Emissions Scenarios - IPCC

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340 Six Modeling Approaches Population Gross Regional Product (GRP) Industrial Value Added Service Value Added Consumer Expenditures Energy Demand Module * Useful Energy Demand (electric and non-electric * Autonomous Energy Efficiency Improvement (AEEI) * Price Induced Energy Efficiency Improvement (PIEEI)| * Secundary Fuel Substitution Electricity Generation Module * Thermal Electric (TE) inputs and efficiency * Non-Thermal Electric (NTE) technological innovation * Exogenous Hydropower Demand for Solid (coal). Liquid (oil, BLF) and Gaseous (gas, BGF) fuels leads to investment in production Cost of [fuels for] electricity Cost of secondary fuels Fuel Supply Module * Exploration for and exploitation of coal,crude oil and natural gas * Changing costs of fossil fuels due to innovation, depletion and wages * Investment in commercial Liquid and/or Gaseous Biofuel (NLF, BGF * Interregional trade in fuels based on relative producer plus transport cost Figure IV-2: Overview of the MAGE EIS/TIMER model. Atmosphere - Ocean System Atmospheric Composition Zonal Atmospheric Climate Primary driving forces • Population growth • Economic growth • Tectmological improvements • Animal husbandry Land Use <strong>Emissions</strong> • All major greenhouse gases • Land cover conversions • Land use emissions • Natural emissions Terrestrial Carbon ' Land cover conversions • Adaptation of vegetation • Regroeth of vegetation • Feedback processes Agricultural Economy • Demand for food • Number of animals • Demand for biofuels • Demand for timber Land Cover Adaptation of vegetation Unsuitable land Extensive grassland Land use rales Crop Allocation Expanding agricultural land Abandoning agricultural land Timber extraction Land quality indicators Terrestrial Vegetation ' Climate Indicators • Potential vegetation • Crop productivity • Soil conditions Figure IV-3: The structure of the TES of IMAGE 2 (including links to other modules).
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 341
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E M I S S I O N S S C E N A R I O S
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PUBLISHED BY THE PRESS SYNDICATE OF
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Contents Foreword Preface Summary f
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Preface The Intergovernmental Panel
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C O N T E N T S Why new Intergovern
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4 Summary for Policymakers Box SPM-
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6 Summary for Policymaker -3.5 i i
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8 Summary for PoUcymake. b Scenario
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lu Summary for Policymakers 0 I I I
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Summary for Policymakers such as fe
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14 Summary for Policymakers CQ so t
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16 Summary for Policymakers CQ ^ Ч
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18 Summary for Policymakers s I, I
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Summary for Policymakers P3 M ^ NO
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CONTENTS 1. Introduction and Backgr
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24 Technical Summai-y intended to b
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26 Technical Summary 1900 1950 2000
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28 Technical Summary Figure TS-2: S
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30 Technical Summaiy Box TS-3: SRES
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32 Technical Summary Figure TS-3: P
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34 Technical Summary Renewables/Nuc
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36 Technical Summary Figure TS-5 il
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38 Technical Summar 1900 1950 2000
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40 Technical Summary 40 1990 2000 2
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42 Technical Summary family). Chapt
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44 Technical Summary 1930 1960 1990
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46 Technical Summary does not exist
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48 Technical Summary CQ CP 00 00 l>
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50 Technical Summary n rí M •л
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52 Technical Summary pa Ю un ^ Ч
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54 Technical Summary (S ее CQ fN
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56 Technical Summary References: Al
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1 Background and Overview
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Background and Overview 61 1.1. Int
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Background and Overview 63 Box 1-1:
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Background and Overview 65 interven
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Background and Overview 67 powerful
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Background and Overview 69 1900 195
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Background and Overview 71 SRES Sce
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Background and Overview 73 1900 195
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Background and Overview characteriz
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2 An Overview of the Scenario Liter
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An Overview of the Scenario Literat
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hn Overview of the Scenario Literat
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3 Scenario Driving Forces
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Scenario Driving Forces 105 3.1. In
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Scenario Driving Forces 107 Section
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Scenario Driving Forces J 09 UN 199
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Scenario Driving Forces 111 deficit
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Scenario Driving Forces 113 recent
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Scénario Driving Forces lis Box 3-
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Scénario Driving Forces 117 Table
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Scenario Driving Forces 119 о I ht
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Scenario Driving Forces 121 in biol
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Scenario Driving Forces 123 0.15 0.
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Scenario Driving Forces 125 GDP per
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Scenario Driving Forces 127 aluminu
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Scenario Driving Forces 129 Table 3
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Scenario Driving Forces 131 cooling
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Scenario Driving Forces 133 saved f
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Scenario Driving Forces 135 give re
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Scenario Driving Forces 137 3.4.3.3
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Scenario Driving Forces 139 economi
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Scenario Driving Forces 141 growth"
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Scenario Driving Forces 143 (a) (b)
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Scenario Driving Forces 145 the ext
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Scénario Driving Forces 147 Global
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Scénario Driving Forces 149 anywhe
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Scenario Driving Forces 151 (a) Sul
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Scenario Driving Forces 153 Nakicen
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Scenaiio Driving Forces 155 3.7. Po
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Scenario Driving Forces 157 Overpro
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Scenario Driving Forces 159 Christi
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Scenario Drivmg Forces 161 lEA (Int
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Scénario Driving Forces 163 Murthy
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Scenario Driving Forces 165 Stevens
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4 An Overview of Scenarios
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An Overview of Scenarios 169 4.1. I
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An Overview of Scenaiios 171 within
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An Overview of Scenarios 173 • De
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An Overview of Scenarios 175 Table
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An Overview of Scenarios drivmg for
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An Overview of Scenarios 179 Figure
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An Overview of Scenarios 181 The A2
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An Overview of Scenarios 183 capita
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An Overview of Scenarios 185 ^ 4j f
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An Overview of Scenarios 187 scenar
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An Overview of Scenarios 189 • Hi
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An Overview of Scenarios 191
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An Overview of Scenarios 193 16 14
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An Overview of Scenarios 197 growth
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An Overview of Scenarios 199 Box 4-
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An Overview of Scenarios 201 Figure
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An Ovei-view of Scenarios 203 The b
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An Overview of Scenarios 205 I ^ 1
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An Overview of Scenarios 207 100 S
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An Overview of Scenarios 211 availa
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An Overview of Scenarios 213 Box 4-
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An Overview of Scenarios 215 produc
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An Overview of Scenarios 217 In par
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An Overview of Scenarios 219 S о
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An Overview of Scenarios 223 a curr
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An Overview of Scenarios 225 4.4.8.
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An Overview of Scenarios 227 20% л
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An Overview of Scenarios 233 Dietz
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An Overview of Scenarios 235 consid
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An Overview of Scenai ios 237 Gallo
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Emission Scenarios
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Emission Scénarios 241 5.1 Introdu
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Emission Scenarios 243 Box 5-1: Sce
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Emission Scenar nos PQ PQ и CN m
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Emission Scenarios 247 tí ü
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Emission Scenarios 249 40 35 |Energ
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Emission Scenarios 251 25 , [Energy
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Emission Scenarios 253 I I .2 I I
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Emission Scenanos 255 the base-year
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Emission Scénarios 257 is between
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Emission Scenarios 259 700 600 Bl F
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Emission Scénarios 261 The range o
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Emission Scénarios 263 oi • •
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Emission Scénarios 265 Table 5-7:
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Emission Scénarios 267 Table 5-9:
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Emission Scenarios 269 technically
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Emission Scénarios 271 ^ — BIT M
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Emission Scénarios 273 4000 AlB AI
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Emission Scenarios 275 M B v/ы —
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Emission Scenarios 277 Box 5-3: Sul
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Emission Scenarios 279 Box 5-4: Fut
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Emission Scenarios о ON — 00 Ч
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Emission Scenarios QS ON NO со ON
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Emission Scenarios 285 Table 5-14:
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Emission Scenarios 287 -OECD90 REF
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Page 301 and 302: 6 Summary Discussions and Recommend
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Page 329: SPECIAL REPORT ON EMISSIONS SCENARI
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Page 339 and 340: Ill Definition of SRES World Re
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Page 344 and 345: 336 Six Modeling Approaches Six Mod
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Page 350 and 351: 342 Six Modeling Approaches Table I
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390 Statistical Table Scenario AlB-
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392 Statistical Table Scenario AIB-
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4U0 Statistical Table Scenario AlB-
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416 Statistical Table Scenario AIC-
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426 Statistical Table Scenario AIG-
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436 Statistical Table Illustrative
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442 Statistical Table Scenario AIT-
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452 Statis-tical Table Scenario AIT
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456 Statistical Table Scenario Alvl
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462 Statistical Table Scenario Alv2
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464 Statistical Table Scenario Alv2
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466 Statistical Table Scenario A2-A
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472 Statistical Table Marker Scenar
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476 Statistical Table Scenario A2G-
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482 Statistical Table Scenario A2-I
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484 Statistical Table Scenario A2-M
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496 Statistical Table Scenario Bl-A
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500 Statistical Table Scenario В1-
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512 Statistical Table Scenario Bl-M
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522 Statistical Table OECDTO^^"'^'"
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526 Statistical Table Scenario BIT-
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532 Statistical Table Scenario BlHi
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542 Statistical Table Scenario B2-A
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554 Statistical Table Scenario B2-I
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556 Statistical Table Scenario B2-M
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558 Statistical Table Scenario B2-1
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572 Statistical Table Scenario B2C-
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574 Statistical Table Scenario B2C-
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576 Statistical Table Scenario B2Hi
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578 Statistical Table Scenario BZHi
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580 Statistical Table Scenario B2Hi
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582 Acronyms and Abbreviations Acro
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584 Acronyms and Abbreviations USCB
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586 Chemical Symbols Chemical Symbo
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588 Units Table X-1: SI (Système I
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590 Glossary of Terms Glossary of T
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592 Glossary of Terms Fuel Switchin
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594 Glossary of Terms standards for
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XII List of Major IPCC Reports
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List of Major IPCC Reports 599 Tech
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