHGs.
• Assess the land consequences of large-scale use of
biofuels.
• Evaluate the impact of climate change on global
ecosystems and agriculture.
Investigate the effects of population, economic, and
technological trends on changing global land cover.
More detailed information can be obtained by referring to the
following web site: http://sedac.ciesin.org/mva/.
IV.4.
Model for Energy Supply Strategy Alternatives
and their General Environmental Impact
(MESSAGE)
A set of integrated models was used to formulate the SRES
scenaiios at IIASA (Nakicenovic, et al., 1998). Model for
Energy Supply Strategy Alternatives and their General
Environmental Impact (MESSAGE) is one of the six models
that constitute lIASA's integrated modeling framework
(Messner and Strubegger, 1995; Riahi and Roehrl, 2000;
Roehrl and Riahi, 2000).
The scenario formulation process starts with exogenous
assumptions about population and per capita economic growth
by region. Energy demand (defined at the useful energy level)
is derived using the Scenario Generator (SG) model, a dynamic
model of future economic and energy development. It
combines extensive historical data about economic
development and energy systems with empirically estimated
equations of trends to determine future stmctural change. For
each scenario, SG generates future paths of energy use
consistent with historical dynamics and with the specific
scenario features (e.g., high or moderate economic growth,
rapid or more gradual energy intensity improvements).
The economic and energy development profiles serve as inputs
for the energy systems engineering model MESSAGE
(Messner and Strubegger, 1995; Riahi and Roehrl, 2000;
Roehrl and Riahi, 2000) and the macro-economic model
MACRO (Manne and Richels, 1992). MESSAGE is a dynamic
linear programming model that calculates cost-minimal supply
stractures under the constraints of resource availability, the
menu of given technologies, and the demand for useful energy.
If estimates detailed energy system structures, including energy
demand, supply, and emissions pattems, consistent with the
evolution of the energy demand produced by SG. MACRO is a
modified version of the Global 2100 model, originafiy
published in 1992 (Manne and Richels, 1992) and
subsequently used widely in many energy studies around the
world. MACRO maximizes the inter-temporal utility function
of a single representative producer-consumer in each world
region and estimates the relationships between macroeconomic
development and energy use. MESSAGE and
MACRO are linked and used in tandem to test scenario
consistency because they correspond to the two different
perspectives from which energy modeling is usually carried out
- top-down (MACRO) and bottom-up (MESSAGE).
The impacts of energy price changes on energy demand and
gross domestic product (GDP) growth are estimated by iterating
shadow prices from MESSAGE and energy demands from the
MACRO model. The iteration is repeated until energy
intensities and GDP growth rates are consistent with the output
of the SG model adopted as exogenous input assumptions at the
beginning of the scenario formulation process. The demand
reductions caused by increasing energy prices in the B2 marker
compared to a hypothetical case with constant energy prices
were calculated with MACRO. Compared to this hypothetical
case the price-induced energy demand savings in the B2 marker
are 8% by 2020, 23% by 2050, and 30% by 2100. Table IV-4
gives the shadow prices for intemational trade for gas, oil, and
coal in the B2 marker. Table IV-5 summarizes the regional
ranges for extraction costs of gas, oil, and coal in the B2 marker.
The atmospheric concentrations of GHGs and the resultant
warming potentials can be estimated by the Model for the
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