Emissions Scenarios - IPCC

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280 Emission Scénarios in tlie Al or Bl familles, but faster than in the A2 family. Sulfur emission projections for the В 2 marker scenario were generated on the basis of minimization of critical loads of acidic deposition using the methodology described in Amann et al. (1996). No explicit link between income levels and sulfur control regime was made in this scenario. The resultant sulfur emissions are 61 IVltS in 2020, 56 MtS in 2050, and 48 MtS in 2100 (see Figure 5-12). All the SRES marker scenarios anticipate increasing levels of sulfur control, with rates and timing ranging from rapid introduction of stringent controls in Bl-IMAGE to more gradual, later, and less stringent controls in A2-ASF. To illustrate the impacts of sulfur controls in the scenarios, an "uncontrolled sulfur" variant of the B2 marker scenario was calculated at the Intemational Association for Applied Systems Analysis (IIASA; for details see Box 5-4). In this hypothetical scenario, sulfur emissions amount to 182 MtS in 2050 and 227 MtS in 2100 (compared to 57 and 47 MtS, respectively, in the B2 marker scenario). These emission levels are much higher even than those in the A2 marker scenario (105 MtS in 2050 and 60 MtS in 2100). 5.6. Regional Distribution and Gridding Regional information on emissions serves at least two major purposes - to identify the contribution of world regionsto the global total and to track shifts in the relative weight of different regions. This information is especially relevant for the development of mitigation scenarios. For climate modeling, the regional distribution of emissions for well-mixed GHGs (COj, CH^, N^O, and halocarbons) may not be that important. However, short-lived gases such as SO2 are radiatively important close to the point of origin only; their local and regional concentrations may significantly change the future climate outlook. The same is true for the group of ozone precursors (CO, N0^, and NMVOCs). To be able to estimate tropospheric ozone concentration levels, regionalized information is indispensable. The initial evaluation showed that the 40 SRES scenarios have a very substantial regional variability in emissions of all radiatively important substances. The detailed and rigorous analysis of this variability falls outside the scope of the cuiTent report. Therefore, this section merely illustrates possible regional pattems based on standardized regional emissions in the four SRES marker scenarios (see also Kjam et al., 2000). Standardized regional outputs from the 40 SRES scenarios are provided in Appendix VII. Subsection 5.6.1 describes emissions of GHGs and SO2 in the four SRES macro-regions, followed by the description of "gridded" SOj emissions (distributed over a ГхГ grid) in 5.6.2. In this report represented by four macro-regions - OECD90, REF, ASIA, and ALM. 5.6.1. Regional Distribution As Tables 5-13a to 5-13d clearly illustrate, the distribution of emissions over the four regions in the base year (1990) is very uneven. For example, while in industrialized regions (OECD90 and REF) fossil and industrial COj emissions are dominant, in the developing regions (ASIA and ALM) the contribution of land-use emissions (deforestation) is also very important. In 1990, developing regions produced much lower volumes of CO, and high-GWP gases than the industrialized world, while their relative share of NjO, CH4, and NO^, emissions was much more substantial (see Figures 5-13a to 5-13d). 5.6.1.1. Carbon Dioxide <strong>Emissions</strong> from Fossil Fuels and Industry As suggested by Figure 5-14, in all the SRES scenario famihes the share of industriaUzed regions (OECD90 and REF) in global total becomes progressively smaller and by 2100 these regions emit from 23% to 32% of the total (Table 5-14, Figure 5-14). In the OECD90 region, standardized fossil fuel and industrial CO2 emissions in the AlB marker scenario (AlB-AIM) increase from 2.8 GtC in 1990 to 3.4 GtC in 2050, and subsequently decline to 2.2 GtC in 2100 (Figure 5-14). Compared to other scenarios, the growth in primary energy use in this region is relatively high, spuixed by rapid economic development (see also Chapter 4). However, after 2050 the increases in the use of primary energy are accompanied by declining emissions through the combination of a lower use of fossil fuels and a switch from coal to gas. The share of nonfossil fuels in the OECD90 region of the AlB marker scenario also increases drastically. In 2100, the contribution of nonfossil energy amounts to 68% of the total primary energy use of the OECD90 countries, the largest non-fossil fuel share for this region of all the SRES marker scenarios. The fossil fuel and industrial COj emission trajectory of the REF region is even less linear than in the OECD90 region. Initially, emissions decline from the base year level of 1.3 GtC to 1.1 GtC in 2020 because of economic restructuring. After 2020, emissions increase, driven by an increased energy demand to support renewed economic growth (Figure 5-14). However, after 2050 emissions decline again primarily through a decrease in population and improved energy efficiency. By 2100, non-fossil fuels in REF contribute 58% of the total primary energy use and the share of natural gas reaches almost 40%. The energy and industry CO, emission growth in the ASIA region of the AlB marker scenario is very high, reflecting rapid economic growth and high energy demand. By 2100 the total primary energy use in this region exceeds the 1990 level more than 10 fold. Standardized COj emissions increase from 1.15 GtC in 1990 to 5.73 GtC in 2050 and then drop to 5.27 GtC in 2100 (Figure 5-14, Table 5-13c). By 2100 contributions from the two major energy sources, non-fossil fuels and natural gas, are 69% and 25%, respectively.
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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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Page 247 and 248: Emission Scenarios
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Page 295 and 296: Emission Scenarios 287 -OECD90 REF
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Page 329: SPECIAL REPORT ON EMISSIONS SCENARI
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Ill Definition of SRES World Re
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Definition of SRES World Regions Me
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336 Six Modeling Approaches Six Mod
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338 Six Modeling Approaches e < .S
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340 Six Modeling Approaches Populat
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342 Six Modeling Approaches Table I
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344 Six Modeling Approaches Table I
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346 Six Modeling Approaches for dev
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348 Data Description Database Descr
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350 Data Description Table V-2. Lis
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Open Process
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Open Process 355 Table VI'2: SRES w
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Open Process 357 1Г)-ч);ОООЧ
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Open Process 359 Preliminary Al Mar
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Open Process 361 Preliminary Al Mar
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Open Process 363 Table VI-4b: Stand
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Open Process 365 Preliminary A2 Mar
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Open Process 367 Preliminary A2 Mar
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Open Process 369 Preliminary Bl Mar
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Open Process 371 Preliminary Bl Mar
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Open Process 373 Table VI-4d: Stand
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Open Process 375 Preliminary B2 Mar
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Open Process 377 Preliminary B2 Mar
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380 Statistical Table Table VII.l:
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3S2 Statistical Table Marker Scenar
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384 Statistical Table Marker Scenar
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386 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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412 Statistical Table Scenario AlC-
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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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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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