&EPA
             United States
             Environmental Protection
             Agency
             Potic
             And Evaluation*
             (PM-221)
21P-2003.3
December 1990
Policy Options For
Stabilizing Global Climate
Report To Congress
Technical Appendices

                                          Printed on Recycled Paper

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POLICY OPTIONS FOR STABILIZING GLOBAL CLIMATE
                 REPORT TO CONGRESS
                           Appendices






                Editors: Daniel A. Lashof and Dennis A. Tirpak
                United States Environmental Protection Agency




                  Office of Policy, Planning and Evaluation









                          December 1990

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  This   document  has  been   reviewed  in  accordance  with   the   U.S.
  Environmental  Protection  Agency's and  the Office of Management and
  Budget's  peer  and  administrative review policies  and  approved  for
  publication.   Mention  of trade names or commercial products does not
  constitute endorsement or recommendation for use.
 Publisher's Note:

 Policy Options for Stabilizing Qlobal Climaie, Report to Congress has been
 published in three parts:

 21P-2003.1   MAIN REPORT (includes Executive Summary)

 21P-2003.2   EXECUTIVE SUMMARY

 21 P-2003.3   TECHNICAL APPENDICES

 Those who wish to order the Main Report or Technical Appendices should
 inquire at the address below:

 Publications Requests
 Climate Change Division (PM-221)
 Office of Policy, Planning and Evaluation
 U.S. Environmental Protection Agency
401 M Street, S.W.
Washington, D.C.  20460

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                            TABLE  OF CONTENTS

                                                                                 Page


                                    APPENDIX A

                               MODEL DESCRIPTIONS

PREFACE	   A-l

INTRODUCTION  	   A-2
     Purpose and Structure of the Atmospheric Stabilization Framework	   A-2
           Emissions Modules 	   A-4
           Atmospheric Composition Module  	,	   A-6
           Ocean Circulation and  Uptake Module	^	   A-7
           Algorithms Used to Estimate Increases in Radiative Forcing	   A-7
           Unknown Sink	   A-7

ENERGY EMISSIONS MODULE  	   A-7
     Introduction	   A-7
     Regional Supply and Demand Models	   A-8
           Energy Flow: Primary Production  to End Use	   A-9
     Basis for Determining Energy Prices 	   A-ll
     Estimating Primary Energy Supply	   A-12
           Fossil Fuels	   A-12
           Hydropower	   A-13
           Nuclear Energy	   A-13
           Solar Energy	   A-15
           Commercial Biomass	   A-15
           Calculating Prices for Primary and Secondary Energy	   A-15
           Estimating Synfuel Conversion  	   A-16
           Modeling Electricity Generation  	   A-16
     Estimating Energy Demand	   A-19
           Bottom-Up Approach:  Energy Demand Through 2025	   A-20
           Top-down Approach: Energy Demand Beyond 2025 	   A-26
           Interface to the End-Use Models	   A-27
           Implementation of Capital Stock  	   A-28
     Estimating Greenhouse And  Related Emissions  	   A-29

INDUSTRIAL EMISSIONS MODULE	'.	   A-31
     Estimating Emissions of CFCs and Halons	   A-31
     Estimating Emissions of CH4 from Landfills   	   A-32
     Estimating CO2 from the Production of Cement	   A-32

AGRICULTURAL EMISSIONS MODULE	   A-35
     Introduction	   A-35
     Estimating Agricultural Activities through 2050:  The Basic Linked System 	   A-35
           National Models  	   A-38
           Regional Models  	   A-42
           Treatment of Agricultural Variables	   A-42
     Completing And Expanding The Estimates Through 2100	   A-44
     Estimating Emissions of Trace Gases	   A-46
           Methane from Rice 	   A-46
           Methane Emissions from Enteric Fermentation in Domestic Animals 	   A-47
           N2O Emissions from Fertilizer Use and Legumes	   A-49
           Emissions from the Burning of Agricultural  Wastes 	   A-49

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LAND-USE CHANGES AND NATURAL EMISSIONS MODULE	  A-49
     Estimating Natural Emissions of Trace Gases  	  A-50
     Estimating Emissions from Changing Land Use	  A-50
           Flux of CO^ Between the Atmosphere and Land Resulting from
           Deforestation and Reforestation	  A-51
           Emissions of N2O, CH^ NO^ and CO	  A-54

ATMOSPHERIC COMPOSITION MODULE	  A-57
     Estimating the Atmospheric Content of Long-Lived Trace Gases  	  A-57
     Measuring Changes in Climate  	  A-61
     The Stratosphere	  .  A-63
     Tropospheric Chemistry	  A-65
     Feedbacks	  A-65
           CO2 Uptake by the Oceans	  A-66
           Methane Emissions 	>	  A-66
           CO2 Emissions 	t	  A-66
           Vegetation Albedo	.J	  .  A-66

OCEAN CIRCULATION AND UPTAKE MODULE	  A-66
     Integrated Box-Diffusion Model	  A-67
     Alternative CO2/Ocean Uptake Models	  A-68

REFERENCES	  A-69
                                    APPENDIX B

                       IMPLEMENTATION OF THE SCENARIOS

DESCRIPTIVE OVERVIEW OF THE SCENARIOS	   B-l
      Scenarios with Unimpeded Emissions Growth	   B-3
      Scenarios with Stabilizing Policies and Accelerated Emissions	   B-4

MACROECONOMIC ASSUMPTIONS FOR THE ATMOSPHERIC
STABILIZATION FRAMEWORK 	   B-5
      Population Growth Rates	   B-5
      Economic Growth Rates		   B-6
      Oil Prices	: .	   B-9

ENERGY	....;..		   B-9
      Energy Demand	 .  ........   B-9
           Transportation	  B-9
           Residential and Commercial Sectors	  B-ll
           Industrial and Agricultural Sectors	  B-ll
      Energy Supply		  B-19
           Production Costs for Fossil Fuels	  B-19
           Gas Flaring Rates	  B-23
           Refinery Efficiencies and Costs	  B-23
           Hydroelectric Resources 	  B-26
           Solar Energy Costs	  B-26
           Nuclear Power Costs   	  B-27
           Biomass Energy Costs and Availability	  B-27
           Synthetic Fuel Costs ..',.•		...  B-29
           Transportation Costs  in the Atmospheric Stabilization Framework 	  B-29
           Distribution Cost Assumptions For The Atmospheric Stabilization Framework . .  .  B-31
           Generation Efficiency	  B-31
      Emission Control Assumptions	  .  B-32
      Carbon Fees	  B-36

                                          vi

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     Results of the Energy Scenarios	   B-36
          Energy Prices	,	   B-36
          Energy Use and Emissions	   B-36

CHLOROFLUOROCARBON AND HALON EMISSIONS  	   B-38

DEFORESTATION	   B-38

AGRICULTURE	   B-41

GREENHOUSE GAS EMISSIONS	   B-41

REALIZED AND EQUILIBRIUM WARMING	   B-43

NOTES	   B-46

REFERENCES  	:	   B-46
                                                                  c.


                                  APPENDIX C

                             SENSITIVITY ANALYSES

FINDINGS	   C-l

INTRODUCTION	 . ,	   C-6

ASSUMPTIONS ABOUT THE MAGNITUDE AND TIMING OF
GLOBAL CLIMATE STABILIZATION STRATEGIES 	   C-6
     No Participation by the Developing Countries  	   C-6
     Delay in Adoption of Policies	   C-9

ASSUMPTIONS AFFECTING RATES OF TECHNOLOGICAL CHANGE 	   C-9
     Availability of Non-Fossil Technologies	   C-9
     Cost and Availability of Fossil Fuels	   C-ll
          High Coal Prices	   C-ll
          Alternative Oil and Natural Gas Supply Assumptions	   C-ll
     Availability of Methanol-Fueled Vehicles	   C-17

ATMOSPHERIC  COMPOSITION: COMPARISON OF MODEL RESULTS
TO ESTIMATES  OF HISTORICAL CONCENTRATIONS	   C-17

ASSUMPTIONS ABOUT TRACE-GAS SOURCES AND STRENGTHS	   C-18,
     Methane Sources	   C-18
     Nitrous Oxide Emissions From Fertilizer	   C-21
          Anhydrous Ammonia	   C-21
          N2O  Leaching From Fertilizer  	   C-21
     N2O Emissions From Combustion	   C-24

UNCERTAINTIES IN THE GLOBAL CARBON CYCLE 	   C-24
     Unknown Sink In Carbon Cycle	   C-24
     Amount of CO2 From Deforestation	   C-27
     Alternative CO2 Models of Ocean Chemistry and Circulation	   C-31

ASSUMPTIONS ABOUT CLIMATE SENSITIVITY AND TIMING	   C-31
     Sensitivity of the Climate System	   C-31
     Rate of Heat Diffusion	   C-33
                                       vii

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ASSUMPTIONS ABOUT ATMOSPHERIC CHEMISTRY:
A COMPARISON OF MODELS  	   C-33
     Model Descriptions	,	   C-36
          Assessment Model for Atmospheric Composition	•	   C-36
          Isaksen Model	  G-36
          Thompson et al. (1989) Model	,	,	   C-37
     Results from  the Common Scenarios  	   C-37

EVALUATION OF UNCERTAINTIES USING AMAC 	'.	   C-40
     Atmospheric Lifetime of CFC-11	   C-40
     Interaction of Chlorine with Column Ozone	   C-44
     Sensitivity of Tropospherie Ozone to CH4 Abundance	,	   C-44
     Sensitivity of OH to NOX	   C-44

BIOGEOCHEMICAL FEEDBACKS	   C-46
     Ocean Circulation  	   C-46
     Methane Feedbacks	:	   C-46
     Combined Feedbacks	   C-46

NOTES	   C-51

REFERENCES  	   C-51
                                       via

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                                   LIST OF  FIGURES
APPENDIX A

     A-l        Structure of the Atmospheric Stabilization Framework   .	  A-3
     A-2        Geopolitical Regions of Climate Analyses  	  A-5
     A-3        Energy Flows   	A-10
     A-4        Supply Model  	A-14
     A-5        Capital Stock Approach	 A-18
     A-6        Typical Outline of a National Model	A-40
     A-7        Tropical Forest Response Curves 	 A-53
APPENDIX B

     B-l
CO2 Emissions from Tropical Deforestation   	  B-42
APPENDIX C
     C-l        Increase in Realized Warming When Developing Countries
                Do Not Participate	  C-8
     C-2        Increase in Realized Warming Due to Global Delay in Policy Options 	 C-10
     C-3        Availability of Non-Fossil Energy Options  	 C-12
     C-4        Impact of 1% per Year Real Escalation in Coal Prices   	 C-13
     C-5        Impact of Higher Oil Resources on Total Primary Energy Supply   	 C-15
     C-6        Impact of Higher Natural Gas Resources on Total Primary Energy Supply	 C-16
     C-7        Realized Warming Through 1985  	 C-19
     C-8        Increase in Realized Warming Due to Changes in the Methane Budget  	 C-23
     C-9        Change in Atmospheric Concentration of N2O Due  to Leaching	 C-25
     C-10       Change in Atmospheric Concentration of N2O Due  to Combustion  	 C-26
     C-ll       Impact on Realized Warming Due to Size of Unknown Sink  	 C-28
     C-12       CO2 From Deforestation Assuming High Biomass  	 C-29
     C-13       Impact of High Biomass Assumptions on Atmospheric Concentrations of CO2  .  . C-30
     C-14       Comparison of Different Ocean Models  	 C-32
     C-15       Impact of Climate Sensitivity on Realized Warming  	   C-34
     C-16       Increase in Realized Warming Due to Rate of Ocean Heat Uptake  	 C-35
     C-17       Regional Differences for Urban Areas with Different Emissions
                of CO and NO  	 C-41
     C-18       OH and Ozone Perturbations in the Isaksen and Hov Model  	 C-42
     C-19       Sensitivity of Atmospheric Concentration of CFC-11 to Its Lifetime  	 C-43
     C-20       Increase in Realized Warming Due to Rate of Interaction of Clx
                With Ozone   	 C-45
     C-21       Increase in Realized Warming Due to Change in Ocean Circulation	 C-47
     C-24       Increase in Realized Warming Due to Methane Feedbacks  	   C-48
     C-25       Increase in Realized Warming Due to Change in Combined Feedbacks  	 C-50
                                              IX

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                                    LIST OF TABLES
APPENDIX A

     A-l        Sector/Subsector Disaggregation in Industrialized Countries  	A-21
     A-2        Sector/Subsector Disaggregation in Developing Countries   	  A-25
     A-3        Differences in Emission Rate by Sector  	A-30
     A-4        Release Profiles for CFC-11  	A-33
     A-5        Assumptions Concerning Methane Emissions from Landfills  	A-34
     A-6        Regional  Disaggregation of BLS   	  A-36
     A-7        Agricultural and Non-Agricultural Commodity Classes 	  A-39
     A-8        Structure and Approach Used to Estimate Fertilizer Use  	  A-43
     A-9        Structure and Approach Used to Estimate Rice Acreage   	A-44
     A-10       Structure and Approach Used to Estima.te Ruminants 	  A-45
     A-ll       1984 Animal Populations and Emission Estimates	  A-48
     A-12       Estimates of Current Emissions from Burning of Agricultural Wastes  	A-50
     A-13       Estimates of Current Emissions from Natural Sources	A-51
     A-14       Fate of Carbon in Undisturbed Ecosystems After Land is Cleared
                for Agriculture   	'.....'	  A-52
     A-15       Carbon in Vegetation and Soils of Different Land-Use Categories in
                the World's Major Tropical Regions  	  A-54
     A-16       Annual Rates of Deforestation (1975-80)	A-55
     A-17       Estimates of Current Emissions from Land-Use Change	  A-56
     A-18       Participants, Contributors, and Reviewers Workshop: A Model for
                Atmospheric Composition	A-58
     A-19       Long-Lived Gases	A-59
     A-20       Short-Lived and Implicitly Solved  Species  	A-60
     A-21       Global Lifetime Assumptions for Long-Lived Gases	  A-62
     A-22       Models of Changes in Forcing	  A-64


APPENDIX B

     B-l        Overview of Major Scenario Assumptions	  B-2
     B-2        Global Population Estimates: 1985-2100  	  B-7
     B-3        World Bank GDP Growth Assumptions: 1986-1995  	  B-8
     B-4        GDP Growth Assumptions	  B-10
     B-5        Assumptions on Vehicle Ownership  and Amount of Travel  	  B-12
     B-6        Average Fuel Efficiency of Cars and  Light Trucks  	  B-13
     B-7        Demographic Changes in the Residential Sector for  Industrialized Countries  ....  B-14
     B-8        Average Improvements in Energy  Intensity in the Residential/Commercial
                Sector in  Industrialized Countries	 . .	.s B-15
     B-9        Key Assumptions in the Residential  Sector of the Developing Countries
                Through 2025			  B-16
     B-10       Key Assumptions in the Commercial Sector of the Developing Countries
                Through 2025	  B-17
     B-ll       Per Capita Production of Basic Materials in Industrialized Countries  	  B-18
     B-12       Energy Efficiency Improvement in the Industrial Sector 	  B-20
     B-13       Key Assumptions in the Industrial Sector of the Developing Countries
                Through 2025  	  B-22
     B-15       Minimum Extraction Cost Curves  for Natural Gas	  B-24
     B-16       Minimum Extraction Cost Curves  for Oil  .	  B-25
     B-17       Minimum Extraction Cost Curves  for Coal  	  B-25
     B-18       Hydroelectric Resources   	  B-26
     B-19       Future World Wide Biomass Energy Potential 	  B-28
     B-20       Cost of Synthetic Fuel Technologies  	  B-30
     B-21       Emission  Rate Differences by Sector 	  B-33

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     B-22       Emission Control Performance  	  B-34
     B-23       Energy Prices   	  B-37
     B-24       Primary Energy Supply in the SCW	  B-49
     B-25-31     Primary Energy Supply by Oil, Gas, Coal, Biomass, Hydroelectric, Nuclear,
                and Solar, Respectively, in the SCW   	  B-49
     B-32       Primary Energy Consumption in the SCW		  B-51
     B-33       Secondary Energy Consumption:  Fuel Versus Electricity in the SCW   	  B-51
     B-34-36     Secondary Fuel Consumption by Oil, Gas, and Solids, Respectively, in
                the SCW  	,	  B-52
     B-37       Residential/Commercial Energy Consumption: Fuel Versus Electricity
                in the SCW	'	  B-53
     B-38       Industrial Energy Consumption:  Fuel Versus Electricity in  the SCW   	  B-54
     B-39       Transportation Energy Consumption: Fuel Versus Electricity in the SCW  	  B-55
     B-40       Electric Utility Energy Consumption	  B-56
     B-41       Energy Conversion Efficiency at  Electric Utility Power Plants in the SCW	  B-56
     B-42       Synthetic Production of Oil and  Gas in the SCW		  B-56
     B-43       Energy Used for Synthetic Fuel Production by Type in the  SCW  	  B-57
     B-44       CO2 Emissions from Fossil Fuel in the SCW	  B-58
     B-45       CO Emissions from Fossil Fuel in the  SCW		  B-58
     B-46       NOX Emissions from Fossil Fuel in the SCW  	  B-58
     B-47-69     Same tables as B-24-46 in the RCW Case	  B-59
     B-70-92     Same tables as B-24-46 in the RCWA  Case   	  B-69
     B-93-115    Same Tables as B-24-46 in the SCWP Case   	  B-79
     B-116-138   Same Tables as B-24-46 in the RCWP Case	  B-89
     B-139-161   Same Tables as B-24-46 in the RCWR Case   	  B-99
     B-162      Chlorofluorocarbon Emissions by Scenario   	  B-39
     B-163      Production of  Wheat in the SCW and  SCWP	  B-109
     B-164      Production of Rice in the SCW and SCWP	  B-109
     B-165      Production of Coarse Grains in the SCW and SCWP  	  B-109
     B-166      Production of Meats in the SCW and SCWP	  B-109
     B-167      Production of Dairy Products in  the SCW and SCWP	  B-110
     B-168      Production of Other Animals and in the SCW and SCWP  	  B-110
     B-169      Nitrogenous Fertilizer Use in the SCW and SCWP   	  B-110
     B-170      Land Under Rice Cultivation in  the SCW and SCWP  	  B-110
     B-171-178   Same Tables as B-163-170 in the RCW, RCWA, RCWP, and RCWR Cases	  B-lll
     B-179      CO2 Emissions by Type in the SCW	  B-113
     B-180      N2O Emissions by Type in the SCW   	  B-113
     B-181      CH4 Emissions by Type in the SCW   	  B-113
     B-182      NOX Emissions by Type in the SCW   	  B-113
     B-183      CO Emissions by Type in the SCW 	  B-114
     B-184-188   Same Tables as B-179-183 in the RCW Case  	  B-115
     B-189-193   Same Tables as B-179-183 in .the RCWA Case  	  B-117
     B-194-198   Same Tables as B-179-183 in the SCWP  Case  	  B-119
     B-199-203   Same Tables as B-179-183 in the RCWP Case	  B-121
     B-204-208   Same Tables as B-179-183 in the RCWR  Case  	  B-123
     B-209      Realized Warming for 1.5-5.5°C  Sensitivities   	  B-44
     B-210      Equilibrium Warming for 1.5-5.5°C Sensitivities  	  B-45
APPENDIX C
     C-l        Impact of Sensitivity Analyses on Realized Warming and Equilibrium Warming  . . .  C-3
     C-2        Comparison of Model Results to Concentrations in 1986	  C-20
     C-3        Low and High Anthropogenic Impact Budgets for Methane 	  C-22
     C-4        Comparison of Emission Estimates for EPA #1-8, RCW and SCW Cases  	  C-38
     C-5        Comparison of Results from Atmospheric Chemistry Models for the  Year
                2050 Compared to 1985	  C-39
                                              XI

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                                   APPENDIX A

                           MODEL  DESCRIPTIONS
PREFACE

     This appendix describes the approaches
and modeling  techniques used to estimate
future  global warming.   The appendix is
intended  to  serve  as  a summary;  detailed
descriptions of the different  models  can be
obtained  from  the  papers and reports  cited
here. Data sources and scenario specifications
are presented in Appendix B.

     This  appendix  draws  heavily  from
separate papers and reports prepared for U.S.
EPA and  includes  some edited  sections of
these reports.   We would like  to  cite the
following works that faU within this category:

•    Frohberg, Klaus K., Phil  R.  Van de
     Kamp,    1988,   Results   of   Eight
     Agricultural   Policy    Scenarios   for
     Reducing Agricultural Sources of Trace
     Gas   Emissions.       Center   for
     Agricultural and  Rural Development,
     Iowa State University, Ames, Iowa;

•    Houghton, R.A.   1988.  The  Flux of
     CO2 between Atmosphere and  Land as
     a   Result   of   Deforestation   and
     Reforestation from  1850 to 2100.   The
     Woods Hole  Research  Center;
ICF Incorporated,    1988.    Global
Macro-Energy Model Summary Paper.
ICF Incorporated;

Mintzer,  I.M.  1988.  Projecting Future
Energy   Demand   in   Industrialized
Countries:   An   End-Use   Oriented
Approach.  World Resources Institute,
Washington, D.C.;

Prather,  M.   1989.   An  Assessment
Model  for Atmospheric Composition.
Proceedings of  a  workshop  held  at
NASA Goddard  Institute  for  Space
Studies,  January  10-13, 1988,  NASA
Conference  Publication  3023,  New
York, 64 pp.; and

Sathaye,   J.A.,  A.N.   Ketoff,  LJ.
Schipper, and  S.M. Lele.   1988.  An
End-Use  Approach to Development  of
Long-Term Energy Demand  Scenarios
for Developing Countries. International
Energy Studies Group, Energy Analysis
Program,   Lawrence    Berkeley
Laboratory, Berkeley, CA.
                                          A-l

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Policy Options for Stabilizing Global Climate
INTRODUCTION

Purpose and Structure of the Atmospheric
Stabilization Framework

      This  appendix   describes  how  the
Atmospheric Stabilization Framework (ASF)
estimates  the magnitude  of possible future
greenhouse  warming  and  the  impact  of
different   strategies  to  stabilize climate -
identifying the different  natural, physical, and
economic   processes   that   affect   future
warming,  and  then .describing  how  those
processes  are modeled.

      The primary purpose  of the ASF is to
provide  a  tool  that   can  estimate  the
magnitude  of  future  greenhouse  warming
under  a  wide variety of  assumptions  about
variables  that  effect  trace gas  emissions,
atmospheric chemistry, and  temperature rise.
The ASF allows the  user  to  measure  the
relative   impacts   of   different   climate
stabilization  policies,   as   well  as   the
importance  of uncertainties  that are inherent
in the data and parameter assumptions, within
a forfhat that is internally consistent.

      The different assumptions required for
the,ASF  that can effect estimates of future
warming fall  into  three  categories:   data;
parameters,   algorithms,  and  models;  and
stabilization strategies. The  data assumptions
range from  estimates of energy resources and
production costs to assumptions about future
growth in population, growth in income, and
current emissions of trace  gases from  the
different natural and anthropogenic processes.
The   assumptions   about    parameters,
algorithms,  and models include variations in
how  energy supply  and  demand  can  be
modeled,  the elasticity of energy supply and
demand to income and  prices, the impact of
changes in  emissions of  the different trace
gases on concentrations of  short-lived gases
such as tropospheric ozone, and the rate of
change of CO2 and heat uptake by the oceans
over time as CO2 concentrations and radiative
forcing change.     Stabilization  strategies
include the  use  of  control technologies to
reduce emissions from energy combustion and
strategies  to shift between energy sources,
reduce  energy  consumption,   and   reduce
emissions from livestock and rice production.
      The ASF explicitly deals with the gases
identified  in  the  literature  as  the  most
important  contributors,  either  directly or
indirectly,  to  future  greenhouse  warming.
With the exception of water vapor arid clouds,
the ASF estimates atmospheric concentrations
of the gases.  The impact of water vapor and
clouds on climate warming is captured in the
parameter  that  defines  climate  sensitivity.
Trace gases explicitly represented in the ASF
that directly affect greenhouse warming include
CO2, CH4, N2O, CFC-ll, CFC-12, HCFC-22,
CFC-113,  CC14,  CH3CC13,  halon  1301, and
tropospheric  ozone;  those  that  haye  an
indirect impact on warming include NOX and
CO.   Volatile Organic Compounds (VOCs)
are included in  the atmospheric composition
module, but changes in emissions over time
are not included at this time. For simplicity,
all of the gases will be  referred  to  in this
appendix  as  greenhouse  gases,  although
strictly speaking,  NOX  and  CO  are not
greenhouse gases.

      The ASF  combines  input  data,  user
scenario specifications, and different  models
to estimate trace gas emissions, changes in the
atmospheric concentrations of the trace gases,
ocean  uptake   of heat   and  CO2,   and
temperature  rise.    The  ASF  provides  a
structure so that emissions  of the different
trace  gases from the different sources are
consistent with input  assumptions  such as
assumptions of  future population, income,
efficiency, etc.  The ASF is  designed to run
on a personal computer where all but a few
of the components are completely specified
and run  during  a session.    Several  of the
components are  run on separate  computers
due to  program  size  and  complexity, and
output from these runs is combined through
data  files  (e.g.,  agricultural  activities are
estimated by an integrated set of 34  models
on a minicomputer and the results of  these
models are transferred to the ASF through
data files).

      Figure  A-l  illustrates  the  overall
structure of the ASF.  It  consists of four
emissions  modules     ~ energy,  industrial,
agricultural, and land-use change and natural
emissions ~ which estimate emissions of the
different  trace  gases  based  on  input  data
assumptions on  population, income, energy
                                            A-2

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                                              Appendix A: Model Descriptions
                               FIGURE A-l
    STRUCTURE OF THE ATMOSPHERIC STABILIZATION FRAMEWORK
  Inputs
 Base case
Assumptions

 Resources

 Population
  Growth

Productivity

Technology
 Alternative
 Strategies
 Emissions
Forecasting
  Modules
Concentration
•• *
Determination
Modules

Atmospheric
Composition
i







1




r
Ocean




                                                             Outputs
                                            Atmospheric
                                           Concentrations
                                               and
                                            Temperature
                                              Change
                                  Feedbacks
                                  A-3

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Policy Options for Stabilizing Global Climate
resources  and  costs,  control  technologies,
control strategies, and'current emissions. The
atmospheric composition and ocean CO2 and
heat uptake modules estimate the changes in
the atmospheric concentrations of greenhouse
gases,   radiative    forcing,    and   global
temperature.  A feedback parameterization
estimates  changes  in emissions rates  due  to
changes in global temperatures.

      Figure A-2  illustrates  the  regional
structure  of the  ASF.   It  disaggregates
emissions   into  four  regions consisting  of
developed nations  and five regions consisting
of developing nations:

Developed Nations

•     U.S.

•     Western OECD    Canada and
                        Western Europe
      Eastern OECD
•     Centrally-
      Planned Europe

Developing Nations

•     Centrally-
      Planned Asia
•     Middle East

•     Africa

•     Latin America

•     South and East
      Asia
Japan, Australia,
New Zealand, and
other eastern
OECD nations

USSR and Eastern
Europe
China, North
Korea, Vietnam,
and other
Centrally-Planned
Asian Economies
Indian Pakistan,
Bangladesh,
Thailand,
Indonesia, and the
remainder of Asia
not included in the
other regions
All of the models within the energy module
provide  energy   supply,   demand,  and/or
emission estimates for each of these regions
separately. The agricultural module provides
detailed estimates of agricultural activities for
the  34  regions  that reflect  the regional
structure of the agricultural activities model
(Basic Linked System), but provides emissions
estimates  for the nine regions listed above.
The  other  emissions   modules  provide
emission estimates for these nine regions, for
the northern\southern hemisphere, or  for the
world as a whole, depending on the module,
the trace gas, and the emission source.

      The  primary  method  of implementing
the interface between the different modules is
the use of scenario description files  and the
integrating model interface files and routines.
For each  scenario,  the scenario description
file contains an identifier for the scenario, a
brief description of  the scenario, and a list of
all  of the data files used to implement the
scenario.   The integrating  model interface
files  contain   detailed  output   from   the
different  modules,  including  trace   gas
emissions,  atmospheric concentrations,  and
data on such activities as energy production
and  consumption,  fertilizer   use,    and
agricultural  production.     The  integrating
model interface routines provide the interface
between the models and the interface file.

      Each of the individual pieces that make
up   the  ASF  is   described  below.    The
remainder of the appendix describes each of
the components in some detail; these detailed
descriptions are  qualitative  and  refer  the
reader to Appendix B for more detail on the
data  assumptions  and   sources  used  to
implement  the  different   scenarios   and
sensitivities.

Emissions Modules                         ^

      Energy  Module.  The  energy  module
estimates   the   emissions   of  trace  gases
resulting from the production, transportation,
distribution, and consumption of fossil fuels.
It  is comprised of  a set  of detailed global
energy end-use  models (DEMAND) and the
Global  Energy  Supply  Model (SUPPLY),
which estimates energy supply and locates the
energy supply/demand balance.

      The end-use models provide a detailed
picture  of energy consumption in the  nine
regions  based  on   future  population   and
income. In developing countries, the end-use
                                            A-4

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                                                              Appendix A: Model Descriptions
                                           FIGURE A-2
                 GEOPOLITICAL REGIONS OF CLIMATE ANALYSES
 KEY:
  1. United States
  2. OECD Europe/Canada
  3, OECD Pacific
  4. USSR/Centrally Planned Europe
  5. Centrally Planned Asia
•  6. Middle East        ^
  7. Africa
  8, Latin America
  9. South and East Asia

  Source: Adapted from Edmonds & Reiily, 1,983a, in Mintter, 1988.
                                               A-5

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Policy Options for Stabilizing Global Climate
models   use  current  energy-consumption
patterns  of  different  countries  to represent
the level  of energy use at  different  levels of
income    and economic  growth.   As  the
income and population increase over time, the
energy patterns in the five  developing regions
change to reflect this growth and any changes
projected due to increases in energy prices
and/or improvements in energy efficiency.

      The  Global  Energy Supply  Model
combines the end-use models with a supply
model within an equilibrium framework that
adjusts energy prices to balance energy supply
and demand.  The supply model estimates
future energy  supply  of  fossil, biomass,
nuclear, solar, and hydro energy sources.  The
model accounts for such factors as resource
depletion, technology improvements, energy
prices,  constraints   to  proliferation,   and
production constraints.

      The  Global  Energy Supply  Model
estimates emissions  of  trace gases using a
capital stock approach that accounts  for the
inherent  inertia resulting from the investment
in   energy   supply   systems   and    the
infrastructure  to  use  that  energy.    The
approach keeps track of different vintages of
technologies that consume energy and allows
for the  future use of more energy-efficient
stock,  technologies   that  produce  fewer
emissions,   and  the   implementation  of
emission controls.

      Industrial  Emissions  Module.     The
industrial   non-energy-related   emissions
include three categories of emissions: CFCs
and halons, CH4 from landfills, and CO2 from
cement production. The U.S. EPA Integrated
Assessment Model is used to estimate future
emissions of CFCs and halons.   This model
accounts  for emissions related to the chemical
production and use of these substances and
for  emissions  that  result  from  product
decomposition.  The model  allows for  the
implementation of various control strategies
and  accounts for alternative  scenarios of
compliance with those strategies. Estimates
of CH4 from landfills and CO2  from  cement
production  reflect  assumptions  concerning
current emissions and the relationships among
population,  income,  and growth  in   the
emissions.
      Agricultural    Emissions    Module.
Agricultural emissions include CH4 from rice
cultivation, CH4 from enteric fermentation in
domestic  animals, N2O  emissions  resulting
from  the  use of nitrogenous fertilizer, and
CH4,  N2O, NOX, and CO emissions resulting
from the burning of agricultural wastes.  The
agricultural   module  combines  a  detailed
regional agricultural model with an emissions
model that applies emission coefficients to the
detailed  rice  paddy  area,  meat  and dairy
production,   and  fertilizer   use  from   the
agricultural model. The emissions model ties
emissions resulting   from  the  burning  of
agricultural  wastes to  land  use  from  the
agricultural model.

      Land-Use    Changes    and   Natural
Emissions Module. The land-use changes and
natural  emissions  module   captures   those
emission sources not represented within  the
other modules.    These emissions  sources
range from  CH4  from  termites  and small
herbivores and  naturally   occurring N2O
emissions from  land  and ocean  sources  to
emissions of gases from deforestation and
non-agricultural   biomass  burning.     The
approach  used  to estimate future emissions
varies considerably by emissions source;  the
Marine   Biological   Laboratory/  Terrestrial
Carbon   Model   (MBL/TCM)  is  used   to
estimate emissions of CO2 from deforestation
and reforestation (Houghton, 1988).

Atmospheric Composition Module

      The atmospheric composition module
uses the emissions estimates  produced by the
emissions modules and estimates  changes in
the  atmospheric   concentrations  of   the
greenhouse gases (Prather, 1989).  The model
is   highly  parameterized    and   considers
feedbacks of increased  emissions, including
changes  to  stratospheric ozone,  increased
penetration   of  solar UV   radiation,  and
subsequent increased  destruction of some of
the long-lived gases.  Other feedbacks include
the impact  of emissions on the levels  of
tropospheric   ozone  and    OH   and   the
subsequent impact on the oxidization of gases
such as CH4.
                                           A-6

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                                                            Appendix A: Model Descriptions
Ocean  Circulation and Uptake Module

      The ASF accounts for  the net flux of
CO2 and heat between  the atmosphere and
the oceans with a box-diffusion formulation
introduced  by Oeschger et al.  (1975)  and
utilized by Hansen et al. (1984, 1988).  Four
alternative  models  of  CO2  uptake  by the
ocean are included in this module to account
for some of the uncertainty in modeling this
process.

      The  box-diffusion model  represents
through a diffusion equation the turnover of
carbon and the flux of heat below an ocean
depth of 110 meters.  The  model includes a
mixed  layer  and a thermocline but no deep
ocean.  The coupling between climate change
and  CO2   uptake  is   captured  through
equations for  CO2 solubility and  carbonate
chemistry.

      The four alternative models provide the
capability to test the sensitivity of the results
to  different  approaches, to  modeling  the
uptake of CO2 by the ocean. Unlike the  box-
diffusion model which is directly coupled to
the  atmospheric   composition  model  (see
above), the alternative models do not capture
the coupling between ocean uptake of  CO2
and climate change. These models include an
alternate  box-diffusion  formulation,  which
includes a deep ocean, an advective-diffusive
model  based on work by Bjorkstrom (1979),
a  12-compartment regional model based on
work by Bolin et  al. (1983), and an outcrop-
diffusion  model   based   on   work   by
Siegenthaler (1983).

Algorithms  Used  to Estimate  Increases in
Radiative Forcing

     The  formulation  used  to estimate
radiative  forcing  due  to   increases  in
atmospheric concentrations of trace gases is
based on calculations from a one-dimensional
radiative convectfve model  (Hansen  et al.,
1981; Hansen et al., 1988; Ramanathan et al.,
1985).    Radiative  forcing  is translated to
temperature   change   using   the   zero-
dimensional   formulation    described   by
Dickinson (1986):

              Q  - A AT = F
where Q is radiative forcing, A is the climate
feedback  parameter,  AT  is  the  realized
warming, and F is the flux of heat  into the
ocean.  The model allows testing of  different
levels of climate feedback  by adjusting the
parameter A.

Unknown Sink
      The model is calibrated using estimates
from Rotty and Masters  (1985) of historical
CO2 emissions from  fossil-fuel  combustion
and  estimates  from  Houghton  (1988)  of
historical CO2 emissions from deforestation.

      Differences between CO2 concentrations
estimated  by the models  and from historical
measurements   are   resolved  through  the
unknown sink.  Behavior of the unknown sink
is allowed to vary in the future.

ENERGY  EMISSIONS MODULE

Introduction

      The  Global   Macro-Energy  Model
selected for use in the  ASF consists  of a
modified version  of  the  IEA/ORAU Long-
Term Global Energy-CO2 Model (Edmonds
and Reilly, 1986) in combination with detailed
end-use models. The IEA/ORAU Long-Term
Global Energy-CO2 Model was developed by
Jae Edmonds  and  John Reilly to  run  on a
personal computer and was released in  1985.
U.S. EPA modified the model to change the
time  steps,  improve  the   energy  supply
component, add emissions of four trace  gases
(CO,  CH4, N2O, and  NOX), interface with
detailed end-use models, and interface with
the ASF.  The detailed end-use models were s
developed at the World Resources Institute
(Mintzer,  1988)  and  Lawrence  Berkeley
Laboratory (Sathaye et al., 1988).

      The time  period of interest, 1985 to
2100, imposed certain  restrictions  on the
design of  the  energy model that  would not
necessarily be imposed on energy models with
shorter  time  horizons.   First, conventional
recoverable resources of oil and gas will  likely
be exhausted by 2100 assuming that  current
trends in consumption  continue.   It was
necessary, therefore,  that  the  model  keep
track of resources and resource depletion and
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Policy Options for Stabilizing Global Climate
simulate  shifts  away  from  the  use  of
conventional oil  and gas  to  other primary
energy sources, such as unconventional  oil
and gas, coal, synthetic fuels, and non-fossil
forms of electricity. The energy model had to
simulate how emissions of trace gases would
change  as  a result  of the  shift  in energy
supply.  This change in emissions could come
about as a result of a reliance on fuels with a
higher or lower carbon content per unit of
energy or on those that require  a substantial
amount of energy to convert them to a useful
form, such as synthetic fuels.  In  addition, the
model had to allow for the future use of non-
fossil technologies that may not  currently
exist,  such as fusion or large-scale biomass
projects:

      The extent of energy consumption over
the long term will be driven  by  a number of
factors,    including   growth   in    income,
development of industries, development of
electric  power capacity, and investment in
energy-consuming  projects  such   as  road
building and the development of mass transit
systems.      In   addition,  future  energy
consumption will depend on the  development
and/or improvement of end-use technologies,
such as steel-manufacturing processes, and the
energy-consumption  efficiencies of  vehicles,
home   appliances,  and  newly    designed
buildings. Finally, the model simulations had
to capture the potential differences in energy
consumption patterns in different parts of the
world   as  incomes  grow   and   end-use
technologies improve.

Regional Supply and Demand Models

      In the time frame of interest, 1985 to
2100, energy  markets  can be  expected to
undergo major fundamental changes. These
changes  include  what  energy  sources  are
exploited,  where  the  energy  sources  are
produced, how they are converted to useful
energy for end^use,  how the energy is used,
and  where the energy is used.  The model
captures these  changes  with regional supply
and demand models within a framework that
addresses both the  regional flow of energy
and  the conversion  of  energy from primary
energy sources  to  end use.

      For  each  model  run, an   internally
consistent  estimate  of  energy  supply  and
demand  is generated.  Energy prices provide
the key variables used by the model to create
this consistent picture.  Through a series of
calculations that  account for  transportation
costs, refining costs, distribution costs, synfuel
conversion costs, and  electricity generation
costs,  the  model  captures the  relationship
between  prices for energy at the  point of
production (e.g., wellhead prices for oil and
gas) and prices for the energy  seen  by end
users.  Energy supply  reflects supply  prices
(prices at the point of production)  and the
energy  demand  reflects  secondary  energy
prices  (prices seen by end users).

      As illustrated in  Figure A-2, the model
breaks the energy market down  into regions,
thus  allowing  consideration   of   regional
differences, which are  expected  to  influence
future energy supply and demand. As with all
models, the regional disaggregation represents
a  balance  between the  significance  of the
effect  that  regional  factors  have  on the
results, uncertainties inherent in the model,
and  the  difficulty of designing  and using a
model that incorporates greater or less detail.

      Regional  factors  that  affect  energy
supply include regional differences in energy
prices, resource endowments, extraction or
production  costs,   and   transportation
constraints.    The  most  important  factors
determining regional  energy  prices  are the
existence of a global energy market and the
costs   of  transporting  energy  from  the
producing areas to the consuming areas.  The
global market for crude oil provides  a  good
example  of regional energy price variations.
For example, for crude oil of similar quality,
prices  will generally run higher in the U.S.
than in the Middle East. This pattern reflects
the role  of the Middle  East in setting oil
prices  and the cost of transporting  the oil
from the Middle East  to the U.S.  Regional
prices also vary within the natural gas market
primarily  because  of  the  high  costs  of
transporting  natural gas either  overseas or
over long distances by land.  Large identified
reserves  of natural gas  remain unexploited
while gas reserves that  are more expensive to
develop and  produce,  but are closer to the
demand markets,  continue to be developed.

      The regional  endowments  of energy
resources as  well as the costs of producing
those resources can vary considerably.   For
example,  the Middle  East  contains  large
                                             A-8

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                                                              Appendix A:  Model Descriptions
resources of conventional crude oil that can
be produced for well  under $20  per  barrel.
The U.S. and Latin America together contain
nearly as much unconventional oil (e.g., oil
shale  or bituminous tar sands); however, those
resources, for the most  part, cost well over
$20  per barrel to  produce.   The cost  of
producing hydroelectric power also varies  by
region.   Both India  and Brazil contain large
untapped hydro resources, but the extent  to
which each country utilizes its hydro resources
will depend on the costs of transporting the
electricity   long   distances,  environmental
constraints,   capital  constraints,   and  the
availability of markets  for the electricity.

Energy Flow: Primary Production to End Use

      The model's simulation of the flow  of
energy from primary energy production to end
use can account for  future shifts in the types
of energy dominating the energy  markets  as
well as the introduction  of new technologies.
As shown in Figure A-3, the flow of energy
starts with the  production of primary  energy
of the following eight types:

•     conventional oil;

•     unconventional oil (includes enhanced
      oil recovery, tar sands, and shale oil);

•     natural   gas    (conventional   and
      unconventional);

•     coal;

•     hydropower;

•     nuclear energy (fission and fusion);

•     solar  energy; and

•     commercial biomass energy.
                        ?
      The model keeps track of a number of
steps  involving transportation, refining, and
distribution  of   energy,  along   with  the
conversion  of  primary energy to  secondary
energy suitable for end  use.  Each of these
steps  imposes costs on the final product and
may  result   in  losses  of  energy.   As   an
example, costs of transporting crude oil  or
natural gas from the wellhead to refineries or
end-use  markets will reflect the proximity of
the supply  source  to  the  destination and
whether  processing,  such  as conversion  to
liquified   natural  gas (LNG),  is  required.
Energy    use   for   transportation   usually
represents a  small  fraction  of the energy
transported (e.g., average 3% for natural gas
in  the  U.S.).    Refining  of  crude oil  to
petroleum products such as gasoline, distillate,
kerosene, and  residual fuel  oil incurs  both
fuel and  non-fuel  costs and  involves  the
consumption of energy (approximately 9% of
the energy refined).  Distribution costs  equal
the  costs  of  delivering  the  energy  to
individual consumers  and  can represent  a
large share of the total costs of energy costs
to  the  consumer  (e.g., distribution  costs
represented 20% of the average  delivered
price of gas in the U.S. in 1985).

      Conversion of  primary  energy  to
secondary energy includes also the conversion
of coal or biomass fuels  to liquid or gaseous
fuels and the conversion  of primary energy to
electricity.  These conversion activities  can
lead to energy losses of  over 70% as well as
substantial  non-fuel  costs.     Conversion
activities captured in the model include the
following:

•     conversion of coal and/or biomass to
      liquid or gaseous fuels;

•     conversion of coal, liquids, and gases to
      electricity;  and

•     conversion of  hydro, nuclear, and solar
      energy to electricity.

The cost  and  efficiency of these conversions
have changed  substantially  during  the past
several years and can be expected to change,
in the  fu'ture  as  well! For  example, current
technologies for  converting  gas to electricity
can be as much  as 25% more efficient than
technologies that  existed in 1978.  Similarly,
breakthroughs  in fuel-cell technology  could
lead to greater gains in conversion efficiency
in the future.

      The  model  completes  the  flow  of
energy by converting four types of secondary
energy -  liquids, gases, solids, and electricity
~ to end-use energy.   The  term end-use
energy can refer  to transportation, heat used
for cooking, cooling produced by refrigeration,
feedstock uses of energy, and to many  other
applications.  The conversion of secondary
                                             A-9

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Policy Options for Stabilizing Global Climate
                                FIGURE A-3

                            ENERGY FLOWS
    Coal
            Conversion
                            'Losses
                                      Electricity
                                      Generation
                                                                   -End-Use
Natural Gas


;

Synfuel Conversion





C

\.
-t^- Losses
/

V



Gases


                                                                   -End-Use
Solids
                                                                   -End-Use
        ^-End-Use
                                         Losses
                                   A-10

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                                                              Appendix A:  Model Descriptions
energy to  end-use energy can incur widely
varying losses of energy as well as non-fuel
costs associated  with the conversion.

Basis for Determining Energy  Prices

      Although  a  wide  variety  of  factors
(including  population, income, and regional
GNP) are assumed to influence future supply
and   demand,   the  model   assumes  that
balancing the supply and demand for energy
ultimately  will  be achieved  by    adjusting
energy prices to reduce or increase supply or
demand.   Energy  prices differ by region  to
reflect the regional market conditions, and by
type of energy to reflect supply constraints,
conversion costs, and the value of the energy
to end users.

      The  model  estimates this supply and
demand  balance  with  an iterative  search
technique to determine supply prices. Using
specified initial supply prices for oil, natural
gas, and  coal, the model locates  prices that
result in energy supply and demand where the
supply of each primary energy type equals the
demand for the energy.

      All  energy  prices  estimated  by  the
model are based on the supply prices for the
fossil  fuels,  that  is,  the  price that  energy
producers can expect to  receive for the fuels
at the wellhead  or at  the  mine.  The prices
reflect a marginal price  about which all but
the marginal producers can adjust their prices
over  their  production  costs.    The  price
structure  does  not,  however, account  for
differences in quality of the product (e.g., ash
content, sulfur content, specific gravity).

      Prices of similar types of crude can vary
by region  by as much  as $3.80  per barrel
(1988 U.S. dollars), and the price of natural
gas can  vary  by  as  much   as  $2.65 per
gigajoule (1988 U.S. dollars) (ICF, 1988).  In
actual  energy markets,  such  differences  in
supply prices reflect whether the regions are
importers   or   exporters  and  a   region's
relationship to the other import  and export
regions.  These relationships can change  as
supply and  demand and the roles of regions
as importers or exporters change over time.

      The   model  simplifies   this  complex
relationship  for each  type  of  energy  by
selecting a  region  that  will act as a major
exporter of the energy form and a region that
will act as a major importer of the energy, by
estimating  the costs of transporting the fuel
from  the selected  exporting region to the
selected importing region,  and by applying a
set of rules concerning the  relationship of the
supply prices  in other regions based on the
prices  in these two regions.  Using crude oil
as an   example,  the  marginal supply  and
demand regions selected were the Middle East
and the U.S., respectively.  Our estimate of
the cost of transporting the crude from the
Middle East to the U.S. equalled $3.80 per
barrel  (1988  U.S.  dollars).   The  rules for
assigning regional supply prices then followed:

•     Crude  oil  supply  prices  in  all  oil-
      exporting countries equaled the price of
      crude oil in the Middle East; and

•     Crude oil  supply prices in all  non-
      exporting regions were at least the
      price of crude oil in the Middle East
      and  at  most  that  price  plus  the
      marginal transportation  cost of $3.80
      per barrel.

For natural gas, the marginal transportation
costs equaled  $2.65 per gigajoule (1988 U.S.
dollars),  which   reflected  the  costs  of
liquefaction, transporting the LNG from the
marginal  exporter  (Middle  East)  to  the
marginal importer (U.S.), and  regasification.
The average transportation  costs for coal were
assumed to be $0.66 per gigajoule.

      This simplification represents  a  trade-
off  between   the   structure  originally
incorporated in the IEA/ORAU model, which
allowed  no regional  differences  in supply
prices due to transportation costs, and a more
complex representation  of the factors  that
determine these differences.  The inability of
the original model  to account for  regional
differences due to transportation cost resulted
in understating the price that producers could
receive from markets within that region.  The
approach we selected to determine  regional
supply prices allowed us to reduce the error
in the  regional  price  differentials  without
completely restructuring  the model.

      Secondary energy prices in each region
are based on the supply price for the marginal
export region, the interregional transportation
cost,  refining  and  distribution costs,  and
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Policy Options for Stabilizing Global Climate
regional tax  policies.   For  electricity,  the
secondary  prices  will  reflect  the  relative
proportions of each  fuel used to produce the
electricity, the secondary prices of those fuels,
the non-fuel costs of converting the fuels to
electricity,   and  the   efficiency   of   the
conversions.

Estimating Primary  Energy Supply

      The approaches used to estimate future
energy  supply vary according to the type of
energy because of fundamental differences in
how the energy source may be exploited over
time and how the energy is used. The way in
which fossil fuels are treated within the model
reflects the limitations in the resource base
and  the behavior  of available  supply and
extraction costs as the resource is  exploited.
The model's treatment of hydro, nuclear, and
solar sources reflect constraints on the annual
supply of each energy type,  estimates of how
the costs of producing the energy will change
over time,  and the impact of relative energy
costs  on  the share of  electricity  produced
from each  source.  Its treatment of biomass
sources reflects the potential availability of
this energy source and competition of biomass
energy with other commercial energy sources.

Fossil Fuels

      For crude oil, natural gas, and natural
gas   liquids,   the    model    provides   a
simplification of the physical and  economic
factors that influence the production of these
resources over time. The factors captured in
the model include the relationship between
prices  and  extraction costs,  the  impact  of
exploiting  finite   resources,  technological
improvements, and constraints on the rate of
production.

      Resources are defined within the model
according  to  the  concept  of  technically
recoverable' resources (which  should not be
confused with the concept of  oil-in-place or
gas-in-place) and represent the total estimated
production from the  resource  base that is
economic at  the prices estimated  by  the
model.  Recoverable resources are categorized
according to estimates of the cost of locating,
developing, and producing them. Estimates of
oil, gas, and natural gas  liquid resources and
of the  costs  of developing  and  producing
these resources are taken from the literature
(e.g., World  Energy Conference,  1980;  ICF,
1982;  U.S.  DOE,  1988).   Details  of these
resource  cost  curves  are  reproduced  in
Appendix B.

      The model  simulates  the  exploration,
development,   and  production   activities
through a number  of steps, which start  with
dividing   the  resource   base   into   four
categories: cumulative  production,  reserves,
economic   undeveloped    resources,   and
uneconomic undeveloped resources.  For  a
selected year in the time horizon, cumulative
production equals  all energy produced from
the resource prior  to that year, and reserves
at the beginning of the year equal reserves at
beginning of the previous year  plus  additions
to the reserves minus production.  Given  a
cost at the wellhead that producers are willing
to incur,  the  undeveloped resources can be
divided  into   economic   and   uneconomic
resources.  The fraction of resources that are
economic will change over time as  the price
changes and as technological  improvements
are  realized  in  locating,  developing,  and
producing the resources.

      Resource production involves a series
of steps, including locating,  developing, and
producing  reserves,  as  well  as  ongoing
maintenance and development.  The rate at
which these  activities  will  take  place  is
influenced by  a numbei of factors,  including
the ability to  locate all economic resources,
the lead time necessary before construction
can begin, the availability of capital, and the
rate at which the resources are produced from
wells.  The model simplifies  these factors by
estimating   the fate  at  which economic
undeveloped  resources  are  proved  and
converted  to  reserves,  and  by   using   a
production-to-reserves ratio  to estimate  the
rate at which reserves are produced.

      The   process  for  estimating   coal
production is very similar, but the factors that
influence production and production  costs are
very  different.   Unlike  oil  and gas,  coal
resources  are often close  to  the surface  and,
in many places, the locations are  known with
more certainty. Also, unlike many oil and gas
fields, which  are  developed to  exploit  the
resources  within  8  to  20  years  (thereby
maximizing  revenues  and  not   necessarily
minimizing costs),  a coal field is developed to
minimize costs or to supply energy to a large
                                            A-12

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                                                              Appendix A: Model Descriptions
electricity-generating  or  industrial  project
usually resulting in a  longer useful life.

      Figure  A-4  illustrates  the  approach
used  to  estimate  future fossil-fuel supplies.
The  model   starts   with  an   estimate  of
recoverable  resources and  a  marginal  cost
curve. The recoverable resources include only
those resources not produced  by 1985, and
the marginal cost curve represents how much
of the resource can be economically recovered
at different supply prices. The marginal cost
curve can change  over time as technological
improvements  reduce  the  costs of locating,
developing, and producing  the resource.

      For each year within the analysis,  the
procedure   simulates  resource  production
through  a series of calculations that  identify
the following:

•     Economic   Resources  --  from   the
      marginal cost curve using the  supply
  .-,-.  price;

•     Cumulative  Production  -- through  the
      last period  and remaining reserves in
      the last  period;

•     Reserve additions; and

•     Production.

Reserve   additions  represent  a  specified
fraction  of  the economic  resources  minus
cumulative production and remaining reserves.
The rate of production equals reserves times
the production-to-reserves ratio.

      The estimates of recoverable resources,
existing  reserves,  and marginal  eost  curves
were developed from a  number of different
sources,  including ICF (1982),  EIA  (1986),
and World Energy Conference (1980).

Hydropower

      Hydropower provides a very attractive,
cost-competitive  source of  electricity.   In
many developed  countries, hydropower  has
been  extensively  developed,   and    few
opportunities for further development remain.
Conversely,  growth in hydropower provides a
major future  source  of  energy  in many
developing  countries.   The  energy  model
treats hydropower differently  from all other
sources of energy,  taking  these  factors  into
account  by using an  exogenously specified
path for the rate of increase in  hydropower
for each region.

      Two  sources  comprise  the basis  on
which   the  rate  of  increase  is  derived:
historical hydro  production from the  EIA
(1986) and technically feasible resources from
Goldemberg et al.  (1987).    (Estimates  of
hydro resources for each region are outlined
in Appendix B.) For each  region, regressions
were used to fit a  logistic equation relating
historical hydro  production and  technically
feasible resources:
    pt = r * s *  [e(c+v'0 /
In  the  equation,  c and v  represent  input
variables, which are specified for each region
and estimated  using  historical  hydroelectric
production  and  technically  feasible hydro
resources. These variables describe how much
of the hydro resources have been developed
and  how  fast  they  will  continue  to  be
developed.   The  variable  t  represents  the
number of years from 1985.  The variable r
represents   the technically feasible hydro
resources, and  the variable s represents  the
fraction of the technically feasible resources
that  will ultimately  be  developed.   The
variable pi represents the hydro  production
for year t.

Nuclear Energy

      The  future  of  nuclear energy is  very
uncertain due  to a  number  of  political,
technical,  and  economic  factors.     To
determine the extent to which nuclear energy
will be used in  the future, the model accounts N
for   two   of  these  factors:     the  cost
competitiveness  of   nuclear   energy  and
political constraints on  the proliferation of
nuclear energy. Political constraints include
restrictions   on   the  export   of   nuclear
technology    to   developing   countries,
moratoriums on  the construction  of  new
plants, and restrictions on the development of
breeder reactors.   Other constraints include
private  investors'  aversion  to  investing  in
high-risk,   high -cost   nuclear    projects.
Estimated  future  costs  of nuclear  energy
reflect   expectations  about   technological
improvements  (e.g., lower  construction costs,
the use of commercial breeder reactors, and
                                            A-13

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 Policy Options for Stabilizing Global Climate
                             FIGURE A-4
                           SUPPLY MODEL
PRICE
                 PRODUCED
RESERVES
   ECONOMIC
UNDERDEVELOPED
                             UNECONOMIC
                            COST CURVE
                        ECONOMIC RESOURCES
                               A-14

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                                                              Appendix A:  Model Descriptions
breakthroughs  in  fusion technology),  costs
associated  with  compliance  with  stricter
environmental  regulations,  and anticipated
increases in the cost of fuels.  Further details
of the nuclear cost  assumptions are outlined
in Appendix B.

      The  cost  factor  is  captured  through
exogenous  input of  nuclear electricity costs, a
set of factors that allows the costs  to decline
over time,  and an environmental cost factor
that   can   be  used  to  slowly increase  or
decrease  nuclear  generation  costs.    The
political and other factors can be captured in
the fuel share weights  used  to determine the
mix of energy types that generate  electricity
(see Modeling Electricity Generation below).

Solar  Energy

      Solar energy  is  potentially  a major
source of energy in the future.  The major
uncertainties affecting  future  growth are the
cost of  harnessing solar energy and concerns
over  electric system load management and
reliability.  Solar power is used for two types
of energy:   heating  (e.g., home heating and
water heating) and electricity generation. The
model treats  these  two  sources  separately.
Home and water heating are dealt with in the
demand component, while solar electricity is
handled in the supply component.

      Currently, the cost of cultivating solar
energy  is  much  greater  than  for  other
commercial electricity sources. Furthermore,
solar  power is available  only  for portions of
the day, and the source can  be unreliable due
to climatic factors.   As a result, dependence
on solar  energy  requires  either substantial
electricity storage facilities,  such as batteries
or    pumped   storage,   or   substantial
conventional backup systems.  The energy
model captures these factors by requiring that
electricity generation by solar  power compete
with fossil and nuclear electricity generation
on a cost-competitive basis.  Solar  electricity
costs  are allowed  to  decline over  time  to
capture technological improvements. Details
of the  costs assumed for  solar energy are
given  in Appendix B.

Commercial Biomass

      Commercial  biomass energy supplies
may also play a major role  in the future.
Biomass   energy    technologies    include
exploitation  of  fuelwood,  forest   residues,
agricultural residues, municipal solid wastes,
animal wastes, and energy plantations.  Solid
biomass can be converted to either gaseous or
liquid  fuels, but  generally with  a  loss of
energy and substantial  fixed costs.   Existing
conversion   projects   include    methanol
production  from  sugar cane  (Brazil)  and
methane   recovery   from  waste   (China).
Current  biomass energy use is not  entirely
sustainable and  is one factor contributing to
net deforestation, particularly in Africa.

      To represent biomass energy, the energy
model uses a supply curve of annual biomass
energy that would  be available at  different
prices. Biomass is treated as a solid fuel that,
like  coal,  may  be  converted  to  liquid or
gaseous fuels, assuming a fixed cost and  net
loss in energy.  Biomass competes with liquid
petroleum  products  or  natural gas  based on
the supply prices of these fuels and the cost
of producing and  converting  the  biomass.
Biomass competes with solid fuels  based on
production costs and on relative efficiencies
and costs of end use. Appendix B provides
further   detail   on  the   numerical   cost
assumptions for biomass.

Calculating Prices for Primary and Secondary
Energy

      As described earlier,  the model keeps
track  of  three  different  levels of prices:
supply  prices,  primary  energy prices,  and
secondary  energy prices.    For  fossil-fuel
energy, the model estimates supply  prices, or
the value that producers can expect  to receive
for the fuel at the wellhead or the mine.  The
model assigns primary  energy  prices to  the
fossil  fuels and  to nuclear,  solar, and hydro
energy sources.  Primary energy prices for the
fossil  fuels represent the value of the fuel in
the   demand   market   and   contain   the
adjustment  for  inter-regional  transportation
(e.g.,  price of crude oil landed at  the U.S.
Gulf  Coast).   Primary  energy prices  for
nuclear, solar, and hydro energy represent the
marginal costs of producing electricity.

      The  model estimates  secondary energy
prices for  four  fuels:  liquids, gases, solids,
and electricity.  Secondary energy prices  for
the first three fuels are  based on the primary
energy prices for fossil fuels plus refining and
                                            A-15

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Policy Options for Stabilizing Global Climate
distribution costs  and, for electricity, are set
to the  overall  average  costs  of generating
electricity   (including    transmission  and
distribution  costs).     The  refining  and
distribution  costs for  fossil  fuels  reflect
estimates of the average costs of processing
and distributing the secondary energy to end
users.  These costs can include fixed non-fuel
costs  and  fuel  costs   (e.g.,  gas  used for
compression).   The  approach used  in the
model involves estimating the non-fuel  costs
on  a dollar basis (to  be  included  in the
secondary price) and accounting for  the fuel
use in the energy demand routines.  Further
details can be found in Appendix B.

      The model  sets the secondary  price of
electricity independently for each  region to a
weighted  average cost  of generating  the
electricity.  This average captures the input
energy  costs, conversion efficiencies, capital
costs, and shares allocated to each fuel type.

Estimating Synfuel Conversion

      The conversion of coal to synthetic oil
or synthetic gas involves both substantial fuel
and   non-fuel  costs,  and   the  amount  of
synthetic fuel production will depend heavily
on  these costs,  as well as on  the   cost of
producing the  coal  and  the value  of the
synthetic   fuels.    For  example,   current
estimates of the non-fuel costs of producing
synthetic   fuels   average   $7/gigajoule  of
produced  gas   (1988   U.S.  dollars)   and
$8/gigajoule  of produced  oil  (1988  U.S.
dollars). Estimates of the energy efficiency of
the conversion process average around  67%.
Additional  details  of  the  costs   of  the
conversion process are outlined in Appendix
B.

      To estimate synfuel production, coal or
biomass production  is  allocated to  three
different uses based on  the relative  value of
coal for each use:  (1) direct secondary energy
consumption (including  consumption for the
generation of electricity), (2) conversion to a
liquid fuel, and (3) conversion to a gaseous
fuel.   The  value of coal for each  use (V;,
where the index i  =c, o, or g) is based on the
supply  prices of the three fuels  adjusted to
reflect  differences in end-use taxes   (for  all
equations, the  subscripts c, o, and g refer to
coal,  oil, and gas, respectively).
      The  cost   to  convert  the  coal  to
synthetic fuel, adjusted  for taxes, (Vc;, where
the index /= o or g) accounts for fuel costs,
taxes, conversion efficiency, and capital costs.
The weighting  factor   for  allocating  coal
production to the three uses is specified by:
              Cj / V;)a
                 (i = o or g),
where  a  is an  elasticity control  parameter
(which is negative)  and S-{  is the  fuel share
weight.     Finally,   the  allocation of  coal
production to each use is determined  by:
q =
j / (sc  + s0
                          + s)  * c
where C is the total coal produced, and C; is
the coal allocated to either coal consumption
for   end-use   and   electricity   generation,
synthetic  oil  production, or  synthetic gas
production.

      As  seen from  the above equation,  as
the value of the oil or gas increases, the share
of coal used  to  produce  synfuels increases.
For   example, if  the  cost  of  producing
synthetic oil and  gas equaled the value of the
oil and gas respectively, then equal shares  of
coal  production  would be  assigned  to the
three uses. The rate at which the fuel shares
change  depends  on  the elasticity  control
parameter where an elasticity  with larger
absolute values yields faster rates of change.

Modeling Electricity Generation

      The approach used to  model electricity
generation captures  the relative cost of using
different  fuels, the  impact  of the mix on
electricity  demand,   and  the   impact   of
changing   generation  technology  on  the
relative cost.  The approach can be separated
into  two  activities:    selecting   fuels  and
estimating generation costs, efficiencies, and
emissions.

      Fuel Shares.   The  fuel mix selection
involves a three-step process that reflects the
basic assumption  that  fuel  selection  for
electricity production will be based on  relative
cost and exogenous factors, such as the desire
to maintain a  diverse mix of technologies, and
that hydroelectric production will be specified
exogenously (underlying this is the assumption
that hydropower  may be cheaper  than the
                                             A-16

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                                                               Appendix A:  Model Descriptions
other sources but is constrained by resource,
political, and environmental factors).   The
first step  uses an  estimate  of the share of
electricity production that  will come  from
hydro  sources.    The  model  allocates the
remaining electricity production to  the  other
fuels based  on costs  of  producing electricity
from  the  different sources  and exogenously
specified  fuel-share  weights.    The model
calculates the costs as follows:
                   p. *
                   ri
          p. _ p.
          S    ri
          (for i = o, g, and c) and
                  C- = V.
                  *-i    vi
             (for i = n and s).

In these equations, the index, i, represents the
fuel type (o  = oil, g = gas, c = coal, n  =
nuclear, and  s  = solar).   The variable P{ is
the secondary price of the fossil fuels, and the
variable F-t represents a price discount  that
large electric generation users receive for fuels
over the average  price to all users.  £j is the
efficiency   factor,   which   represents  the
multiplicative  inverse  of  the  marginal
efficiency  of converting the  fossil fuel  to
electricity.  H^  represents  the  marginal non-
fuel costs of producing the electricity.   The
variable Vi represents the  costs of producing
electricity from  nuclear  and  solar sources.
The variable C; represents  the marginal  unit
cost   of  producing  electricity  from  the
appropriate fuel  type.

      After estimating the marginal costs  of
producing  the  electricity,  the   share   of
electricity  produced  from  each  source  is
estimated as  follows:
Si =
                  W—
                  ~
           (W0 + Wg + Wc + Wn +  Ws)
In these  equations,  the variable Jfj  is  the
exogenously specified fuel-share weight.  The
variable a is the logit substitution parameter.
W{   is  the   calculated  fuel-share  weight
reflecting relative cost differentials, and  the
variable   S;   is   the   share  of  electricity
production, excluding hydroelectricity,  that is
produced from energy type i.

      As  can be seen from these equations,
three factors  influence the  estimates  of  the
fuel   shares:      the   costs  of  electricity
production, the exogenous fuel-share weights,
and  the logit substitution parameter.   For
fossil fuels, the costs of electricity production
will  change over  time as the prices of the
fuels   change    and   as   technological
improvements or emission controls change the
marginal efficiencies and  non-fuel costs.  For
the other fuels, solar and  nuclear, the costs of
producing   electricity   over  time  will  be
specified exogenously.  The exogenous fuel-
share weights provide a  way of reproducing
the  1985   fuel  selection  and  a  way  of
restricting  the use of  certain energy sources
(e.g.,  nuclear  energy  in   less-developed
countries).  In general, the exogenous fuel-
share weights are  initialized to represent the
current fuel selection but  are modeled so that
fuel  selection is solely based on  economics
after 40 years.    The  substitution elasticity
captures the variations that will occur in fuel
selection   due  to  a  number  of  factors,
including  system   reliability  and  location-
specific    environmental    regulations   or
economic factors.

      Fuel Use and Emissions. In the second
step  of the generation/fuel selection process,
the  model estimates the price of electricity
using the fuel shares, fuel costs, and non-fuel
costs as described above  and accesses the
demand routines to estimate  the demand for
electricity.  The third step involves readjusting
the fuel shares to  reflect  the fixed  amount of
hydroelectricity production and the estimated
demand.    In  the  third  step,  the  model
estimates the average  efficiency and non-fuel
costs for producing the  electricity for each
fuel.

      The   model  uses   a   capital   stock
approach to estimating trace gas emissions
along with marginal and  average efficiencies
and  non-fuel costs of electricity production.
Figure  A-5 illustrates how the capital  stock
approach works  over time.   For each fuel
type, the model starts out with an existing mix
of technologies  that are  used to convert the
fuel  to electricity.  Over  time the  initial mix
of   technologies   is   retired   and    new
technologies are added to replace the retired
stock and to satisfy increases in demand. For
the initial  stock, the model retires the stock
in equal shares over its useful life.  All capital
stock added after the  first period is retired
immediately after its  useful  life  has  been
exceeded.
                                             A-17

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    Policy Options for Stabilizing Global Climate
                                 FIGURE A-5
                          Capital Stock Approach
e
IB
3
"O
tu
0>
o
111
   1985   1990  1995   2000  2005  2010   2015  2020   2025  2030
       Existing      New 1985-1990    New 1990-1995    N»w 1995-2000
                                    A-18

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                                                            Appendix A:  Model Descriptions
      For   example,  in   1985   gas-fired
generating   technologies   consisted  of  gas
turbines, gas boilers, and gas combined-cycle
units. Each unit is described according to its
useful   life,  non-fuel  costs,   generation
efficiency,  and  trace  gas  emissions   per
gigajoule of energy consumed by the unit. If
the useful life of these units is assumed to be
40  years,  then 1/40 of the  initial stock is
retired in each year through 2025.  If we
assume  that one  exajoule  of  electricity is
produced from gas units in 1985 and that in
1990 this increases to 1.05, then the existing
stock would  be  able  to  produce  0.875
exajoules  of electricity and the  remaining
0.175 would be produced with new stock.
The model would allow the 0.175 exajoules to
be  produced  through  a   combination  of
technologies  that  might  be comprised  of
simple gas turbines used for peaking and gas
combined cycles.   In addition, in  1990 the
model could allow the user to  estimate the
effect of applying  control technologies  to a
specified percentage  of the  existing units as
well as  to  all  new  units.    The  control
technologies   will   affect   the  costs   and
efficiencies,  as well as the  emissions  that
result from the combustion.

      In the  above  example, the  marginal
costs and efficiencies used to determine the
share of electricity produced by the different
fuels  would  be   based   solely   on   the
combination of technologies and controls on
the new units and  not  the existing stock.
Both the new and the existing  technologies,
however, would be considered for calculating
total fuel use and emissions of trace gases.

      The exogenous fuel-share weights  and
the existing  combination  of technologies are
based on  data from  a number  of different
sources. The report on combustion emissions
prepared  by Radian Corporation  (Radian,
1990) provided the  basis  for the different
technologies available, the  efficiencies,  the
non-fuel costs, and the trace gas  emissions.
The combination  of technologies  currently
used in  the U.S. is based on data  from the
U.S. Department of Energy (EIA, 1983; EEA,
1983).  For the rest of the world, we used the
same mix of technologies for each fuel type
but  adjusted   the  efficiencies  based  on
efficiency estimates from various sources. The
fuel-share weights  are  based  on  energy
consumption data from the United Nations
(1987), EIA (1986), and the detailed end-use
analyses for developing countries provided by
the Lawrence Berkeley Laboratory (Sathaye et
al., 1988).  The combination of technologies
that will be used in  the future is  based  on
current  trends in the U.S.  and on scenario
assumptions.

Estimating Energy Demand

      One of the key parameters affecting the
level of future emissions is the demand  for
energy and how that demand will change over
time.  Strictly speaking, consumers do  not
demand energy per se, but the type of services
that energy can  provide.   Throughout  the
world,  energy  is  used for  many  different
purposes,  such as heating,  cooling, cooking,
transportation, and lighting. Energy is  also a
key component in many industrial processes;
for example, energy  is used  for  producing
steam,  providing  heat, and  as  a catalyst  for
chemical reactions such  as those occurring
with the use of coke in steel production. The
pattern of future energy use that results from
consumer   demands  for  these services will
depend on many factors, including the rate of
growth in population, changes in income as
determined by the rate of economic growth,
technological changes in  end-use  equipment,
the introduction of technologies that alter the
amount and type of energy demanded, and the
regional pattern of demand for products that
require energy for their production.

      The  energy model  uses  a combination
of two different approaches to estimate the
future  demand  for   energy:   a  top-down
approach  and a bottom-up approach.   The
bottom-up approach  (the  end-use models)
looks in detail at how the income will  be
distributed, how these distributions will affect
consumption  of  products   and  use   of
transportation, and how industry will change
to meet the change in demand. The bottom-
up  approach  is  used  to   estimate energy
demand  through  2025.    The  top-down
approach  relates  the  growth in demand  for
energy services  to  growth  in population,
income, and energy   prices  through income
and price elasticities and is used to extend the
estimates   of  energy  demand  from  2025
through the end of the model's time horizon.
                                           A-19

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Policy Options for Stabilizing Global Climate
Bottom-Up  Approach:
Through 2025
Energy  Demand
      End-Use Model: Industrialized Countries.
The industrialized  countries end-use  model
estimates  the demand for end-use energy  in
the industrialized countries  through 2025; it
was  developed  by  the  World  Resources
Institute  (Mintzer,   1988)  and  modified by
Lawrence Berkeley Laboratory/ICF specifically
for use in the ASF.  The model  utilizes an
end  use-oriented,  bottom-up  approach  to
estimating energy demand in the industrialized
countries  for each  of  two  energy  forms,
electricity  and fuels.   Fuels  represent all
commercial   energy   sources,   excluding
electricity, and include all petroleum products,
natural gases, natural gas  liquids, and coal.
Non-commercial  biomass  fuels   are  not
considered.  Population changes, increases  in
GNP, and saturation effects drive  changes  in
major energy-using activities. Parameters that
represent  energy intensity per unit o;f output,
or service delivered to the activity level, are
applied as the basis for deriving estimates  of
energy use.

      The model disaggregates energy end use
into three sectors:

•     Residential/Commercial;
•     Industrial/Agricultural; and
•     Transportation.

The model further disaggregates the industrial
and transportation  sectors  into  subsectors
representing different  types  of industrial
output  and modes  of transportation.  Table
A-l summarizes this disaggregation.

      Data on  historical  energy use  and.
activity patterns are used to estimate  future
activity levels, energy intensity, and energy use
by country.  Regional estimates of energy use
by sector, which  equal the sum of  country-
specific estimates,  are  calculated for every
five-year period from 1985 to 2025. Estimates
of  future activity  and intensity  levels are
functions  of the  assumed rate of growth  in
population, real GNP growth, rates of changes
in  energy prices,  rates  of improvement  in
engineering efficiency  of energy  use,  and
estimates  of the elasticity of energy demand
to changes in income and price.
      Estimates of future  energy use in the
combined residential and commercial sector are
tied   to   changes   in   the   total   space
requirements for domestic households and the
efficiency of energy use  relative to domestic
energy use in 1985.  Future residential floor
area reflects  the  estimated population  per
household, area required per capita, and total
population.   Demographic  trends for  each
country  provide   the basis  for  estimating
population per household and floor area per
capita  in 2025.  Users  specify the level of
improvements in energy efficiency per unit of
floor area,  which reflect scenario and policy
assumptions.   Values for  floor  space  and
efficiency improvements in the years between
1985 and 2025 are  interpolated  using logistic
growth curves.

      The model uses the following equations
to estimate  energy  use in the  combined
residential/commercial sector separately for
fuels and electricity.   First, total residential
floor   area,  Fat,   is  estimated  based  on
population,  persons  per  household,   and
average floor area per household as follows:

           Fat = (Fht/Hot)*Popt.

In this equation,  the variable Fht represents
the average floor  area per  household.  The
variable Hol represents the average number of
persons per household, and the  variable Popt
represents  the population in the region.  All
three  variables (Fhv Hov  and  Popt)  are
exogenously specified.

      Total energy use, £t,  in the residential
and commercial sectors is then  calculated as
follows:

         Et =  [Em1985*(l-efft)]*Fat

The index  t represents the energy form  (fuel
or  electricity).     The  variable   Em1985
represents  the energy use  in the  combined
sector in 1985 per square meter  of residential
floor space.  The variable efft represents the
cumulative gains  in  average efficiency from
1980 to year t. Efficiency improvement, effv
in  the  combined   sector  is   exogenously
specified and reflects a number  of factors,
including the vintage of the building stock,
assumptions    on   older   units  that  are
                                            A-20

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                                                            Appendix A:  Model Descriptions
                                        TABLE A-l

               Sector and Subsector Disaggregation for Industrialized Countries
Sector
      Subsector Breakout
Residential/Commercial

Industrial
Transportation
None

Basic Materials
  Iron and Steel
  Non-ferrous metals
  Chemicals and Feedstocks
  Paper and Pulp
  Stone, clay, and glass
Other

Automobiles and light trucks
Trucks and buses
Air travel
Rail travel
                                           A-21

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Policy Options for Stabilizing Global Climate
remodeled,  and the energy intensity of new
and replacement stock.

      Energy demand in  the industrial sector
is  modeled as the sum of energy used in the
production of basic materials and energy used
in fabrication, finishing, agriculture, and other
non-manufacturing  activities.    The  model
estimates  the   energy  used   during   the
production of five separate categories of basic
materials: iron and steel; non-ferrous metals;
chemicals and feedstocks;  paper and pulp; and
stone,  clay,  and  glass.  Production of these
commodities  represents  70% of  industrial
energy  use   in  the  U.S.  in  1980  and  the
majority of  industrial energy use for most of
the industrialized countries  included in the
demand model.

      For each basic material, the demand for
future energy use is estimated as a function of
the  per  capita  production,   the  fuel and
electricity intensity per ton of manufactured
product, population, and  price elasticities of
demand.  Historical production data provide
the starting  point for the analysis and future
output is indexed to the  level of production
in 1985.  For countries for  which historical
data is unavailable, data applying to countries
that are similar in terms of level of economic
development, population, etc., are  used as a
basis for deriving the production estimates.
Future  energy  intensities  and  per  capita
production    are   specified    for   2025.
Interpolation using a  logistic curve provides
values for the intervening years between 1985
and  2025.   Assumed decreases in  energy
intensity reflect scenario assumptions and are
based  on  analyses  of  currently   available
technologies.   Assumptions  of per capita
production  in 2025 reflect historical trends
and saturation effects.

      Estimates   of   the  energy   use   in
industrial activities other  than production of
basic materials are set as a fraction of the
estimated energy  used in the  production of
basic materials.   This  fraction is assumed to
increase  over time reflecting the shift from
commodity  manufacturing  to services and
other industrial activities.  The  fraction for
1985 for each country  is  based on historical
data, if such data are  available, or on data
from  countries  with  similar  economies,  if
historical data  for  that country  are  not
available.
      As  shown in  Table A-l,  the model
disaggregates    energy    demand   in   the
transportation  sector into  four  categories:
automobiles  and  light  trucks,  trucks  and
buses, air  travel, and rail  travel.   Vehicles
falling under  the  first  three categories  use
liquid fuels exclusively, while rail vehicles are
modeled as using both fuel and electricity.

      The  procedure for  estimating  energy
use for automobiles and light trucks factors in
variables such as energy use per mile traveled,
average number of miles traveled per vehicle,
and  number  of vehicles  per capita.   The
model estimates energy use for each country
separately.  First, the model estimates average
vehicle miles traveled per vehicle, Vmv based
on  miles traveled  in 1980, and then adjusts
this figure  to reflect the impact of prices and
income as  follows:

      Vmt =  Vm1980 * (l+Pgt*Pe)(<-198°)
In this equation, the variables are defined as
follows:

      Vmt --     average number  of  miles
                  traveled per vehicle;

      Pgt  -     growth in fuel prices;

      Pe   -     price elasticity of demand
                  for transportation services;

      Igt   -     growth in income; and

      le   --     income   elasticity    of
                  demand.
                                         .  \
Given the vehicle miles traveled, the following
equation   is   used   to   estimate    the
transportation demand for energy:

        Ft = Eit * Vmt * Vct * Popt

The variables in this equation are defined as
follows:

      Ft   --     fuel   used   in   the
                  automobile and light truck
                  category;
      Ei,
energy use per vehicle mile;
                                             A-22

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                                                             Appendix A:  Model Descriptions
      Vc,
number  of vehicles  per
capita; and
      Pop,  --     population  in  year I  for
                 the country.

      Energy intensity  for  1985 is derived
from historical  data  collected by the Motor
Vehicle Manufacturers  Association and  the
United Nations. The user specifies the energy
intensity in  2025, consistent with the intent of
the scenario,  and values in the intermediate
years are interpolated using a logistics curve.
Users also  specify changes  in the number of
vehicles per capita.

      The  procedure used  in the model to
estimate energy demand for trucks and buses
is similar to the approach taken to derive  this
estimate  for  automobiles   and  light  trucks.
The only difference is that the price elasticity
of demand  is  assumed to be zero.

      The  approaches to  estimating  energy
use by the  rail  and  air  transport sectors  are
similar and  reflect estimates of future demand
for travel  and  transport  and  the  energy
intensity  of  providing the  transportation
service.   For passenger travel,  the  model
estimates the  total distance of travel  required,
converts the distance to ton-km,  and uses an
energy intensity (energy per  ton-km)  to obtain
energy use.  For freight, the model estimates
future activity (ton-km) directly.   The model
translates  passenger  kilometers  to  ton-km
using conversion factors (of 0.11 and 0.08 ton-
km  per passenger-kin  for   rail  and  air
transport, respectively) which  account  for the
estimated weight of the vehicles.

      Future  demand  for  passenger  travel,
kilometers,  is a function of demand in 1985,
growth  in  real income,   and  the  income
elasticity of  demand.   Freight  traffic is  a
function of freight traffic in 1985, growth in
real income, the income elasticity of demand,
growth in real prices, and the price elasticity
of demand.  Users specify the energy intensity
of the transportation service exogenously to
be consistent with the intent of the  scenario.
Electricity use and fuel use for rail transport
are calculated separately.

      End-Use Model:  Developing Countries,
The model of energy demand in developing
countries through 2025 was developed by the
International Studies Group, Energy Analysis
Program of the Lawrence Berkeley Laboratory
(Sathaye et  al.,  1988).   This  model uses an
end  use, bottom-up  approach  to  estimate
demand  that  emphasizes the  fuel  uses and
circumstances facing the developing countries.

      The developing  countries  represent a
diverse   group   of   countries   that   has
experienced  steady  and  rapid  growth  (4.7%
annually) in the use of modern energy  (coal,
oil,   natural   gas,   nuclear,   hydro,   and
geothermal   sources)   since   1973.     The
countries included in this category range from
some of the poorest  countries in the  world
such as  Bangladesh and Ethiopia to some of
the richest countries such as Saudi Arabia and
Kuwait.  They include exporters and importers
of energy.

      Within  each country, urbanization and
industrialization  has  characterized  modern
economic development and  has  led to this
growth in energy demand.  Factors  that have
influenced urbanization include the wealth of
the country, whether  it imports or exports
energy, and  whether the country  is  centrally-
planned or market-oriented. For example, the
share of the  population in Saudi Arabia  living
in urban centers increased from 39% in 1965
to  72%  in   1985.    In the  Ivory Coast,
population in urban centers grew almost twice
as fast as the overall growth rate.

      Urbanization facilitates the adoption of
modern  lifestyles.    Adoption  of  modern
lifestyles facilitates increased  ownership of
appliances and vehicles which, in  turn, results
in increases  in the consumption of electricity
and other modern fuels.  This shift to modern
fuels  is  accompanied  by   a  shift   from
traditional biomass fuels,.which  is  sustained
even during  times of economic adversity.

      Biomass and other renewables represent
a  large  share   of energy  use  in   many
developioe countries (41% in  India and 68%
in Bangladesh).  Fuelwood is a major form of
biomass energy, and current rates  of fuelwood
use exceed  the  annual biomass increment
leading   to  deforestation  and positive net
fluxes of CO2 to the atmosphere.  Energy use
derived   from  biomass   is,   in  addition,
extremely inefficient  compared with   that
achieved through the use of modern fuels.
                                           A-23

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Policy Options for Stabilizing Global Climate
      The  modeling approach used  for the
developing  countries  disaggregates  energy
demand into five regions, three fuel types, and
six  sectors.  The five regions are consistent
with the regional disaggregation  used in the
ASF and consist of Latin America, Africa,
Middle  East,  Centrally-Planned Asia,  and
South and East Asia. The three energy forms
are electricity, biomass  and renewables, and
modern fuels.   The six sectors  are further
broken  down into subsectors that  represent
different types  of  activities  that  occur at
different stages  of  economic  development.
Table  A-2  illustrates  the  sector/subsector
disaggregation along with examples of the
types of activities included in the sector and
the forms of energy used.

      The model estimates the shifts between
the different subsectors as modern  economic
development is pursued.  For example, in the
agricultural sector,  economic development
results in the shift from traditional agriculture
methods of production, which use human and
animal motive power, to modern techniques,
which involves mechanized power and makes
use of  fast-growing varieties of crops  that
require regular and large amounts of fertilizer
and water.

      The transition between the subsectors
from  traditional  activities to more  modern
ones can be very rapid as can the increase in
the use of modern energy  (e.g.,  in South
Korea  the  transition  spanned a period of
three  decades).    The  pattern  of  growth
reflects a  wide range  of factors.   As an
example, the emergence  and  rapid growth of
modern transportation characterizes the early
stages   of  economic   growth.     Use  of
transportation  services  by  the  lower  and
middle  income brackets depends heavily on
decisions    concerning    road   and   rail
infrastructure,   settlement   patterns,   and
location of industry.  Also, energy intensity,
which  increases during the initial  stages of
economic development, may  later decline as
more energy-efficient processes and machinery
replace less efficient processes and outdated
energy-intensive machinery.

      The models  vary  among  regions but
contain  a  number  of  common  elements.
GDP, in real  terms, acts as  an  indicator of
economic activity.  The composition of GDP
changes   as  manufacturing  and  service
industries assume a greater role, thus reducing
the role of agriculture.   While  mining and
energy  processing  currently  account for a
large   share   of  energy  use  in   industry,
manufacturing will assume a  larger share in
the future.  Demand in 1985, by region and
sector,  is estimated either  by extrapolating
data from groups of countries that represent
a large share  of the region or by  allocating
energy supply  data obtained from the United
Nations  and  similar  sources according  to
energy use patterns of a few countries in the
region (Africa, Middle East).

      The models estimate future energy use
by  estimating ftiture activity  levels such  as
vehicle use and output of raw materials and
by  applying factors  representing the energy
intensity of these activities.   Activity levels
reflect population growth, income, and  the
distribution of income to the population.  The
future energy intensity of these activities and
changes  in energy intensity reflect historical
data   as   well   as   exogenously   specified
assumptions.

      Within  each   region,  population  is
separated into quintiles  based on historical
income  per  capita.   The   distribution  of
population in the quintiles is kept constant
over time, and the average income per capita
for each quintile is shown to grow consistent
with assumptions on real  GDP growth.

      The models estimate activity levels in
2025  by mapping the income per capita  in
each  of the  quintiles to  activity levels  per
capita and by multiplying  those results by the
estimated population in each of the quintiles.
The mapping from income  to  activities is
based  on current patterns of energy use  in
different  countries  at  different  levels  of
income.  This mapping is adjusted for 2025 to
reflect  the impact of the costs of energy-
intensive goods (automobiles, appliances, etc.)
and the decline  of these costs in real terms.

      The composition of energy end use is
consistent between  regions.    Residential
energy use is  divided into various end uses,
including  cooking,   water   heating,  space
heating,  lighting,   and   appliance   use.
Transportation  is divided into two modes,
land and air,  and land transport  is further
divided by vehicle type. The model estimates
the level  of  activity  and/or   ownership  and
                                            A-24

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                                                             Appendix A:  Model Descriptions
                                         TABLE A-2

                   Sector/SubSector Disaggregation in Developing Countries
Seetor/Subsector
Energy-Using Activities
Main Form of Energy
Agriculture
  Traditional
  Mechanized

Fisheries
  Non-motorized
  Motorized

Industry

  Handicraft
  Light
  Heavy
  Energy Intensive
  Feedstocks

Transportation
  Personal
  Informal Public
  Formal Public
  Light Truck
  Heavy Truck
'  Rail
  Air

Residential
  Rural

  Urban
Commercial
  Buildings
Ploughing and irrigation
Powering of pumps and tractors

Powering of:
Nets, canoes
Fleets

Production of:

Weaving Baskets
Shoes, textiles
Metal processing
.Cement, Aluminum
Fertilizers, chemicals

Powering of:
Cars, motorcycles
Jitneys
Buses, rail, transit
Cooking, lighting

Cooking, lighting

Appliances Operation
Lighting/space heating and
cooling, etc., in offices,
hotels, restaurants
Animals
Electricity, Diesel
Diesel

Electricity, fuel oil,
natural gas, coal
Gasoline
Diesel (mostly)
Diesel (mostly)
Gasoline, diesel
Diesel (mostly)
Coal, diesel, electric
Jet fuel (mostly)
Biomass, kerosene,
electricity
LPG, kerosene,
electricity, biomass
Electricity, natural gas
Electricity (mostly)
Source: Sathaye et al, 1988.
                                            A-25

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Policy Options for Stabilizing Global Climate
multiplies  by the  energy intensity of  the
activities to obtain energy end use.

      Industrial  energy use  is divided into
electricity  and  non-electricity components.
The current  ratio of  each  component is
calculated  for 1985 and  estimated for 2025.
Energy  use is estimated  by applying  these
ratios to  the estimated  level of industrial
value-added.     For   appropriate   regions,
consumption of fossil  fuels in the refining,
chemical feedstocks, and fertilizer industries,
as  well   as  in   other   energy-processing
industries is accounted for separately.

      Current fuel  and electricity intensities
in the commercial sector are  based  on data
from  those countries  where  the data  are
reported  separately  from  the  residential
energy use.  Estimates of future energy  use in
these sectors are based on similar ratios  and
estimates  of  future value  added  in  these
sectors.    The approach  taken  to  estimate
energy end use for the agricultural sector is
similar to  the approach for the  commercial
and services sector but  is based on  rough
estimates  of the fuel and electricity use in
those sectors.

      The model  relies  on  a  number  of
assumptions concerning the impact of energy
prices, the development of the energy market,
and the  rate  and role  of  technological
innovation.  Although  resource  constraints
may drive prices up, the model assumes that
these constraints will not be a bottleneck to
economic  growth.    Energy  markets  will
develop  in  an  orderly  manner.   Higher
economic growth combined with higher energy
prices will result in technological innovation
and improvements in the efficiency of energy
use, which will offset a large part  of the costs
of  the  more  expensive  energy.  Unproven
technologies are not included in  the view of
the world in 2025.

Top-down Approach: Energy Demand Beyond
2025

      The top-down approach to estimating
future energy demand, for both industrialized
and developing countries, ties  future demand
for energy to changes in population, income,
and energy prices  through  a set of simple
relationships that  utilize income and price
elasticities.  The model selects from different
fuels to satisfy demand based on the relative
costs of meeting the demand and keeps track
of the stock of technologies used to  satisfy
demand in order to change efficiencies, costs,
and emissions.

      The basis for the  modeling of  energy
demand  is the demand  for end-use energy.
End-use  energy  may  be  defined  in  many
different ways  for  different applications of
energy and even for  the  same  application.
For example, the end-use service provided by
a conventional fireplace, a furnace, and a heat
pump  is temperature  control in the  house,
but the fuels used, the cost, and the  energy
efficiencies  can ' vary  considerably.   In  a
conventional fireplace, most of the   energy
from the combustion of wood escapes through
the chimney.  With conventional oil and gas
furnaces,  over  30%  of  the energy  is  lost
through the flue.  With  a  pulse  gas furnace,
however,  the amount  of energy lost  is  less
than 5%.   A heat  pump can,  on average,
provide the same type of end-use energy as a
pulse gas furnace but with up  to 75% less
secondary energy (coefficient of performance,
COP, of  1.7, although more primary energy is
required to produce the  electricity).

      The model disaggregates  the f  energy
demand for each region into three end-use
sectors:      residential/commercial,
transportation,  and  industrial,  where  the
relationship between population, income, and
prices vary between sectors. The first  step is
to estimate the demand for  end-use energy for
each region and each sector as  follows:

Residential/Commercial and Transportation
                                         \
       EEt = EEl * Cgta * Igtb * Pgt;

Industrial

       EEt = EEl * Cgta * Ggtb.

The   variables  in  the  above  equations
represent the following:
EE
                  demand for end-use energy
                  in year t;

                  demand for end-use energy
                  in the starting period;
                                           A-26

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                                                            Appendix A: Model Descriptions
      Cgt  --     growth  in  the  cost  of
                 providing    the  end-use
                 energy;

      a    --     price elasticity;

      Igt  --     growth   in   per   capita
                 income;

      b    --     income  elasticity;

      Pgt  --     growth in population; and

      Ggt  —     growth in regional GNP.

The growth in the cost of providing the end-
use energy will reflect the secondary prices of
energy, the non-fuel costs of providing the
secondary energy, the efficiency of providing
the secondary energy, and the fuel shares.

      The approach used to  calculate fuel
shares and the efficiency with which the end-
use energy  is  provided  is the same as that
used for calculating fuel shares and efficiency
for the generation sector.  Using the capital
stock approach,  the model  determines  the „
marginal  efficiency   and non-fuel  costs  of
converting each type of secondary energy to
end-use  energy.   Note  that  the marginal
efficiency refers to the average efficiency of
the  combination  of technologies  used  to
satisfy new  demand  or replace retired stock.
Combining  the secondary prices of energy
with  the marginal  efficiencies and  non-fuel
costs, the  model  estimates  the  cost  of
providing the end-use energy with each type
of fuel.  Using these  costs, end-use fuel-share
weights, and elasticity control parameters, the
model  can  estimate the  share   of end-use
energy satisfied by each fuel (see Electricity
Generation above).

      Given these shares and the demand for
end-use energy, the model then uses a capital
stock approach  to  estimate  the average
efficiency of providing the end-use energy, the
consumption of secondary fuels, and emissions
resulting from the  consumption.   As  with
electricity generation, the user can introduce
new technologies and efficiency improvements
over time as well as  apply emission controls.
Interface to the End-Use Models

      The end-use models are run separately
and  require  input  of  a  wide  range  of
assumptions concerning the stock  of energy-
using  equipment  (e.g.,  vehicles,  building,
appliances,  electric  utility powerplants), as
well as population, income, energy prices, and
efficiency.   The  models  produce  a set of
outputs  that  include  the   demand  for
secondary  energy and  income  and   price
elasticities. The demand for secondary energy
is broken down into three categories:   fuels,
electricity, and biomass; and the demand for
fuels is not further divided by fuel type (e.g.,
demand for fuels represents the total demand
for oil, natural gas,  and  coal).  The income
and price elasticities allow the global model
to deviate from the  input price assumptions
for the end-use models in order to balance
supply and demand.

      In order to interface with the end-use
models,  the   energy  demand   estimates,
elasticities,  efficiency  assumptions,   price
assumptions, and income assumptions made in
the end-use models must be put into a format
suitable for use in the global model.  The
efficiency assumptions  must  be  replicated
within  the framework of the global  model,
and conversion factors must be specified that
allow the demand estimates to be converted
into  estimates of  end-use energy for each of
the three sectors.  For each  period  through
2025, the global model  uses the estimate of
energy demand from the end-use model and
converts the demand to end-use energy  using
the efficiency  assumptions and the specified
conversion factor. It then adjusts the end-use
to reflect  changes  in  income and  energy
prices.    The  model allocates the  end-uses
energy to secondary fuels and converts the
end-use energy back  to energy demand -using
the  same procedures  as in  the  top-down
approach, with the  exception  that the fuel
share for electricity is specified by the end-use
model.   If  the efficiency  assumptions, the
income assumptions, and the energy  price
solutions replicate the input  assumption of
the end-use model, then the global model will
reproduce  the  results  from  the  end-use
models.
                                           A-27

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Policy Options for Stabilizing Global Climate
      After 2025 the model estimates energy
demand using the top-down approach, basing
all estimates on the end-use energy estimate
in 2025 and changes in prices, population, and
income from 2025.

Implementation of Capital Stock

      The  model calculates changes in end-
use fuel and non-fuel  costs  and emissions
resulting from end-use energy using the same
capital  stock  approach   as is  used  for
estimating costs for electricity generation. As
with the generation side, the model  keeps
track   of  different  vintages  of  capital,
application   of  emission   controls,   and
efficiency   improvements.     The   model
maintains different sets of  capital stock for
each  of  the  end-use  sectors  and  allows
different assumptions  concerning  emission
controls and efficiency improvements for each
sector and for different  technologies within
each sector.

      As  with  the generation  sector,  the
assumptions   about the   existing  mix  of
technologies    are   based   primarily   on
information on energy  consumption  in the
U.S. and  in other OECD  countries.   The
approach  differs  depending on  the  end-use
sector  and  fuel  type.     The  sectors  are
residential,   commercial,   industrial,   and
transportation.  The fuel types are liquids,
gases,  solids,  and  electricity.   The basic
approach   for  developing   the  mix   of
technologies and fuel types for the year 1985
is discussed below.

      Primary energy consumption estimates
were taken from United Nations (1987), and
secondary energy consumption estimates were
developed from OECD (1988) for the OECD
countries and from Sathaye et al. (1988) for
the   developing   countries.      For   the
USSR/Eastern Europe, information from the
OECD  countries   was  used to  apportion
secondary demand, since detailed information
on the centrally-planned  European countries
was not available.  This step categorized each
region's energy consumption by fuel type and
end-use  sector.   Within each  sector  the
following  steps were  taken to categorize
demand in greater detail.

      Residential energy use was classified by
type of application and fuel source using data
from  El A (1988).   This  source  contained
information for the U.S.  for  the  year  1984
(1985  data was  not yet  available).   The
categories by type of application were space
heating, air conditioning, water heating, and
appliances. The fuel sources were natural gas,
distillate  fuel  oil  and  kerosene, liquified
petroleum  gas  (LPG),  and electricity.   This
breakdown  was   also  applied   to   other
industrialized  countries  (on  a  percentage
basis) since comparably  detailed information
was  not available  for  these regions.   The
breakdown for  the  developing countries was
developed  from  information  provided  by
Sathaye et  al. (1988).

      Commercial energy demand by fuel type
was based  on OECD (1988)  and  Sathaye et
al.  (1988).    Type  of   application  was
determined  from   EIA   (1978),   which
categorized energy consumption  in   the
commercial sector by type of fuel and end-use
application for the United States. Major end-
use applications included space conditioning,
water   heating,   cooking,   lighting,   and
refrigeration.   This information  was  also
applied to  other regions  to classify their
commercial energy  consumption by  end-use
category.

      Transportation  energy  demand  was
categorized  using  OECD  (1988).   For  the
OECD   countries  this  source  provided
information on  energy  use  by  mode  of
transportation (e.g., rail, road, air, etc.) and by
type  of  energy  (i.e, coal, gas,   oil,  etc.).
Sathaye et al. (1988) was used for categorizing
demand in the developing countries.

      End-use classification in the industrial
sector was based on information for the U.S.s
in OECD (1988),  which  categorized  coal
demand   by  industry.      The   following
sources/assumptions were used  to  apportion
this  demand to  end-use  categories:    (1)
metallurgical coal demand for use in coke
ovens for steel-making, from EIA (1988); (2)
coal  demand for cement  kilns and  other
minor applications, also from EIA (1988); and
(3) the remaining demand was assumed to  be
consumed in boilers.

      U.S.  industrial consumption  of oil and
natural gas was not classified by industry in
the OECD (1988) data.   For these fuels
aggregate  demand was  disaggregated by end
                                            A-28

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                                                             Appendix A: Model Descriptions
use using information in  EIA (1978), which
indicated  the pattern of fuel  consumption
within the U.S.  industrial secior.   For each
fuel    type,   percentage   esiimates   were
determined for (1) the amouni of fuel used as
a  raw  material,  i.e., oil used  in  asphalt
production and  natural gas used in fertilizer
production; (2)  the  amount  of fuel used in
transportation, e.g., diesel or  gas used to fuel
vehicles in construction or mining;  (3) the
amount of fuel  consumed in boilers used to
produce steam;  and (4)  the  amount  of fuel
used in other applications, e.g., dryers, ovens,
etc.  The  quantity of oil or gas consumed in
boilers  and  in  other applications,  such  as
dryers, was allocated  to  industry based on
information in EIA (1983),  which  indicated
the proportion of fuel use consumed by each
industry.  This detailed classification  for the
U.S.  was  also   applied  to  the  aggregate
demand estimates for the other regions since
this information was unavailable.

Estimating Greenhouse And  Related
Emissions

      The production and  consumption  of
energy discussed previously generates a variety
of emissions that affect global climate.  In the
model these emission estimates are generated
once  energy  use is determined  from the
equilibration of  supply  and  demand.  The
greenhouse  gases for which estimates are
provided in the  energy model include carbon
dioxide (CO2),   nitrous  oxide  (N2O), and
methane  (CH4); the  model also  estimates
emissions for carbon monoxide (CO) and
nitrogen oxides  (NOX), which,  although not
greenhouse  gases,  indirectly affect  global
climate as a  result of their interactions with
other gases in the atmosphere. The emission
estimation procedure  is discussed  below in
greater detail.

      The type and quantity of emissions will
depend not only on the amount and type of
energy consumed, but also on the manner in
which the energy is consumed. In the model,
consumer   demand  for  end-use  energy
produces  emissions  from several  types  of
energy, including fossil  fuels  such  as oil,
natural gas,  and coal.  These emissions are
estimated  on a sectoral basis  by  primary
energy  application.   That  is, as  discussed
earlier in the energy demand section, energy
use  is first  categorized  by  type  of energy
within each of the major energy-consuming
sectors  that  are  included  in the model -
industrial/agricultural, residential/commercial,
transportation,  and  the  utility  sector  for
electricity generation.  Within each of these
sectors, energy is consumed  to provide some
type of service.  For example, electric utility
powerplants consume fossil  fuels to provide
electricity (which  is  then consumed  by  the
other sectors); automobiles, trucks, and buses
consume gasoline or diesel  fuel; industrial
boilers consume  residual oil or natural gas to
produce steam; furnaces consume natural gas
or  oil  to  provide heating  in  homes  and
buildings; etc. In the energy  model this level
of detail  reflects  the  different  methods by
which  energy may be consumed  and hence,
the different methods by which emissions can
be generated.

      This level of disaggregation is necessary
to capture the various inefficiencies that occur
in  the production  of  end-use  energy  for
different   applications   and  how   these
efficiencies may  change over time.   In  the
model  these  parameters  are  specified  by
representative cost, efficiency, and emissions
characteristics.  Table A-3 summarizes these
key  characteristics for  some of the major
fossil-fuel-burning technologies in each sector.

      In the energy  model  several types of
non-fossil energy can also be chosen to supply
end-use energy demands.  The quantities of
emissions from  these  other  energy sources
depend on  the  specific energy type.   For
example, nuclear energy is assumed to have
zero  emissions   for  the  five  trace  gases
indicated in Table A-3 (CO2, CO, CH^, N2O,
and NOX). Special consideration is given to
biomass energy   as  a  renewable  resource.
Consumed  biomass   does   emit  various
quantities of CO2; however, if consumed on a
sustainable basis, the carbon  from which  this
gas is formed has been^stored in the biomass
material during  the plant's growth.   To
capture the  net  recycling of carbon,  CO2
emissions from biomass are assumed to be
zero.

      For emissions  of other gases from the
combustion of fuelwood and other  biomass
energy  sources,   the  model uses  emission
estimates  for  1985 and ties  changes in  the
quantities of these emissions to  changes in
the  use  of  biomass  in   the  developing
                                            A-29

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 Policy Options for Stabilizing Global Climate
                                         TABLE A-3




                            Differences in Emission Rate By Sector




                                    (grams per gigajoule)
Efficiei
Source (%)
Electric Utility (g/GJ delivered electricity)
Gas Turbine Comb. Cycle
Residual Oil Boilers
Coal - PC Wall Fired

42.0
32.4
31.3
Industrial (g/GJ delivered steam for boilers; energy
Coal-Fired Boilers
Gas-Fired Boilers
Kilns - Coal

Residential/Commercial (g/GJ energy output)
Distillate Oil Furnaces
Gas Heaters
Transportation (g/GJ energy input)
Automobiles
Trucks
80
85
ncy
C02

120,300
230,000
330,000
output for kilns)
130,000
57,000
65-75 300,000-


75
70

350,000

111,000
101,000

Trace Gas
CO

70
43
42

110
18
75


17
13

54,900 10,400

73,300
600
CH4

13
2.2
2

2.9
1.5
1


7
1

36
8
N20

20
44
45

18
3.5
2


NA
NA

0.5
NA
NOX

400
590
1400

390
71
500


65
61

400
1,200
Source: Radian,  1990.



NA = Not Available.
                                           A-30

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                                                            Appendix A: Model Descriptions
countries, which have been derived from the
energy model.

INDUSTRIAL EMISSIONS MODULE

      The   Industrial   Emissions  Module
provides estimates of trace gas emissions from
three different  activities:  use of CFCs and
haltins, decay of organic  matter in landfills
(CH4), and cement production (CO2).   The
factors  that  affect  future  emissions  vary
considerably as do  the mechanisms to reduce
future emissions.

Estimating Emissions of CFCs and Halons

      The CFC emissions component of the
U.S. EPA Integrated Assessment Model (U.S.
EPA, 1988) provides estimates of emissions of
CFCs and  halons  under different  economic
scenarios, policy objectives,  and compliance
scenarios  through  the  year  2100.   Future
production of CFCs reflect assumptions about
future  demographic and  economic  trends,
regional  and global  control strategies  to
reduce the   production  and  use  of  these
chemicals,  and compliance  with regulatory
controls.   Estimates of emissions resulting
from the  production and use of CFCs account
for the different uses and rates of release
associated with those uses.

      The    CFC    emissions   component
disaggregates production  and emissions of
CFCs into ten compounds, eight applications,
or end uses, of CFCs, and ten global regions.
The regional disaggregation conforms closely
to that used throughout the ASF (Canada and
Western  Europe are further  disaggregated in
the CFC model) where production scenarios,
control  strategies,  and  compliance  with
controls can  be specified separately for each
region.  The  ten compounds are as follows:
      CFC-11;
      CFC-12;
      HCFC-22;
      CFC-113;
      CFC-114;
      CFC-115;
      Carbon Tetrachloride (CC14);
      Methyl chloroform (CH3CC13);
      Halon 1211; and
      Halon 1301.
Each  of these compounds is associated with
as many as six different end uses, where these
end uses and possible substitutions influence
the production of CFCs and the release rates.
There are a  total of eight end-use categories
included in the model:
      aerosol propellants;
      flexible foam;
      rigid polyurethane foam;
      rigid nonurethane foam;
      refrigeration;
      solvent;
      fire extinguishants; and
      miscellaneous.
The   model   estimates  production   and
emissions starting from 1931; the time frame
can be extended to 2165, although the ASF
utilizes emissions only through 2100.

      The  overall procedure for  estimating
emissions involves, first,  estimating  global
production of the different compounds, which
reflects   demographic   and   economic
assumptions  of   the   scenario.     Global
production  is  allocated  to  regions  and
applications using sharing rules.   Regional
shares vary both  historically  and  in  the
projections,   reflecting   shifts  in   global
production due to differing rates of economic
development and  other factors.

      Policy alternatives are then  applied to
the production scenarios to reduce or shift
the relative uses of the different compounds.
These policy alternatives can  reflect a number
of  issues,   including  constraints  on  the
production    of    different   compounds,
compliance  with  these  constraints,  shifts
between  compounds  as a   result  of  the
constraints, and the impact  of technological
development, which may encourage the use of
alternative compounds in regional  and global
production.

      Releases  of the different compounds to
the atmosphere are then estimated based on
the projections of production by  type of
compound and type of application. For some
uses of CFCs, such as for aerosol propellants,
the   compounds   are   released  into  the
atmosphere soon  after the production  of the
compound.   In   other   applications  the
                                           A-31

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Policy Options for Stabilizing Global Climate
compound is released slowly.  Releases from
refrigeration  depend  on  the integrity  and
useful  life  of the refrigeration system,  and
releases from rigid foams depend on the rate
at which  the rigid  foams  decay.   As an
example, production of CFC-11  for use  in
rigid polyurethane  foam  can contribute  to
releases of CFC-11 20 years later.

      The  model simulates  these  delayed
releases, or  banking,  of  compounds  by
applying release profiles to the production of
each compound  by end use.  These release
profiles match the production of the chemical
in a given year to emissions in future years.
The release  profiles  are based  on Quinn
(1986).

      Table A-4 illustrates the release profiles
for CFC-11.  The release profiles that allocate
the  CFCs   range from   almost  immediate
release, in the case of aerosol propellants, to
release  profiles that span 20 years.   In all
cases,  100%  of  the  compound produced is
eventually released to the  atmosphere.   A
limitation of the model is that  it does not
allow revision of the  release profiles  over
time to reflect technological development that
results in reduced emissions.

Estimating Emissions of CH4 from Landfills

      Approximately 80% of municipal solid
wastes  collected in urban areas  around the
world is deposited in landfills or open dumps
(Bingemer  and  Crutzen,  1987).    Sanitary
landfilling (compaction of wastes, followed by
daily capping with a layer of clean earth) is
used   primarily   in   urban  centers    in
industrialized countries.  A  large portion  of
these waste  disposal sites  develop anaerobic
conditions resulting in the decay of  organic
matter to CH4.

      Future disposal of solid wastes will be
driven  by a number of factors, including the
amount of available land suitable for sanitary
landfilling,  the switch  to incineration as a
means   of  disposing  of  wastes,  increased
urbanization   and   waste   generation   in
developing  countries, and policies such  as
waste  minimization  and  CH4 recovery  to
reduce wastes or  emissions.  Waste dumping
rates   in  the  industrial   world   are   now
beginning to level off.  However,  because  of
strong   population  growth   and   increasing
urbanization,  CH4  production  from  waste
dumps  in   the  developing  world  can  be
expected to grow in the future (Bingemer and
Crutzen, 1987).

      The approach  used  to  estimate future
emissions of CH4 from landfills is based on
estimates of the current level of emissions as
well  as  on  future  population  and  GNP
growth. Our approach is threefold. First, the
literature provided estimates of current global
emissions of CH4 from landfills, which can
range  from  30  to  70 Tg  CH4 per  year
(Bingemer  and Crutzen, 1987).   The global
emissions estimate   is   then  subdivided  by
region  based on  the  amount  of carbon
disposed of in each region  (Bingemer and
Crutzen, 1987). Estimates of future regional
emissions were developed for each   of the
nine  integration  model  regions separately,
assuming   a  close  relationship  between
emissions measured on  a per capita basis and
average GNP/capita (see Table A-5).

      For the U.S., emissions from landfills
are assumed to remain flat.   For the rest of
OECD, emissions are  expected to increase
slightly as  a result  of  increased  population
and   increased   GNP/capita.     For   the
developing  countries, emissions rise rapidly
because  of  rapid  increases  in population,
GNP, and urbanization.

Estimating  CO2 from the Production of
Cement

      The  CO2  emissions   resulting   from
cement  manufacture   occur  during   the
production  of clinker.  A  mixture of cement
rock,  limestone, clay, and shale are crushed
and   blended  to   a   mixture   that  is
approximately 80% limestone  by weight.  This
mixture is fed into a  kiln where it is exposed
to progressively  higher temperatures.   The
emissions of CO2 occur during the calcination
process when  the   limestone  (CaCO3)  is
converted   to   lime   (CaO)   and   CO2.
Approximately 0.14 ton of carbon is emitted
per ton of cement produced (Rotty, 1987).

      For  the  developed   regions  (U.S.,
OECD-West, OECD-East, and the USSR and
Centrally-Planned Europe), future emissions
of CO2 from cement production through 2025
are tied to  assumptions made in the end-use
models on growth in economic output  from
                                           A-32

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                                                              Appendix A:  Model Descriptions
                                         TABLE A-4

                                 Release Profiles for CFC-11

                                          (percent)
End Use
          Years after Initial Use
        2        345
                                  10    15    20
Aerosol Propellent
  annual release
  cumulative released

Flexible Foam
  annual release
  cumulative released

Rigid Polyurethane Foam
  annual release
  cumulative released

Rigid Nonurethane Foam
  annual release
  cumulative released

Refrigeration
  annual release
  cumulative released

Miscellaneous
  annual release
  cumulative released
100,0
100,0
100.0
100.0
 14.5
 14.5
 4.5
 19.0
 4.5
23.5
 4.5
 28.0
 4.5
32.5
 4.5
55.0
 4.5
77.5
  4.5
100.0
 60,0
 60.0
 19,0
 19.0
100
100
 40.0
100.0
 8.1
 27.1
 7.3
34.4
 65.6
100.0
Source: Quinn, 1986.
                                             A-33

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Policy Options for Stabilizing Global Climate
                                      TABLE A-5




                Assumptions Concerning Methane Emissions from Landfills
Region
U.S., Canada, Australia
Other OECD
USSR & E. Europe
Developing Countries
TOTAL
Waste C
Dumped
(106 t C/yr)a
37
19
13
16
85
Regional Emissions
Total
(Tg/yr)
13.0
6.7
4.6
5.7
30.0a
Per Capita
(K)6g/yr)
46.4
12.6
11.0
1.6

Average 1985 ,
GNP/Capitab
(103, S1988)
18
10
5
0.7

a Bingemer and Crutzen, 1987.



b World Bank, 1987.
                                         A-34

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                                                             Appendix A: Model Descriptions
the stone, clay, and glass sectors.  After 2025,
the  rate. of growth  is  reduced  to reflect
reductions in the rate of economic growth in
those regions. For the  developing countries,
cement   production   is  allowed  to  grow
consistently  with  growth  in  GNP  until  it
reaches  levels of production consistent with
production in the developed countries.

AGRICULTURAL EMISSIONS MODULE

Introduction

      The Agricultural  Module of the ASF
estimates  emissions of  trace gases resulting
directly  from  the  production  of  agricultural
products.      This   module   provides   a
comprehensive look at  changes in land area
under  cultivation,  regional  production  of
different crops,  meat and  dairy  production,
and fertilizer use, and then ties these activities
to emission  coefficients  to  produce estimates
of annual emissions.

      The agricultural  module  is  used  to
estimate emissions of four trace  gases that
result from  four agricultural  activities: rice
cultivation (CH4), nitrogenous fertilizer use
(N2O), animal husbandry (CH4), and burning
of agricultural wastes (N2O, CH4, CO, and
NOX).    The  module  ties CH4 emissions
resulting  from anaerobic  decomposition  in
flooded rice fields to the estimated land under
paddy  rice  cultivation.    Methane  released
through  enteric  fermentation in  domestic
animals follows  the production estimates of
meat and dairy  products and  population
estimates  of domestic animals  used for labor.
Nitrous   oxide   that   evolves   from   the
application of fertilizer follows projections of
nitrogenous  fertilizer  use.   Emissions of  all
four  of  the  gases   resulting   from  the
combustion   of  agricultural  wastes follow
estimates  of  the use  of cultivated land.
Carbon dioxide emissions resulting from the
combustion of agricultural wastes are assumed
to  net  to  zero  within each  year  due  to
recycling during plant growth.

      The agricultural module consists of two
components:  an agricultural activities model
and an emissions model.   The  agricultural
activities model  is a detailed regional model
of agricultural production,  land use,  fertilizer
use, and product consumption through 2050
(Frohberg et al., 1988;  Fischer et al., 1988)
with a simplified approach to extending the
projections  through 2100.   The emissions
model applies  emission coefficients  to  the
results from the activities model, allowing for
changes in these coefficients to represent the
impact of policies to reduce emissions.

Estimating Agricultural Activities through
2050:  The Basic Linked System

      Agricultural  activities   through 2050
were estimated by the Center for Agricultural
and  Rural  Development  (CARD) at Iowa
State University  through use  of the Basic
Linked System (BLS) (Frohberg et al., 1988).
The  BLS  is  a  tool  developed  and  used
primarily for analyzing policies to improve the
agricultural  production  and   distribution
system over a medium-term horizon (for the
1980s and  1990s).    The origins  of the BLS
lie  with the Food  and Agriculture Program
at the  International Institute  for Applied
Systems  Analysis,  Laxenburg,  Austria,  in
cooperation with the Center for World Food
Studies,   Amsterdam.      These   two
organizations,   with  the  participation   of
researchers from around the world, took the
lead in conceptualizing and constructing the
BLS,  which was then  transferred to  several
research   institutions    including   CARD.
CARD has subsequently extended the  time
horizon to 2050 for U.S. EPA's use in  the
ASF.

      The  BLS combines  34  national and
regional models (see Table A-6) within  an
integrating framework  that  uses prices and
flows of capital  to balance  global  supply,
demand, and trade.  Twenty national models,
which   represent   80%  of   the   world's
population  and  production,  are  used xto
estimate agricultural activities  for  specific
countries   (or  in  two cases,  groups  of
countries).   The  rest of   the world  is
represented in 14 simplified regional models.
Each  regional  model   represents a  set  of
countries  with similar  income  levels  and
import and export characteristics with  respect
to agricultural products and crude oil.

      The integration of the 34  national and
regional models  includes  an  equilibrating
mechanism  that addresses the major  factors
affecting the global market including prices
for  the   different  agricultural  products,
imports, exports, and level of stocks.  At the
                                            A-35

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Policy Options for Stabilizing Global Climate
                                       TABLE A-6

                              Regional Disaggregation of BLS
                  Japan

                  Mexico
                  Nigeria
                  Pakistan
                  Turkey
                  European Community
                                        Group 2            Group 3

                                        Kenya              CMEA (USSR & Centrally Planned
                                                             Europe)
                                        New Zealand        China
                                        Thailand            India
                                                           United States
National Models

         Group 1

 Argentina

 Australia
 Austria
 Brazil
 Canada
 Egypt
 Indonesia

Regional Models

Africa
  1   oil exporters (Algeria, Angola, Congo, Gabon)
  2   medium-income calorie  exporters (Ghana,  Ivory  Coast,  Senegal, Cameroon, Mauritius,
      Zimbabwe)
  3   medium-income calorie importers (Morocco, Tunisia, Liberia, Mauritania, Zambia)
  4   low-income calorie exporters (Benin, Gambia, Togo, Ethiopia, Malawi, Mozambique, Uganda,
      Sudan)
  5   low-income calorie importers  (Guinea,  Mali, Niger, Sierra Leone, Burkina Faso,  Central
      African Republic, Chad, Zaire, Burundi, Madagascar, Rwanda, Somalia, Tanzania)

Latin America
  1   high-income  calorie exporters  (Costa Rica, Panama, Cuba, Dominican Republic, Ecuador,
      Surinam, Uruguay)
  2   high-income  calorie importers  (Jamaica, Trinidad, Tobago, Chile, Peru, Venezuela)
  3   medium-/low-income (El Salvador,  Guatemala, Honduras, Nicaragua, Colombia,  Guyana,
      Paraguay, Haiti, Bolivia)
Asia
  1
  2
      SE Asia high-/medium-income calorie exporters (Malaysia, Philippines)
      SE Asia high-/medium-income calorie importers (Republic of Korea, Laos, Vietnam, Korea,
      DPR, Kampuchea)
  3   Asia low-income calorie importers (Nepal, Burma, Sri Lanka, Bangladesh)
  4   SW Asia high-income oil exporters (Libya, Iran, Iraq, Saudi Arabia, Cyprus, Lebanon, Syria)
  5   SW Asia medium-/low-income calorie importers (Jordan, Yemen Arab, Yemen Democratic,
      Afghanistan)

Rest of the World -- Developed Countries

      Albania, Andorra, Faeroe Islands, Finland, Gibraltar, Greece, Greenland, Hong Kong, Iceland,
      Israel, Liechtenstein, Malta, Monaco, Norway, Portugal, San Marino, Singapore, South Africa,
      Spain, Sweden, Switzerland, Vatican City, Yugoslavia
                                          A-36

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                                                           Appendix A:  Model Descriptions
                                 TABLE A-6 (Continued)

                             Regional Disaggregation of BLS
Rest of the World - Developing Countries

1    Africa:  Botswana,  British  Indian  Territory,  Cape Verde,  Comoros,  Equatorial Guinea,
     Djibouti, Guinea-Bissau,  Lesotho,  Namibia,  Reunion, St. Helena,  Sao Tome, Seychelles,
     Spanish North Africa, Swaziland, Western Sahara

1    Central America: Antigua, Bahamas, Barbados, Belize, Bermuda, Cayman Islands, Dominica,
     Grenada, Guadeloupe, Martinique, Montserrat,  Netherland Antilles, Panama Canal Zone,
     Puerto Rico, St. Kitts-Nevis,  St. Lucia, St. Pierre and Miquelon, St.  Vincent, Turks and
     Caicos, Virgin Islands (UK), Virgin Islands (USA)

3    South America:  Falkland Islands, French Guinea

4    Asia:  Bahrain, Bhutan, Brunei, East Timor, Gaza Strip, Kuwait, Macau,  Maldives, Mongolia,
     Oman, Qatar, Sikkim, United  Arab Emirates

5    Oceania: American Samoa, Canton and Enderbury Islands, Christmas Island, Cocos Islands,
     Cook Island, Fiji, French Polynesia, Gilbert Islands, Guam, Johnston Island, Midway Islands,
     Nauru, New  Caledonia, New Hebrides, Niue Islands, Norfolk Islands, Pacific Islands, Papua
     New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, Wake Island, Wallis
     and Futuna Islands
                                          A-37

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Policy Options for Stabilizing Global Climate
beginning of each year, the model estimates
regional  prices for the different agricultural
products.  The national and regional models
then base their decisions to allocate capital
and labor based on these prices.  At the end
of  the  year,  the  model  determines  the
wholesale  and  retail  prices,  determines
consumption, and estimates the level of trade.
Export  restrictions  and  tariffs  can  affect
regional  prices as  well as the flow of goods.
Prices for agricultural products and the level
of trade form a major component in the flow
of capital between regions.

National Models

      The national  models  are aggregated
into  three groups based on  the structural
formulation of each  model.   The structure
of the models within  Group 1 are similar;
those within Group 2 are similar (and closely
related to those in Group  1); the structures of
the models within Group 3 are different for
each nation  (USSR  and  Centrally-Planned
Europe are treated as a single nation).

      The national  and  regional  models
address the  specific  factors  that  have  an
impact   on   agricultural  production   and
consumption in each of the countries/regions.
FOr production, these factors include decisions
by domestic producers, allocation of primary
inputs (land, labor, and capital) and allocation
of interine~diate inputs  (feed and fertilizer).
For  consumption and  trade,  these  factors
include stock  holding, sectorial  gross GDP
and  investment,   and  allocation  of family
income.   These factors  also reflect  region-
specific policies and  the relative impact of
these policies.  The approach varies between
groups of models, which reflects the specific
characteristics of the region.

      The availability and allocation of capital
provide a major component of the structure
of the  domestic  models.  Consumers  can
spend  no more than their  after-tax income
plus government  transfers.    Government
revenues  come  from  taxes  or  from  the
ownership  of  production.     Agricultural
production  depends  on  allocation   and
investment of  capital.

      Group  1 and  Group  2 Models.  The
models  for the  Group  1  and  Group  2
countries estimate the behavior of producers,
consumers, and the government and  how this
behavior  will  change  over  time  due  to
changing  economic  conditions and  policies.
These   models   assume   that   agricultural
production   and   the    consumption   of
agricultural  goods  are  determined  in  large
part by  efforts  of  producers to maximize
profit and of consumers to maximize utility,
as well as by policies set by the government.
The parameters of these models are estimated
using data from the time period 1961 to  1976.

      The models   contain  an  agricultural
sector   and   a    non-agricultural   sector.
Production  from the agricultural sector  is
aggregated into  nine commodity classes as
shown in Table  A-7.  The non-agricultural
sector represents  the rest of the economy and
is used as both a sink and source of capital
and  is also used to process  and distribute
agricultural  products.  Figure A-6 illustrates
the  typical  structure within  the  national
models.

      For  each   region,   demand   for
agricultural  products  consists   of   human
consumption, feed,  stocks, and for industrial
use, seed and waste.  The estimates of human
consumption are  based on past consumption
patterns and reflect income, tastes, and habits.
Changes   in  income  and  prices  allow
consumption patterns to change.

      Producer   decision   and   agricultural
production depend  both  on prices  and the
availability of the primary inputs:  land, labor,
and capital.  While  land is used  in  only the
agricultural sector, both the agricultural and
non-agricultural sectors compete for labor and
capital.  For each year and for each crop, the
models  estimate yields,   optimal   fertilizer
application   rates,    and   least-cost   feed
application  rates  and allocates  the  primary
and intermediate  inputs in order to maximize
net income (revenue minus costs).  For crops,
yield is a function  of fertilizer application.
For livestock,  yield  is a function of feeding
intensity.

      Although labor and capital are treated
differently in the models, they are assumed to
be  homogenous  inputs  to the  production
model  and mobile between the  two sectors.
Labor  is  not  disaggregated  based  on  skill
levels or whether  it is family or hired. Within
the agricultural  sector, labor is  allowed to
                                            A-38

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                                                             Appendix A:  Model Descriptions
                                        TABLE A-7

                    Agricultural and Non-Agricultural Commodity  Classes
Commodity'Class                    Main Components               Type of Measurement


Agricultural
Wheat                                                             Total weight
Rice, milled                                                              Total weight
Coarse grains                                                       Total weight
Bovine and ovine meat                                              Carcass weight
Dairy products                                                      Milk equivalent
Other animal products               Pork, poultry, eggs, fish          Protein equivalent
Protein feed                             Oilcakes, fish/meat meal          Protein equivalent
Other food                         Oils, fats, sugar, vegetables,         .    Unit value of exports
                                   fruits, coffee, cocoa, tea          (expressed in US S)
Nora-food agriculture                Clothing, fiber, industrial         Unit value of exports
                                   crops                            (expressed in US S)

Non-Agricultural                     All non-agriculture outputs             Domestic prices
                                                                   (expressed in US S)
                                           A-39

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Policy Options for Stabilizing Global Climate
                                 FIGURK A-6
               TYPICAL OUTLINE OF A NATIONAL MODEL
                                                r   Stocki  4-  pollci««
                                                Excess demand
                                                 trad* deficit
    Source: Parikhctal., 1988.
                                    A-40

-------
                                                             Appendix A: Model Descriptions
 move  freely among  the  various  enterprises
 (associated with the different commodities).

      Capital   is   accumulated    through
 investment   and   depreciation.      Once
 investment in each sector is determined, the
 capital within the sector is fixed.  Over time,
 the capital is freed for reinvestment  through
 depreciation. Capital is mobile  between the
 different enterprises in the agricultural sector,
 although a distinction is made between  crop
 enterprises and livestock enterprises.  Capital
 is more mobile  between the crop enterprises
 than among the livestock subsectors although
 a gradual  shift between crop enterprises and
 livestock enterprises is possible.

      The  model allows   the  amount  of
 available land for cropping and  pasture  to
 change, but it is  very inelastic  to  changing
 economic  conditions.  Technical  progress is
 captured in the yield functions.

      Group 3 Models.  Four models (U.S..
 China,  CMEA,  and  India) make  up  the
 Group 3  category.   The  structure  of  each
 model  is different.

      The agricultural component of the U.S.
 model   is   Michigan  State   University's
 intermediate model of U.S. agriculture, which
 is  an  econometrically  based supply  model.
 The model has some similarities to the Group
 1  and  Group  2 models  but  incorporates
 specific U.S. policies such as domestic price
 policies, trade quotas, land-set-aside  policies,
 and wheat and coarse-grain stock policies.

      The China  model differs considerably
 from  the  other  regional models primarily
 because of the lack  of data available from
 China. As a result, the main purpose of the
 China model is to check for consistency in the
agricultural sector for the scenarios generated.

      The  China  model  differs  from  the
models in Group  1 and Group 2  in terms of
how  yield is treated, how available land is
calculated  and  allocated to  the  different
sectors, and how  data on  animal production
and human consumption is derived.  Yield is
specified as  both  a function of fertilizer use
and irrigation practices.  Cultivated acreage is
a function of arable land,  irrigated land, and
horse power available.  Animal production is
based on trends and the availability of feed,
and   human  consumption   is  based   on
government-set target levels of consumption
that  are  adjusted based on trade and deficit
rcali/aiions.

      The USSR and Centrally-Planned Europe
(CMEA)  model  is  similar   to  the  other
country/regional models but contains funda-
mental  differences  that  reflect  the specific
features  of the centrally-planned economies.
Like the Group 1 and Group 2 models, the
production model uses the same methodology
and is based  on the same data (FAO).  The
differences lie in  that agricultural policy and
policy goals  are  determined  by  a centrally
planned economy and are an integral part of
the central plan for the whole  economy. The
internal market is separated from  the global
market and producer prices reflect production
expenses  as  opposed   to  market  value.
Consumer  prices  reflect  wage  and income
targets and are not set to balance supply and
demand.

      The  differences  between  the CMEA
model and the Group 1  and Group 2 models
include  treatment of growth in the economy,
production   bounds,  consumption  trends,
relationship  to  the   global   market,  and
treatment of land. Users  specify the desired
growth  in  the economy  and  allocation  of
investment.   Lower and  upper bounds  on
production assure levels of supply and  limit
growth  Consumption estimates are based  on
data  from FAO (1981) and published data  on
targets   for  private  consumption.    The
interface with the global market is performed
by   first   adjusting   stocks,    modifying
investments  in  the  rest  of  the  economy,
modifying  investments  in  the  agricultural
sector, adjusting private consumption of non-
agricultural products,  and, finally, modifying
food  consumption.     Land   use  is  not
considered in the model because of the lack
of data in this area.

      The  differences  between  the  India
model and the Group  1 and Group 2 models
are  related   to   the   disaggregation   of
production  into  groups,  the  methods  for
estimating   future   production,   and   the
determination of demand.  Like  the  other
models,   the  India  model   includes   an
agricultural sector and non-agricultural sector,
but the non-agricultural sector is divided into
two components:  rural and urban.  Income is
                                           A-41

-------
Policy Options Cor Stabilizing Global Climate
generated endogenously, and its allocation  is
based on the  distribution  of assets such as
land, livestock, and implements, as well as on
tenancy structure.

      Production is aggregated into 16 major
crops, nine minor crops, and several animal
products  and   is   estimated    using  an
econometric   approach  that   bases   land
allocation on relative differences in expected
revenues. Yields are a function of irrigation,
fertilizer, rainfall, time, and  prescribed  rates
of adoption of high-yielding varieties of crops.

      Consumer  demand is  aggregated into
the nine commodities used with  the other
national models, and the more detailed supply
results   are   combined   for  consumption
purposes. Demand is estimated separately for
each of ten income classes  and reflects an
optimal allocation of income.

      Policy  instruments   available to  the
government  include  tariffs, as  in  the other
countries/regions, but  include some specific
regional capabilities. These include subsidies
on   trade,  buffered   stock  releases   of
agricultural    products,    support   prices,
procurement levels, and procurement prices.
The model  also operates   a food-rationing
system for the urban population.

Regional Models

      Each  of   the   14   regional  models
represents a group of countries at comparable
levels of income with similar relationships to
the world market.  The basis for  the supply
and demand projections for these models are
the  results  from the  moderate  economic
growth  scenario of FAO's  study Agriculture:
Toward 2000  (FAO,  1981).  But since the
FAO projections are based on constant prices,
the models for the low- and medium-income
regions  allow  adjustments  to  the  forecast
using price elasticities based on the behavior
of the  national  models in  the BLS for the
developing countries.   The models ensure
consistent physical and financial balances with
an exchange component that allocates income
for consumption purposes.   For the regional
models   in   the  remaining   high-income
countries, the  approach is the same, but the
supply  and demand  target  levels  follow the
trend of 1961-1980 historical data.
Treatment of Agricultural Variables

      Nitrogenous   Fertilizer.      Inorganic
nitrogenous fertilizer is  an explicit  decision
variable  in  all models except the  regional
models.   The regional  models  determine
nitrogenous fertilizer  use  from  output  of
agricultural   products  using   a  statistical
relationship based  on data from the  early
1980s.  All models consider only inorganic
nitrogen. Table A-8 summarizes the approach
used  within the  different types  of models.
Organic nitrogen is not explicitly  considered
in  the models  and  is  not  part  of  the
production or  yield functions.

      For the national models, nitrogen use
is determined on a per hectare basis, although
the approach varies by model.  The Group 1
models, along with the China, India, and U.S.
models  use   nitrogen    response   (yield)
functions. The Group 2 models and  those of
CMEA  use   production  functions  and
determine  nitrogen  use   by  crop.    Total
nitrogen use for Group 2 and CMEA models
equals acreage times per-hectare use,  summed
over all crops.

      Acreage   Used   in   Rice   Production.
Group  1  models and models  of the  U.S.,
China, and India, determine acreage used in
the production  of  rice.   In  the Group  1
models, rice acreage is a  function of inputs,
including labor and machinery, while in the
U.S.,  China, and  India models,  rice acreage
directly follows  changes  in relative prices.
The Group  2 models, regional models, and
the CMEA  model  simulate rice production
directly as a function of the relative changes
in prices.

      Rice acreage  includes both dryland rice
and paddy rice.  Only paddy rice contributes
to   methane   production.     Table  A-9
summarizes the approach within the different
types of models.

      Ruminants. Ruminant populations are
estimated in  the   models  using  the same
procedures used to  calculate rice  production.
As a result, the numbers of  ruminants are
directly calculated within Group 1 models and
the U.S., China, and India models. Two types
of ruminants are calculated in these models:
dairy cows  and all  other  bovine  and  ovine
                                            A-42

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                                                             Appendix A:  Model Descriptions
                                        TABLE A-8

                   Structure and Approach Used to Estimate Fertilizer Use
Model
      Approach
Group 1 Models


Group 2 Models


Group 3 Models

     China



     India


     U.S. '



     CMEA

Regional Models
Individual crops -- except fruits and  roughage,  which have  a nitrogen
balance built in --  use yield response functions to nitrogen application

Response to nitrogen use is modelled on the basis of total  production
rather than yield per  hectare
Individual  crops use  yield  response functions to  nitrogen fertilizer,
including manure application, but only one average per hectare application
rate (for all crops)

Most  of the important crops use  yield response functions  to nitrogen
application

Wheat,  corn,  soybeans,  and  cotton have  yield response  functions  to
nitrogen application, while the nitrogen balance of the remaining crops are
calculated

Response to nitrogen use is modeled on the basis of total production

Balance  of nitrogen calculated  after the  level of crop production is
determined

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Policy Options for Stabilizing Global Climate
                                         TABLE A-9

                    Structure and Approach Used to Estimate Rice Acreage
Model
      Approach
Group 1 Models

Group 2 Models

Group 3 Models

      China

      India


      U.S.

      CMEA

Regional Models
Acreage allocated to rice according to relative profitability

Production determined directly and rice acreage not estimated



Acreage allocated to rice determined based on  past trends

Acreage allocated to rice, of which there are three different types of crops,
based on relative profitability

Acreage allocated to rice based on relative profitability

Production determined directly and rice acreage not estimated

Production determined directly and rice acreage not estimated
animals  used for meat production.  Table A-
10  summarizes  the  approach  within  the
different types of models.

Completing And Expanding The Estimates
Through 2100

      For  the  purposes of  the emissions
model, the estimates of rice acreage, ruminant
populations,  and  nitrogenous  fertilizer use
must be completed for all of the regions and
then extended through 2100.  As explained in
the previous  section, the acreage  used to
produce rice is  not estimated  for all of the
regions.  Fertilizer use is reported in several
different units  and  must be  converted to
grams of nitrogen.

      The  first step performed by the model
is to estimate  the rice acreage for those
countries/regions where  the acreage is not
solved for directly.  For each time period
between 1985 and 2050,  the model calculates
the average yield  per acre for the countries
where both rice acreage and production are
specified. The model then applies this global
average yield estimate to production of rice
                          for those countries/regions where the acreage
                          has not been directly calculated.

                                Next  the  model   estimates country/
                          regional production of the  nine agricultural
                          product types through 2100 by first estimating
                          regional demand through  2100 and then esti-
                          mating  regional  production to  satisfy that
                          demand.    Using  the  detailed  demand
                          estimates through 2050 for  each of the nine
                          agricultural   product   types,   the   model
                          calculates total demand in the year 2050 for
                          each country/ region where the total demand
                          includes human   consumption,   feed, seed,
                          industrial  use,   and  waste.    Using  the
                          projections  of  regional population  through
                          2100,  the  model  estimates  the  rate  of
                          population growth and applies these rates of
                          growth to total demand in 2050, which results
                          in estimates of demand per country/ region
                          for each time period from 2050 to 2100.
                          Summation  of  the  country and  regional
                          results provides global estimates of demand.
                          Country and  regional production  for  the
                          period 2050 to 2100  are estimated by first
                          growing  production consistent with growth in
                          population  and    then   normalizing   the
                                            A-44

-------
                                                             Appendix A:  Model Descriptions
                                        TABLE A-10

                    Structure and Approach Used to Estimate Ruminants
Model
      Approach
Group 1 Models


Group 2 Models

Group 3 Models

     China

     India

     U.S.

     CMEA

Regional Models
Bovine and ovine animals and dairy cows identified endogenously along
with slaughter weight and milk yield.

Production determined directly and ruminant animals not estimated
Ruminant animals determined based on past trends

Production determined directly and ruminant animals not estimated

Production determined directly and ruminant animals not estimated

Production determined directly and ruminant animals not estimated

Production determined directly and ruminant animals not estimated
production   estimates   so    that   global
production equals global demand.

      Rice yields for each country and region
are held constant after 2050. These yields are
applied to estimated production, resulting in
estimated rice acreage for each country/region
through 2100.

      Estimation of fertilizer  use after  2050
involves several steps.  First, detailed model
results for the period 1985 to 2050 were used
to estimate the relationship between growth
in production of rice, wheat, and coarse grains
and growth in fertilizer use. The model then
applies   this   relationship   to   estimated
production from 2050 to  2100 resulting in
estimates of fertilizer use by region.

      Fertilizer use is tied only to increases in
production of three crops for several reasons.
First, the countries/regions where fertilizer use
are reported by crop, wheat, rice, and coarse
grains account  for  around  70% of fertilizer
use.   Second, the  components of the other
commodity classes include  a wide variety of
products where the fertilizer  use per unit of
product might not be homogeneous between
                          regions  (e.g., clothing, fiber, and industrial
                          crops measured in  U.S. dollars).

                                The functional  form of  the  equation
                          used  to  estimate   regional   nitrogenous
                          fertilizer use, Fft, follows:

                                Fr,t =  Zr,2050 + a(Wr,t ' Wr,205o)

                              + b(Rr t  - RF)205o) + C(Cr,f ' Cr,205o)'

                          where

                                r      =   index for the country/region,

                                t      =   index for  the  year  (e.g.,
                                           2075),

                                Z t    =   fertilizer use  estimated  by
                                           the  BLS  (1985   through
                                           2050) for each  region and
                                           period,
                                  r,t
=    estimated fertilizer use after
     2050,
                                Wrt   =   production of wheat,
                                            A-45

-------
Policy Options for Stabilizing Global Climate
      R
        r.t
       •'r.t
production of rice, and

production    of    coarse
grains.
The parameters a, b, and c represent fertilizer
use per unit of production.   For the regions
Turkey and CMEA, this functional form was
applied starting in 2000 due  to the  high
increases in fertilizer use in  the original BLS
results,  which   were  inconsistent   with
production levels.

      The  parameters  for  fertilizer  use per
unit of production  were estimated using the
results of the BLS through 2050.  The model
selects parameters  a,  b, and c  in order to
minimize the sum of the squares of the error
term Erp where the error term is defined as
follows:'

    Er,t =  Zr,1985  + a(Wr,t  " Wr,198s)

         + b(Rr,t  - Rr,1985)

         + c(Cfit - Cr)1985)  - Zr.t

The summation of the squares  of the error
term is over  all regions (except Turkey and
the USSR, which  display growth rates well
above the rates for all other regions) and over
the time periods 1985  to 2025, in five-year
increments, and 2050.

      Total land use is extrapolated  to  2100
only for those regions where total land use is
estimated by the BLS country/regional models.
The model extrapolates the trend in land use
per capita from 2025-2050 to the period 2050-
2100.

Estimating Emissions of Trace Gases

      The emissions of trace gases estimated
by the agricultural component include  CH4
emissions associated  with  rice production,
N2O  from nitrogenous fertilizer  use,  CH4
from   enteric  fermentation  in  domestic
animals, and  CH4, N2O, NOX, and CO  from
burning of agricultural wastes.  Emissions of
CO2 from the burning of agricultural wastes
are assumed to net to zero each year, since
the carbon released  to the  atmosphere is
recycled during plant growth.
Methane from Rice

      Methane emissions associated with rice
production  occur as a result  of anaerobic
decomposition in flooded  rice fields,  which
allows  CH4 to  escape to the atmosphere
through ebullition  (bubbling)  through  the
water column, diffusion across the water/air
interface,  and transport   through  the  rice
plants.  Research suggests that the amount of
CH4 released to the  atmosphere is a function
of  rice species,  number  and duration of
harvests, temperature, irrigation practices, and
fertilizer use, although quantification of these
factors is poor since few measurements have
been taken.

      Our approach to estimating CH4 from
rice production applies an emission coefficient
to   land    area   under   rice   cultivation.
Measurements  of rice paddy CH4 flux have
yielded  average emission coefficients of 25 g
CH^n^/harvest  for   a  study in  California
(Cicerone et  al., 1983) to  54  g  CH4/m2/
harvest for a study in Italy (Holzapfel-Pschorn
and Seller, 1986). Using the flux-temperature
relationship derived  from  the Italian data,
Holzapfel-Pschorn and Seiler (1986) derived
emission coefficients  from approximately 45 to
120 g  CH4/m2/harvest for  the tropical  and
sub-tropical regions, where over 95% of the
global rice acreage is located.  We adopted a
mid-range   emission   coefficient   of   75
g/m2/harvest, which  when  multiplied by  the
harvested rice paddy acreage in 1985 of 144.7
million  hectares  (FAO,   1986),  yields   an
annual emission of about  110 Tg, the same
number  as   that  given  by  Cicerone  and
Oremland   (1988) for  this  source.    The
emission coefficient is applied to estimates of
future  land  area under cultivation (double-^
cropped areas are  counted  twice),   which
accounts for land each  time it is harvested.
However, the  land area estimates from BLS
include  estimates of  land area for dry rice as
well as  land area for paddy rice.  Dry  (or
upland) rice fields are not flooded and do not
emit CH4.   Also, land used for upland  rice
represents only a small fraction of the land
area under rice cultivation  (less than 9% in
Asia, where over 90% of the world's rice is
grown).   The model adjusts for this  by
reducing  the  land acreage  under   rice
cultivation.
                                           A-46

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                                                            Appendix A:  Model Descriptions
Methane Emissions from Enteric Fermentation
in Domestic Animals

      Methane  is  a by-product  of enteric
fermentation in herbivores, a digestive process
by which carbohydrates are broken  down by
microorganisms   into simple  molecules  for
adsorption into  the bloodstream.   Although
some non-ruminant animals produce CH4, the
highest losses come from  ruminants.   The
quantities of CH4  emissions depend on  the
type, age, weight, and energy expenditure of
the animal, as well as the quality and quantity
of feed.

      The  approach  to  estimating  future
emissions involves  several steps:   estimating
animal   populations,   selecting    regional
emission   coefficients  and  applying   the
emission    coefficients    to   the   animal
populations, and  allowing  these  emission
estimates  to  increase  over  time   using
estimates of  future agricultural  activities.
FAO  data  (FAO,  1986)  provided animal
populations by type (cattle, dairy cows, sheep,
buffalo, goats, pigs, horses, camels, mules, and
asses) and by country. For each animal type,
emission  coefficients were obtained  from  the
literature (Crutzen et al.,  1986, and Lerner et
al.,  1988).   Estimates  of the appropriate
coefficients   to   apply   to   the   animal
populations for  each country  were based on
factors such as the uses to which the animals
were put  and the feeding practices. Applying
the  emission  coefficients to  the  animal
populations resulted in estimates of emissions
by animal type and by  country. Table A-ll
summarizes  these  emission   estimates  by
region and animal  type.   The model then
aggregated   these   emissions   into  four
categories for each of the 34 countries/regions
represented by the individual models  within
BLS:

•     emissions related to bovine and ovine
      meat  production, which equaled  the
      emissions from cattle and sheep;

•     emissions related to  dairy production,
      which equaled the emissions from dairy
      cows;
•     emissions  related   to   other   meat
      production,   which   equaled   the
      emissions from pigs; and

•     all  other  emissions  from  domestic
      animals.

      The  method  for  estimating emissions
over time reflected the data available in all of
the individual models within the BLS.  Some
of the country models  included information
on  animal  stocks and feed  usage, but since
bovine and ovine animals were combined and
the animal  stock  was  available  for  only  a
portion of the countries/regions, the following
approach was used for each  country/region:

•     growth in emissions from bovine  and
      ovine meat  production are  consistent
      with  the growth  in meat  production
      from the BLS;

•     growth in emissions from  dairy  cows
      are consistent with the growth in dairy
      production from the BLS;

•     growth in emissions related to pigs are
      consistent with growth in other meat
      production  from the BLS; and

•     emissions from all  other sources are
      kept  flat.

Several major issues concerning  the emissions
forecasts should be addressed.  First, impacts
on  emissions  due  to  changes  in  feeding
practices over  time  will not  be  captured
within this  approach because information on
the feed  use  for  the  animals  and  animal
stocks is limited.  Second, the combination of
cattle and  sheep  into one category  assumes
that the ratio of these two  animal populations
remains constant within each region.  Annual
emission coefficients range from  35 to 55
kg/animal for cattle  to  5  to 8 kg/animal for
sheep (Crutzen et al., 1986), and meat  yield
varies from 100 to 300 kg/animal for cattle to
5 to 30 kg/animal for sheep (FAO, 1986).  In
Brazil  and  the   U.S.,  for example,   this
assumption can lead to an error of up to 15%
and 20%, respectively, in  the emissions  per
                                           A-47

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Policy Options for Stabilizing Global Climate
                                                                         TABLE A-U
                                                        1984 Animal Populations and Emission Estimates
Cattle
Region*
ARGENTINA
AUSTRALIA
AUSTRIA
BRAZIL
CANADA
EGYPT
INDONESIA
JAPAN
MEXICO
NIGERIA
PAKISTAN
TURKEY
EEC
KENYA
NEW ZEALAND
THAILAND
CMEA
CHINA
INDIA
U.S.
AFRICA-1
AFRICA-2
AFRICA-3
AFRICA-4
AFRICA-5
LATIN AMER-1
LATIN AMER-2
LATIN AMER-3
ASIA-1
ASIA-2
ASIA-3
ASIA-4
ASIA-5
REST OF
WORLD
TOTAL
Pop.
50530
20426
1652
118101
10556
870
6615
3209
28600
10620
13672
11000
51705
9200
5791
4609
94519
57660
155160
102840
4016
12390
5658
47913
44654
22707
16622
38551
2437
6891
47904
7901
3306
32286

1050571
Emis.
(10* g)
2729
1103
58
6377
581
30
232
113
1001
372
479
385
1825
322
204
161
3337
2018
5431
5656
141
434
198
1677
1563
795
582
1349
85
241
1677
277
116
' 1361

42908
Sheep
Pop.
(10J H)
30000
139242
214
17500
791
1450
4790
22
6400
12000
24272
48707
62184
6700
70344
22
185605
98916
40890
11411
15085
8134
22507
47018
30745
26108
21197
13186
99
365
4949
65330
23823
100180

1140186
Emis.
(10* g)
150
696
2
88
6
7
24
0
32
60
121
244
497
34
563
0
1485
495
204
91
75
41
113
235
154
131
106
66
0
2
25
327
119
725

6917
Dairy Cows
Pop.
(10fH)
2970
1735
981
14700
1728
955
185
1473
8900
1180
2680
6200
28073
2800
2119
11
57551
857
27000
11200
859
669
1984
6522
5735
2551
2750
4347
58
325
6684
3357
1559
10660 ,

221358
Emis.
(10* g)
160
94
88
794
145
33
6
133
312
41
94
217
2527
98
191
0
5180
30
945
941
30
23
69
228
201
89
96
152
2
11
234
117
55
843

14180
Pigs
Pop.
(10J H)
3800
2527
3881
33000
10760
15
3620
10423
18370
1300
0
11
78703
100
420
4150
143467
298693
8650
55819
657
2179
401
1590
2996
8301
5846
8207
9829
19909
3230
289
0
45297

786440
All Other
Emis.
(10* g)
4
3
6
33
16
0
4
16
18
1
0
0
118
0
1
4
215
299
9
84
1
2
0
2
3
8
6
8
10
20
3
0
0
67

959
Pop.
(103 H)
6403
719
74
17520
409
5847
10828
81
21962
26968
45586
19678
3997
8932
208
6198
17933
12840
147880
11755
5192
8205
12955
47034
54829
3554
7227
11504
5645
5323
25555
25793
9991
32618

721243
Emis.
(10* g)
70
9
1
172
7
133
169
1
152
136
842
135
40
78
2
308
231
1528
3681
193
34
43
121
412
641
42
51
93
174
217
544
169
69
254

10751
Total
Pop.
(103 H)
93703
164649
6802
200821
24244
9137
26038
15208
84232
52068
86210
85596
224662
27732
78882
14990
499075
568966
379580
193025
25809
31577
43505
150077
138959
63221
53642
75795
18068
32813
88322
102670
38679
221041

3919798

Emis.
(1° g)
3113
1905
155
7464
755
204
434
262
1515
610
1536
980
5008
532
960
474
10447
4370
10270
6965
280
543
501
2554
2561
1065
841
1669
272
492
2482
890
358
3249

75715
* For an explanation of the regions, see Table A-6.
Sources:  FAO, 1985; Crutzen et al., 1986; Lerner et al., 1988; Fung, pers. communication.

-------
                                                            Appendix A: Model Descriptions
 ton meat production  from the two animals.
 Also, the ratio of meat production to animal
 stocks is assumed to remain constant within
 each region.

 Nf> Emissions  from  Fertilizer  Use  and
 Legumes

      Application  of nitrogenous  fertilizer
 enhances the rate of flux of  N2O released
 through  microbial  processes  in  soils both
 through nitrification and denitrification.  The
 enhanced emissions vary considerably due to
 type of fertilizer used, application practices,
 soil conditions,  rainfall,  and  other  factors.
 Research has also shown that use of legumes
 to fix nitrogen will  also enhance the flux of
 N2O to  the  atmosphere.    It  has  been
 estimated  that  enhanced levels of  N2O
 emissions  result  from   the   leaching   of
 nitrogenous fertilizers into surface water and
 ground waters.

      The  approach  to  estimating   the
 fertilizer-induced emissions of N2O involves
 disaggregating nitrogenous fertilizer use into
 five categories, applying emission coefficients
 (fraction of N applied that  evolves as N2O) to
 each of these categories to estimate the direct
 emissions from  the  soils, and  applying  a
 separate emission coefficient to approximate
 the emissions resulting from leaching.   The
 five categories of nitrogenous fertilizer, which
 were selected based on similarities in emission
 rates, are as follows:

 •     Ammonium  Nitrate and  Ammonium
      Salts;
 •     Nitrate;
 •     Urea;
 •     Other Nitrogenous and Other Complex;
      and
 •     Anhydrous Ammonia.

 The allocation of  the fertilizers to  these
 categories were based  on statistics from FAO
 (FAO, 1987),  and the relative  shares were
 kept  constant   over  time   unless  policy
objectives included  the conversion to  other
 fertilizer types.

      The emission coefficients were obtained
from  the literature  (Galbally,  1985; Fung,
pers. communication) and are reproduced in
Appendix B.  Since estimates  from different
sources (Eichner,  1988;   Breitenbeck,  pers.
communication) vary considerably, the model
allowed  sensitivity analysis  using different
coefficients.     The   literature   addressing
enhanced fluxes from leaching of fertilizer and
from  human and  animal  wastes  provided a
wide range of emissions, from approximately
0.5%  to over 3% of nitrogen evolved as N2O
(Conrad  et al., 1983; Kaplan et al., 1978;
Ronen  et  al.,  1988).   Due  to  the large
uncertainties and  the  wide range of factors
involved,  one  coefficient  (2%  of nitrogen
evolved as  N2O) was applied to all fertilizer
types  equally  and  allowed  to  vary between
runs to test the sensitivity  of the results to
the different assumptions.

      Enhanced N2O emissions from legumes
are as highly uncertain, ranging from  0.02 to
0.3 Tg N per  year (Eichner, 1988).  For the
purpose of this analysis, these emissions were
assumed  to lie towards the lower  range, i.e.,
0.02 Tg N.

Emissions from the Burning of Agricultural
Wastes

      Emissions of N2O, CH4,  NOX, and CO
result from the burning of agricultural wastes
such  as  rice  straw  (emissions of CO2  are
recycled  in  the  plant  growth).  The model
estimates emissions using estimates of current
global emissions of the different gases from
the literature  (Logan  et al., 1981; Crutzen,
1983;  Logan, 1983; Bolle et al., 1986; Crutzen
et al.,  1979; Seiler and Crutzen, 1980; Seiler
and Conrad, 1987; Cicerone and  Oremland,
1988) and allows these  emissions to grow over
time consistent with growth in total land use
for agriculture  as predicted   by  the BLS.
Since land  use is not provided for  all regions
within the BLS, the  total land  use for those *
regions where it  is specified  is  used as a
proxy.  Table A-12 illustrates  the range of
emission estimates from these sources.

LAND-USE CHANGES AND NATURAL
EMISSIONS MODULE

      Natural  sources   of  emissions   of
greenhouse   gases   include    anaerobic
decomposition  in  wetlands   and   enteric
fermentation  in  wild  ruminants   (CH4),
nitrification and denitrification in soils (N2O),
natural processes in oceans and fresh waters
(N2O), and lightning (NOX). Emissions from
changes in  land use include CO2, N2O, CH4,
                                           A-49

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Policy Options for Stabilizing Global Climate



                                       TABLE A-12

             Estimates of Current Emissions from Burning of Agricultural Wastes

Lower Range
Model
Upper Range
N2O
(Tg N)
0.3
0.4
0.6
CH4
(Tg CH4)
14
15
28
NOX
(TgN)
1
4
7
CO
(TgC)
30
67
110
        Sources:

        N2O = Crutzen, 1983; Seller and Crutzen, 1980.
        CH4 = Cicerone and Oremland, 1988; Seiler and Crutzen, 1980.
        NOX = Logan, 1983; Seiler and Crutzen, 1980.
        CO  = Logan et al, 1981; WMO 1985; Seiler and Crutzen, 1980.
NOX,  and CO from biomass burning during
deforestation, and enhanced N2O  emissions
from disturbance of soils.

Estimating Natural Emissions of Trace Gases

      The procedures for estimating emissions
of trace gases from natural sources involved
the selection of estimates of current emissions
from the literature and making sure that these
estimates   were   consistent   with   other
parameters and emission estimates within the
model.  These estimates were held constant
over time except where modified by feedbacks
from changes in CO2 concentrations or from
changes in realized warming (see discussion in
Feedbacks below).

      Table  A-13 summarizes  the different
natural sources of trace gases included in the
analysis.   The table provides references for
the different  estimates and also  provides
ranges on the emissions estimates from the
literature. The emission estimates  under the
heading labeled Model refer to the estimates
used  in  the six  scenarios  described  in
Appendix B  and in the rest of the  report.
Estimating Emissions  from Changing Land
Use

      Emissions of trace gases from changing
land  use  include  releases  of CO2  from
burning  and/or decomposition of  organic
matter during land clearing and deforestation;
releases  of  CO   and
N2O
                              due  to  soil
disturbance after land clearing; and releases of
N2O,  CH4,  NOX,   and   CO  from   the
combustion   of  organic   matter   (biomass
burning)  due  to  prescribed  forest
burning  of  savanna' '" ~aSS~~HvsSS
idefbrestatjSn; ^    1ba^d»~~xle*afiSg   and
deforestation are  driven  by  a number x of
factors; the  importance of  each  varies  by
region and by country.  Inj^opicajLA-frica and
South and Southeast Asia, jra]*M jpopulation
growtfiT™ajppears ^o^^^^ "siitical- factor
affecfinj^deK^tafibn.  The niajority of the
population engages in agricultural practices,
arid  most of the increases in agricultural
production have come from increases in the
area under cultivation through deforestation.
Seventy  percent  of Africa's  deforestation
stems from swidden agriculture.
                                           A-50

-------
                                                           Appendix A: Model Descriptions
                                       TABLE A-13

                    Estimates of Current Emissions  from Natural Sources
Trace
Gas
Source
Emission Estimates
Model  Low  High
Reference
CR,
Wetlands
(Tg CH4)  Wild Ruminants &
           Small Herbivores
          Termites
          Oceans
          Freshwater
          Wildfires
  O     Natural Lands
  g N)   Oceans/Freshwater
         Wildfires
115     100   200      Cicerone and Oremland, 1988

  4      26       Crutzen et al., 1986
 40      10   100      Cicerone and Oremland, 1988
 10      5    20       Cicerone and Oremland, 1988
  5      1    25       Cicerone and Oremland, 1988
  2      24       Cicerone and Oremland, 1988;
                       Seiler and Crutzen, 1980

  6                    Bolle et al., 1986
  2                    Bolle et al., 1986
  0.05    0.04           0.07Crutzen, 1983;
                       Seiler and Crutzen, 1980
NOX
(TgN)

CO
(TgQ
Soils
Lightning
Wildfires
Oceans
Wildfires
12.5
3.5
0.5
20
10
4
2
0.1
10
5
16
20
0.9
35
20
Logan, 1983; WMO, 1985
Logan, 1983; WMO, 1985
Seiler and Crutzen, 1980
Logan et al., 1981; WMO, 1985
Logan et al., 1981; WMO, 1985
      The procedures for estimating current
and future emissions of trace gases from these
sources   involves   implementation  of   a
terrestrial carbon model and parameterization
of emissions  of N2O,  CH4, NOX, and CO
based on the  literature.  Several scenarios of
tropical    deforestation   and    plantation
establishment   were   developed    (see
APPENDIX B and Houghton, 1988), and the
Marine   Biological  Laboratory/  Terrestrial
Carbon  Model   (MBL/TCM) was used  to
forecast   CO2   emissions   from
deforestation/reforestation and associated land
disturbance.   Current emissions of the other
four gases resulting from soil disturbance and
biomass  burning  were  taken  from   the
literature, and then either kept flat over time
or tied to future emissions of CO2 from land
clearing.
                                      Flux  of CO2  Between the Atmosphere  and
                                      Land   Resulting  from   Deforestation   and
                                      Reforestation

                                            The model  of the net flux of CO2
                                      between  the   atmosphere  and   terrestrial
                                      biosphere (MBL/TCM) acts as a bookkeeping
                                      device that  uses scenarios of changes  in the
                                      use of land  as a key input to changes  in the
                                      balance of carbon in the  soils and vegetation
                                      (Houghton et al., 1983).  The model requires
                                      estimates of the rate of land clearing, the fate
                                      of  the  cleared land,  and  the  amount of
                                      biomass stored both in the vegetation and in
                                      the soils.

                                            When forested  land  is  cleared,  the
                                      carbon   stored  within   the vegetation  is
                                      oxidized quickly through burning  either to
                                          A-51

-------
 Policy Options for Stabilizing Global Climate
dispose of the biomass or use as a fuel, or the
vegetation  is  oxidized slowly through decay
and  decomposition.   The   model  captures
these  different  rates   of   oxidization  by
allocating the  cleared land  to  three  major
categories:

•     cleared  for fuelwood;
•     cleared  for use as crops or pasture; or
•     cleared  for harvest and industrial use.

A response curve for each type of ecosystem
and  each category  of clearing activity  maps
emissions of carbon over time, including after
the land is abandoned and the vegetation is
allowed  to regrow.   Furthermore, the land
cleared  for harvest  and industrial  use  is
further categorized  according to whether the
products  are   used  for  paper  and  paper
products (40% of the category) or for lumber
or industrial wood.  The rate of oxidation for
vegetation cleared for fuelwood is assumed to
be within 1 year of clearing; paper and paper
products decay within 10 years, and lumber
and industrial  wood can take up to 100 years
to decay. Cleared  vegetation from different
land types decays at various  rates (see Table
A-14).   Figure A-7  illustrates  for tropical
forests the response curve for changes in the
carbon   content  in  vegetation   following
clearing  for   agriculture, as  well  as  what
happens if the land is abandoned.
      Response curves also show the changes
in the content of carbon in  the  soils after
changes in land use (see Figure A-7).  Unlike
the carbon content in vegetation, the carbon
content in soils may increase shortly after the
land is cleared but then declines gradually as
the biomass decays.

      The MBL/TCM considered only fluxes
from   tropical  regions  (tropical  Africa,
America,  and  Asia) and  two  types  of forests
(open   and   closed).     Emissions   and
accumulation  of carbon were projected from
1985  through 2100.    Land-use  changes
included deforestation to create permanent
croplands  and  afforestation/  reforestation,
which   consisted   of   the   formation  of
plantations.  The maximum error introduced
by not considering abandonment of cropland,
shifting  agriculture,  and  no  shifting  to
pastures  is   less   than  10%  (Houghton,
unpublis-hed data).  Clearing from temporal
and boreal regions were not included because
recent estimates suggest  that the net flux in
these regions is currently low.

      The MBL/TCM used a low and a high
estimate of the amount  of carbon stored in
the vegetation and soils of different land-use
types. These estimates are based on the data
shown in Table A-15.  In cases where two
estimates are shown in the table (i.e.,  carbon
                                        TABLE A-14

                          Fate of Carbon in Undisturbed Ecosystems
                            After Land is Cleared for Agriculture
                                                                             Years
                                                                         Required for Soil
Fraction Left
Fraction Oxidized
Ecosystem Dead in Soils By 1st Year
Tropical Moist Forest
Tropical Seasonal Forest
Tropical Woodland/Scrubland
Tropical Grassland
.33
.33
.50
.50
.40
.40
.40
.50
By 10th Year
.67
.67
.50
.50
to Reach Minimum
Carbon Content
15
15
15
15
Source:  Houghton et al., 1983.
                                            A-52

-------
                                      Appendix A: Model Descriptions
                        FIGURE A-7
          TROPICAL FOREST RESPONSE CURVES
  a
  £
c **
o e
JQ o
« **
,*5 n
                                                     Time
Clear
                       Abandon
                                                     Time
          Clear
             Abandon
                          A-53

-------
Policy Options for Stabilizing Global Climate
                                       TABLE A-15

                    Carbon in Vegetation and Soils of Different Land-Use
                      Categories in the World's Major Tropical Regions
                             Carbon in Vegetation*
                             (IP3 kg
                Carbon in Soils
                (IP3 kg hectare'1*)
Tropical
Region
America


Africa .


Asia


Type of
Forest
Moist
Seasonal
Dry
Moist
Seasonal
Dry
Moist
Seasonal
Dry
Undisturbed
Forest
82 (176)
85 (158)
27 (27)
124 (210)
62 (160)
15 (90)
135 (250)
90 (150)
40 (60)
Mature
Fallow
33 (70)
34 (63)
11 (11)
50 (84)
'25 (64)
6 (36)
90 (90)
50 (50)
35 (35)
Agriculture
5
5
5
5
5
5
5
5
5
Undisturbed
Forest
100
100
69
100
100
69
120
80
50
Mature
Fallow
90
90
62
90
90
62
108
72
45
Agriculture
70
70
48
70
70
48
84
56
35
 * Values outside parentheses are derived from volumes of growing stock.  Values inside
parentheses are based on direct measurements of carbon stocks.

Source: Houghton et al., 1985.
in  vegetation  of  undisturbed  forest  and
mature fallow), the values outside parentheses
were used for the low biomass estimates, and
the values  inside parentheses  were used for
the high biomass estimates.

      Table A-16 summarizes the assumptions
used for the rate of deforestation from 1975
through 1980, which were used in the base
year (1985) estimates of CO2  emissions.   In
scenarios associated with high  biomass, areas
of  fallow  forests  were   converted   to
permanently cleared land at rates around 60%
higher than  the rates  used  with the low
biomass assumptions.  Also, when the high
biomass assumptions are used,  higher rates of
clearing of tropical  forests  are used;  these
higher rates  include estimates of  tropical
forests cleared by the landless, which may not
be  included in  FAO  statistics (Houghton,
1988;  Houghton et al., 1983).
Emissions of N2O,  CH^ NOX and CO

      Current estimates of emissions of N2O
resulting from the  gain of cultivated land are
based on estimates in the  literature (Bolle et
al., 1986; see Table  A-17) and are grown
according to patterns  of the net flux of CO2
from tropical deforestation as projected by the
MBL/TCM.  This ties the emissions  of N2O
closely to the model estimates of the amounts
of tropical land cleared  in each year.

      Estimates  of emissions of N2O, CH4,
NOX, and CO resulting from biomass  burning
were  disaggregated   into  several different
categories (Seiler  and  Crutzen,  1980;  see
Table A-17):

•     Industrial  combustion of biomass and
      fuelwood;
                                           A-54

-------
                                                             Appendix A:  Model Descriptions
                                        Table A-16

                           Annual Rates of Deforestation (1975-80)

                                     (106 hectare/year)
Region
Tropical America
Tropical Africa
Tropical Asia
Total
Closed Forest
4.4
1.3
1.8
7.5
Open Forests
1.3
2.3
0.2
3.8
Fallow Forests
2.8
1.5
5.7
10.0
The low biomass assumptions were based on rates of deforestation in the closed and open forests;
the high  biomass assumptions were  based on rates of deforestation in closed, open, and fallow
forests.

Sources:  Houghton et al., 1985; Houghton et al., 1987.
                                            A-55

-------
Policy Options for Stabilizing Global Climate
                                        TABLE A-17

                    Estimates of Current Emissions from Land-Use Change
Emission Estimates
Trace Gas
CH4
(Tg CH4)


N2O
(TgN)



NOX
(TgN)

CO
(TgC)

Source
Shifting agriculture, population
increase and colonization
Prescribed fires, savanna and
bush burning
Gain in cultivated land
Shifting agriculture, population
increase and colonization
Prescribed fires, savanna and
bush burning
Shifting agriculture, population
increase and colonization
Prescribed fires, savanna and
bush burning
Shifting agriculture, population
increase and colonization
Prescribed fires, savanna and
bush burning
Model
19.8
9.5

0.4
0.5
0.3

5
2
160
50
Low
18
9

0.2
0.4
0.2

1
1
85
25
High
35
18

0.6
0.7
0.4

9
4
300
90
References
Cicerone and Oremland,
1988; Seiler and Crutzen, 1980
Cicerone and Oremland,
1988; Seiler and Crutzen 1980
Bolle et al., 1986
Crutzen, 1983;
Seiler and Crutzen, 1980
Crutzen, 1983;
Seiler and Crutzen, 1980
Logan, 1983;
Seiler and Crutzen, 1980
Logan, 1983;
Seiler and Crutzen, 1980
Logan, 1981; WMO, 1985;
Seiler and Crutzen, 1980
Logan, 1981; WMO, 1985;
Seiler and Crutzen, 1980
•     Burning of agricultural wastes;

•     Wildfires;

•     Shifting  agriculture,  population,  and
      colonization; and

•     Prescribed  forest   fires,   and
      burning of savanna and bushland

Procedures  for  estimating  future  emissions
due to  industrial biomass and  fuelwood use,
burning of agricultural wastes, and wildfires
were described  in  the  sections  of  this
appendix that discuss emissions from energy-
related  sources, and  natural and  agricultural
sources.     Table   A-17  summarizes   the
estimates  along  with references for  these
emissions.                                 x

      Estimates of future emissions of these
gases from shifting  agriculture, population
pressures,  and  colonization  are  tied  to
patterns of net fluxes of CO2 resulting from
tropical   deforestation  which,   for   each
deforestation scenario, closely reflect the rate
of land clearing in the tropics and also reflect
differences   in  biomass   stored   in   the
vegetation.  Emissions from prescribed forest
fires, and burning  of savanna and bushland
are kept flat over time.
                                            A-56

-------
                                                            Appendix A: Model Descriptions
ATMOSPHERIC COMPOSITION MODULE

      The At mospheric Composition Module
estimates changes in atmospheric concentra-
tions  of trace  gases  using a  highly para-
meterized model  developed for  this  study.
The  Assessment  Model  for   Atmospheric
Composition  (AMAC)  was  developed  by
Michael Prather of NASA/GISS, in coopera-
tion   with  members  of  the  atmospheric
sciences community (see Table  A-18).  This
model was then closely integrated  with  an
ocean uptake model to determine CO2  and
heat uptake by the ocean, and with the entire
ASF  to  achieve  complete specification  of
emissions of the different trace gases.

      The atmospheric composition model is
a highly  parameterized model for estimating
atmospheric composition.   The  model uses
first- and second-order relationships between
parameters  to  estimate  the   effects   of
emissions on the  global atmosphere and  on
global   warming.     Annual   and  globally
integrated quantities are used to define first-
order  effects on climate, stratospheric  ozone,
and tropospheric oxidants  in so far as they
control  atmospheric  composition  (Prather,
1989).  The primary advantages of the model
are that it represents the interactions between
chemistry, composition, and climate and that
it can be run for a large number of scenarios.
Its primary  limitations pertain to the high
parameterization  and simplification  of  the
physical   processes  occurring   in   the
atmosphere.

      To estimate atmospheric concentrations
or perturbations to concentrations of different
long-  and  short-lived species  the  model
combines estimates of emissions of chemically
and radiatively active  trace gases  with  an
ocean CO2 and heat uptake model, a  model
of increased forcing due to  increases  in
atmospheric  concentrations  of  radiatively
active  gases,  and  a  model   of emission
feedbacks.  The model uses global emissions
estimates of 14 long-lived gases and estimates
of emissions of CO, NOX, and non-methane
hydrocarbons (NMHCs) by hemisphere. The
ocean CO2 and heat uptake model  is a box
diffusion formulation introduced by Oeschger
et al. (1975) and utilized by Hansen et al.
(1988).   The model of increased forcing  is
based on calculations from a one-dimensional
radiative convective model (Hansen  et al.,
1981; Hansen et al., 1988; Ramanathan et al.,
1985). The model of feedbacks is based on
work by Lashof (1989) and captures increased
fluxes of CH4  from  rice paddies, bogs, and
from  CH4  hydrates  due  to  increases in
temperature; uptake of CO2 due to increased
fertilization   from   increased   CO2
concentrations;  and  increases   in   CO2
emissions resulting from increased respiration
under higher temperatures.

      Table A-19  lists the long-lived  gases
included in the model formulation. The long-
lived  gases  include major  radiatively  active
gases, such as N2O, CH4, CO2, CFC-11, CFC-
12, HCFC-22,  carbon tetrachloride (Ccl4),
methyl  chloroform  (CH3CC13), and  halon
1301 (CF3Br), as well as gases that affect the
composition of the  stratosphere,   such as
N2O, CFC-11, CFC-12, HCFC-22, CFC-113,
Ccl4,  CH3CC13, methyl  chloride  (CH3C1),
halon 1301  (CF3Br), halon 1211 (CF2ClBr),
and methyl bromide (CH3Br),

      Table A-20  lists  the short-lived  and
implicitly solved species included within  the
model.  They include water vapor, NOX, CO,
OH,   tropospheric    O3,   column    O3,
stratospheric O3,  and  variables for  total
inorganic  chlorine,  inorganic bromine,  and
odd nitrogen.  NOX and NMHCs are treated
differently  in  the  model  than  the  other
implicitly solved species in that all estimates
of  the  impact  of  changes   related  to
perturbation of these gases in  the atmosphere
are based directly on changes  in emissions.

      Uncertainty surrounding the estimates
of  future   atmospheric   composition   and
changes in climate are captured by varying the
key  parameters  in  the  model.    These
parameters define the climate feedback,  the
coupling between chemically active gases and
the short-lived  and implicitly solved species,
and  the lifetimes of long-lived gases.  While
the  variations used  do  not  represent a
detailed and complete uncertainty  analysis,
they  demonstrate the  range  of uncertainty
surrounding  the  results  and  the  relative
importance of the different assumptions.

Estimating the Atmospheric Content of Long-
Lived Trace Gases

      The   model  determines   the global
atmospheric content of the long-lived  gases,
                                           A-57

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Policy Options for Stabilizing Global Climate
                                    TABLE A-18

                   Participants, Contributors, and Reviewers Workshop:
                         A Model for Atmospheric Composition
                 Name
Affiliation
                -Dan Albritton
                 Robert Dickinson
                 Inez Fung
                 Richard Gammon
                 James Holton
                 Ivar Isaksen
                 Malcolm Ko
                 Andrew Lacis
                 Dan Lashof
                 Shaw Liu
                 Jennifer Logan
                 Jerry Mahlman
                 Pauline Midgley
                .Michael Prather
                 Ron Prinn
                 Nien Dal Sze
                 Anne Thompson
                 Dennis Tirpak
                 Don Wuebbles
NOAA, Colorado
NCAR, Colorado
NASA, New York
NOAA, Washington
U. Wash,, Washington
U. of Oslo, Norway
AER, Massachusetts
NASA, New York
U.S. EPA, Washington, D.C.
NOAA, Colorado
Harvard, Massachusetts
NOAA, New Jersey
ICI, Delaware
NASA, New York
MIT, Massachusetts
AER, Massachusetts
NASA, Maryland
U.S. EPA, Washington, D.C.
LLNL, California
                 Source: Prather, 1989.
                                        A-58

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                                             Appendix A:  Model Descriptions
                         TABLE A-19




                      Long-Lived Gases
Gas
Nitrous Oxide
Methane
Carbon Dioxide
CFC-11
HCFC-12
CFC-22
.CFC-113
Carbon Tetrachloride
Methyl Chloroform
Methyl Chloride
Halon 1301
Halon 1211
Methyl Bromide
Carbon Tetrafluoride
Chemical
Symbol
N2O
CH4
CO2
CFC13
CF2C12
CHF2C1
qF3ci3
Ccl4
CH3CC13
CH3C1
CF3Br
CF2ClBr
CH3Br
CF4
Reference
Concentration
300 ppb
1600 ppb
345 ppm
220 ppt
375 ppt
80 ppt
30 ppt
100 ppt
110 ppt
600 ppt
2 ppt
2 ppt
10 ppt
60 ppt
Source:  Prather, 1989.
                            A-59

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Policy Options for Stabilizing Global Climate
                                     TABLE A-20

                         Short-Lived and Implicitly Solved Species
           Reference
Species       State       Description
trop-OH    (%)1         mean perturbation to global OH levels
NH-OH    (%Y         mean perturbation to OH levels in the northern hemisphere
SH-OH    (%y         mean perturbation to OH levels in the southern hemisphere
NH-O3     (%)          mean perturbation  to  tropospheric ozone  levels in the  northern
                        hemisphere
SH-O3     (%)1         mean perturbation  to  tropospheric ozone  levels in the  southern
                        hemisphere

NH-CO    (100 ppb)    mean concentrations of CO in the northern hemisphere
SH-CO     (60 ppb)     mean concentrations of CO in the southern hemisphere

trop-H2O   (%)!         perturbation to mean tropospheric water vapor

col-O3     (%)1         perturbation to total ozone column
upp-O3     (%Y         perturbation to ozone column above 30 km

str-NO     (18 ppb)     (HNO3+NO+NO2+NO3+2xN2O5+HNO4+ClNO3 at ~ 35 km)
str-CL.     (2.78 ppb)    (HCl+Cl+ClO+2xCl2+HOCl+ClNO3 at ~ 40  km)
str-Brx     (12.9 ppt)    (BrO+Br+HBr+HOBr+BrNO3 at ~ 25 km)

str-H2O    (3 ppm)      mean concentrations at tropopause


1 The reference states of these species are modeled as % changes from their  values in the reference
year (1985).

Source:  Prather, 1989.
                                         A-60

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                                                             Appendix A:  Model Descriptions
excluding CO2, on an annual basis by adding
annual  sources  and  removing (subtracting)
annual losses. Annual sources are defined by
the four emissions models and are checked
for consistency  with  assumptions on  global
lifetimes   and    observed    increases   in
atmospheric  concentrations.   Annual  losses
reflect atmospheric destruction and are based
on global  lifetimes  of  the  gases.    The
atmospheric  content  of  CO2  is  treated
separately with an ocean uptake model, which
models the dominant sink of carbon.

      If  global  lifetimes   and  observed
increases in atmospheric concentrations for a
long-lived  trace  gas  are specified  for the
reference year, 1985,  then the annual source
in  that  year  equals  the  annual loss  (e.g.,
atmospheric burden divided by global lifetime)
plus the annual increment.   If the emission
estimates from the emissions modules do not
equal this value then the  difference is noted
and the  emission estimates are scaled  to the
estimated annual source described above.

      The atmospheric composition  model
obtains the annual sources of the long-lived
gases from the four emissions modules.  For
all gases,  excluding CO2,  the  emission
estimates  include  all anthropogenic  and
natural sources  of IneZgases.  For  CO2, the
estimate' includes  only  the  anthropogenic
sources of CO2.  The model interpolates the
-values provided  by  the  emissions  modules,
which are provided for 12 time periods (in 5-
year increments  from  1985 to 2025, and in 25-
year increments thereafter),  to obtain annual
values  needed  for  the  annual  integration
performed in the atmospheric composition
model.

      The global lifetime,   defined  as the
global   content  of  the  species   in  the
atmosphere  divided  by  the global  losses,
represents  an  approximation  of   a   more
complex destruction process that depends on
variables that  differ  considerably  over the
globe.  The model addresses this uncertainty
in  the  estimates of the global lifetimes by
allowing  specification  of  ranges   for the
lifetimes.     Global  lifetimes   for  the
perhalogenated hydrocarbons (CFC13, CF2C12,
C^gClg, Ccl4, CF3Br, and CF2ClBr) assume
stratospheric loss only. Global lifetimes for
CH4, CH3CC13,  CHFC12, CH3C1, and CH3Br
assume  that  dominant   loss   is  in  the
troposphere by  reaction with OH, and  the
lifetimes have been set to be consistent with
models  for global  OH.   Stratospheric  losses
are also considered for CHF2C1 and for CH4.
Table A-21 summarizes the assumptions used
for the different long-lived  gases.

      The  annual  integration   for   global
content of the long-lived gases involves adding
the annual source and removing  the annual
losses associated with both stratospheric and
tropospheric   destruction.     Losses  from
stratospheric  destruction account  for the lag
in transport as  follows:

          Xt  = Xt4  + S, - X/TL,

            ' Xt-lag/SLt>

where Xt is the  global concentration in  year t,
St is the annual source, TLt is  the lifetime
associated with tropospheric sinks, SLt  is the
lifetime associated with  stratospheric  sinks,
and t-lag reflects the amount of time needed
for the increased concentrations to transport
to  the  stratosphere  and contribute to  the
stratospheric destruction. The model updates
the  global   lifetimes  annually  to   reflect
perturbations in column  ozone, stratospheric
transport, realized temperatures,  and OH
concentrations.

Measuring Changes in Climate

      Changes   in climate  are  measured
through  estimates of changes in  radiative
forcing at the top  of the troposphere due to
changes in greenhouse gases, modeling of heat
uptake  of the oceans, and estimates  of
changes in tropospheric temperature required
to restore radiative equilibrium at the  topxof
the troposphere.   In the model  we  have
assumed a climate  sensitivity of  2.0-4.0°C
although we have tested a range of sensitivity
from 1.5 to 5.5°C.

      The change  in radiative forcing  at the
top of the troposphere is instantaneous  and is
estimated  from   changes   in  atmospheric
concentrations of greenhouse gases from pre-
industrial levels.  The  change  in radiative
forcing  is based on calculations from a one-
dimensional  radiative   convective  model,
assuming  that  no climate feedbacks  occur
(Hansen et al., 1981; Ramanathan et al., 1985;
Hansen et al. 1988).  These yield an increase
                                            A-61

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Policy Options for Stabilizing Global Climate
                                       TABLE A-21

                     Global Lifetime Assumptions for Long-Lived Gases
Gas
                  Global
                 Lifetime
Assumptions
N2O
                 160 yr
CK,
                 9.6 yr
Perhalogenated Hydrocarbons
 CFC13
 CF2C12
 CC14
 CF2ClBr
 CF3Br
 CF4

Hydrohalocarbons

CH3CC13

CHF2C1

CH3C1
CH3Br
                  65 yr
                 140 yr
                  90 yr
                  50 yr
                  15 yr
                 110 yr
                 large
                  6.3 yr

                 15.5 yr

                  1.5 yr
                  1.6 yr
      destroyed   predominately   in   the   stratosphere.
      Reductions in upp-O3 lead to increased penetration of
      solar UV and to  shorter  lifetimes,  and vice versa.
      Increases in stratospheric mixing rates lead to higher
      concentrations in  the  photodissociation  region  and
      shorter lifetimes

      approximately  95%  destroyed  in  troposphere with
      reaction with OH.  The lifetime responds  immediately
      to changes in  OH and to  changes in realized warming
      like N2O
      like N2O
      like N2O
      like N2O
      like'N2O
      like N2O
loss over the next century is insignificant
loss dominated by reaction with tropospheric OH and lifetime
responds to changes in OH
like CH3CC13, lifetime for reference atmosphere based on
scaling of lifetime for  CH3CC13
same as above
same as above
                                           A-62

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                                                             Appendix A:  Model Descriptions
of  4.3  waus/meter2  at  the  top  of  the
troposphere for a doubling of CO2 or 1.26°C
in global surface air temperature.  Table A-22
summarizes the equations used to estimate
the changes in forcing for the different gases.

      Equilibrium surface temperature (for a
specified year)  represents  the  amount  of
warming expected to occur if the atmospheric
concentrations were to stabilize (at the levels
in that year) and the  global climate was
allowed to  reach equilibrium. For a doubling
of CO2, which would provide an increase of
1.26°C in the global surface air temperature
with  no   feedbacks,  the  increase    with
feedbacks is expected to range from 1.5-5.5°C.
For   each  scenario,   the   atmospheric
composition model is solved for two different
estimates of the feedbacks, one at 2.0°C and
one at 4.0°C, by using  different values of the
feedback parameter,  A.   The  relationship
between radiative forcing and warming is:

               F =  Q - AAT

where F is  the flux of heat into the ocean, Q
is the radiative forcing,  A  is  the  feedback
parameter,  and  AT is the global mean  surface
air  temperature which is  assumed to  be the
temperature of the mixed layer of the ocean.

      Changes  to  the  mean  tropospheric
temperature  represent the mean surface air
temperature and are used in the  model as a
surrogate for climate change.  This variable
depends on the equilibrium temperature and
heat uptake by the ocean and is calculated by
the box-diffusion model. The variable directly
affects tropospheric chemistry through  the
temperature dependence of kinetic rates and
abundance  of water vapor.

      Tropospheric water vapor abundance is
assumed  to  respond   instantaneously   to
changes in  tropospheric temperatures and to
maintain a constant distribution of relative
humidity.   Perturbations to water vapor are
calculated  relative  to  the  reference state
(1985) and are set  at  a  6.2% increase  per
degree centigrade near 25°C.   Tropospheric
water vapor affects tropospheric chemistry
directly in  the model.   The feedback  of
changes  in  tropospheric  water vapor  on
equilibrium temperatures is captured in  the
feedback coefficient, A.
The Stratosphere

      The  model  represents  stratospheric
ozone with two variables:  (1) col-O3 -- the
total stratospheric plus  tropospheric column,
and  (2) upp-O^  -  ozone  in  the  upper
atmosphere,  the  column  above   30  km.
Different processes control the state of each
of these variables and they also have different
impacts on  the lifetimes  of  the long-lived
gases.   Ozone is the  primary  source of
chemically reactive species in the atmosphere.
It competes for solar ultraviolet radiation that
destroys  many long-lived  gases  and  has  a
direct   radiative  effect   on  stratospheric
temperatures.  The approach in the  model is
aimed  solely at determining changes  in the
stratospheric loss rates of long-lived gases and
in  the  tropospheric  chemistry   that   is
controlled by the stratospheric ozone column
(i.e., OH).

      The model uses two variables,  str-C^
and  str-Brx,  to  represent total  inorganic
chlorine and bromine mixing ratios.   They
equal the sum of all chlorine and  bromine
atoms, respectively, contained in the  source
gases  list in Table A-19.   For chlorine, the
mixing ratio, measured in ppb, represents the
average mixing  ratios  at  40 km  over the
different latitudes  and seasons.   The mixing
ratio  for bromine  is measured  in  ppt  and
represents the average mixing ratios at  25 km
over the different latitudes and seasons.

      The model uses the variable str-NO to
represent the  levels of odd-nitrogen  in the
stratosphere.  It is initialized to the maximum
average  mixing  ratio  of about   18  ppb
presently occurring in the tropics between 30
and 40 km.  The model estimates changes in
odd  nitrogen  based  on  changes  in  the
abundance of N2O, applying a time lag  of 2.5
years to the  mean tropospheric concentration
of N2O.  Perturbations due to other sources,
such as tropospheric lightning, thermospheric
and  mesospheric  NO,  and  ionization  by
cosmic rays, are not included.

      The model currently does not estimate
changes in  the abundance of stratospheric
water or of  the rate of circulation in the
stratosphere.     The   model  does  allow
exogenous  specification  of changes in the
mixing ratio of stratospheric water (str-H2O)
                                           A-63

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Policy Options for Stabilizing Global Climate
                                        TABLE A-22

                               Models of Changes in Forcing
Gas
                      Reference
Units
Cone.
Equation for Net Radiative Forcing (w/m )
CO.
CR,
N20
CH4/N20
ppm




ppm

ppm
285




1.02

.2853
CFC13
CF2C12
CHF2C1
£2^3^13
CC14
CH3CC13
CH3C1
CF3Br
CF2ClBr
CH3Br
CF4
trop-O3
ppb
ppb
ppb
ppb
ppb
ppb
ppb
ppb
ppb
ppb
ppb
% change
0
0
0
0
0
0
0
•0
0
0
0

Fc-F2g5 where c is the concentration of CO2 &
Fc =' ln[l +  .942*c/(l+.00062*c) + .0088*c2+
3.26*10-6c3 + .156*c13*e-c/76°] * (4.3/1.26)

see below

see below

(g(x,y)-g(x0,y0)) * (4.3/1.26) where x and y are the
concentrations of CH4 and N2O and x0 and y0 are
the reference concentrations of these gases  and

g(x,y) = [0.394x0-66+0.16xe-1-6x]/[l+0.169x°'62]
+ 1.5561n[l +y°-77(109.8+3.5y)/(100+0.14y2)] '
                                                                              \1.52n
                                              -0.0141n[l+0.636(xy)u-/:>+0.007x(xy)

                                              0.23 *c (where c is concentration of gas)
                                              0.29*c
                                              0.10*c
                                              0.39*c
                                              0.17*c
                                              0.03*c

                                              0.34*c
                                              .01 (% change in tropospheric O3)
                                            A-64

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                                                            Appendix A: Model Descriptions
and changes in the rate of circulation in  the
stratosphere (circ).

Tropospheric Chemistry

      The primary focus of the tropospheric
chemistry component  of the  model  is   to
estimate changes in the global mean levels of
OH  and tropospheric O3.   These changes
then determine the oxidizing capacity of  the
troposphere and the global lifetimes of CH4,
CO, CH3CC13, and HCFC-22.  Prediction of
trends in global tropospheric models  is, at
present,   a   difficult   research   problem
complicated by a lack of knowledge about  the
global distribution of NOX; the estimates of
changes  in O3, therefore, must be assigned
large  uncertainties.

      The   model   simulates   the   two
hemispheres  separately  due  to  significant
asymmetries observed in many of the shorter-
lived  gases such as CO, NOX, and NMHCs,
which play a major role in the budgets of OH
and O3.  Averaging  even  over a hemisphere
may not adequately represent  the interactions
of highly variable species such as OH with  the
other trace gases.

      The model represents the perturbation,
from  the annual mean value for tropospheric
concentrations  of  OH, from the reference
state (e.g., 1985) with three variables: SH-OH,
NH-OH, and trop-OH. The variables SH-OH
and  NH-OH represent  the perturbations to
the  concentrations  in  the  southern  and
northern hemispheres, respectively, and trop-
OH   represents   (an   equally   weighted)
combination of these two  values:

   trop-OH  = 0.5*NH-OH + 0.5*SH-OH

      Perturbations  to  tropospheric  ozone
will   directly  affect radiative  forcing  and
indirectly affect the long-lived  source  gases
controlled by OH.  The model assumes that
the   sources   of   tropospheric   ozone
(tropospheric   chemical    reactions   and
stratospheric ozone) respond to atmospheric
.composition and that the loss frequencies
(photochemical and surface reactions) remain
constant.      Tropospheric   ozone   is
disaggregated into two hemispheres due to its
short life (a few months).
      The model uses variables that represent
 annual  mean  concentrations of CO  in each
 hemisphere   (NH-CO   and    SH-CO).
 Interhemispheric transport from the northern
 to the southern  hemisphere is modeled using
 a single coefficient and an exchange residence
 time of one year. Sources of CO include  the
 oxidization of CH4, which is proportional to
 OH levels,  oxidization of NMHC, which is
 proportional to  the annual  flux of NMHC,
 and direct emissions of CO.  Loss of CO is
 proportional  to   OH   levels   in  each
 hemisphere.

      Due to  the extremely short lifetime of
 NOX, from hours to weeks, and  to the wide
 variation of concentrations of NOX, over three
 orders of magnitude, the  model uses only  the
 emissions estimates of NOX and  does  not
 estimate concentrations. The model estimates
 the impact  of perturbations in NOX on  the
 formation of O3 directly from changes in  the
 emissions of NOX.  The  sources  of NOX  are
 disaggregated by hemisphere and the effective
 flux is represented in the model  as NH-NOX
 and SH-NOX.

      The model  estimates  the  impact  of
 NMHCs  on  tropospheric chemistry  in a
 manner similar to that used with NOX.   All
 impacts are based  on changes in the annual
•flux  of  NMHCs  (NH-NMHC  and  SH-
 NMHC).   The  difficulty of estimating  the
 impacts  of NMHCs is due to a number of
 factors, including the fact that the category
 NMHCs includes  a number of gases  (e.g.,
 Cy-^, Cy-Ig, isoprene, etc.) that have different
 concentrations and different reactivities with
 OH.

 Feedbacks

      The ASF allows the incorporation of a
 number  of  possible feedbacks from  climate
 warming.   These  can  include  increased
 stability  of the thermocline and  therefore
 reduced  uptake of CO2 from the ocean (see
 OCEAN  CIRCULATION  AND  UPTAKE
 MODULE below) and major changes in ocean
 circulation resulting in massive changes  in
 CO2 uptake and possible net fluxes from  the
 ocean.   The  model also allows changes  in
 emissions of greenhouse gases from natural
 sources as realized temperatures increase.
                                           A-65

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 Policy Options for Stabilizing Global Climate
 C02 Uptake by the Oceans

      Changes in ocean  chemistry, mixing,
 biology,  and  general  circulation  have  the
 potential   to   change   the   amount   of
 anthropogenic  emissions  taken up by  the
 oceans.  The  ASF captures these. feedbacks
 through a number of automatic and optional
•features   that  are  closely  tied  into  the
 atmospheric composition model.

      The model  addresses  feedbacks  on
 ocean  chemistry  by including in the  ocean
 model  equations  for   CO2  solubility and
 carbonate  chemistry (Lashof,  1989).   The
 model adjusts  the  partial  pressure of CO2
 between the sea surface and the atmosphere
 based on the temperature of the mixed layer.

      The  model   optionally   allows  the
 modeling of  reduced  CO2 uptake due  to
 increased stability of the thermocline.   When
 selected, the eddy  diffusion coefficients  are
 assumed to be inversely proportional  to  the
 square root of the temperature gradient at the
 top  of  the  thermocline.    (See  OCEAN
 CIRCULATION  AND   UPTAKE MODULE
 discussion  of  the thermocline and  the eddy
 diffusion coefficient.)

      The  model   optionally   allows  the
 investigation of the results of major changes
 in  ocean  biology  and  circulation.   This
 feedback is one of the reasons suggested for
 the  rapid  changes  in  CO2 concentrations
 during the glacial-intergjacial transitions. The
 feedback  is  modeled  by  setting  the eddy
 diffusion coefficient to zero  (or  near zero)
 when  the  realized  temperature  reaches  a
 certain level.

 Methane Emissions

      The literature  suggests  there   are  a
 number of feedbacks from increased tempera-
 tures that affect  emissions  of  CH4 from
 different  sources  by   increasing   rates   of
 microbial  activity  and emissions  of CH4
 hydrates from continental slope sediments.
 These  feedbacks  are modeled by increasing
 emissions as a linear function of increases.in
 realized temperature, allowing for time lags in
 the response.  The increased emissions  are
 included within the atmospheric composition
 model   and   affect  future   atmospheric
 chemistry,  composition,  and forcing.   The
following  categories  of emissions  include
feedback formulations:

•     methane emissions from rice paddies;

•     methane emissions from wetlands; and

•     releases of methane  hydrates  due to
      warming of the oceans.

CO2 Emissions

      Changes in the emissions of CO2 have
been proposed due  to increased fertilization
resulting  from  higher  atmospheric  CO2
concentrations and  from the disruption of
existing ecosystems,  resulting in reductions in
biomass and soil carbon. The procedure for
modeling increased CO2 fertilization is to tie
the increase in carbon stored in the terrestrial
biosphere linearly to increases in atmospheric
concentrations   of   CO2  (Lashof,   1989).
Annual net fluxes equal the change in carbon
stored.  The procedure for modeling increased
CO2  fluxes due to  disruption of existing
ecosystems is similar to the approach used for
CH4 emission feedbacks.  Increased emissions
of CO2 are specified as a linear function of
realized temperatures  where a time  lag is
allowed.

Vegetation Albedo

      The approach to modeling the feedback
of climate warming  to  changes in vegetation
albedo is to implement the  gain through the
climate   feedback   factor   (A,   units
watts/meter2/degrees  Kelvin), -see  OCEAN
CIRCULATION  AND  UPTAKE  MODULE
below). In order to implement a 1% increase
in  the planetary  albedo  with  a  climate
sensitivity of 3°C for a doubling of CO2, the
factor  A would  change from   1.43  (4.3
watts/meter2/3°C) to 1.20.

OCEAN CIRCULATION AND UPTAKE
MODULE

      The net flux of CO2 between the ocean
and  the atmosphere  and  the  role  of the
oceans in slowing  the rate  of  warming are
handled within a separate component of the
ASF  that  is  closely  integrated with  the
Atmospheric  Composition  Model.     The
approach utilizes a box-diffusion model  that
was developed at GISS (Hansen et al., 1984)
                                           A-66

-------
                                                             Appendix A:  Model Descriptions
and modified for use in the ASF.  Alternate
models  of CO2 uptake by  the  oceans were
implemented for use in the ASF, including an
alternative  box-diffusion   formulation,  an
advective  diffusive model, a 12-compartment
regional   model,  and an   outcrop-diffusion
model (Moore and  Ringo, 1988).

Integrated Box-Diffusion Model

      The integrated model of ocean heat and
CO2 uptake utilizes a box-diffusion approach
introduced by Oeschger et al. (1975).   In the
model the ocean is divided into a mixed layer
and a thermocline, which is further divided
into  nine  compartments (the  deep ocean  is
not  included in  the  formulation).    The
approach  to  modeling the diffusion of heat
and CO2 is similar, and the model addresses
the coupling  of climate and  CO2 uptake.

      For heat, diffusion into the mixed layer
is  a  function of  the  net forcing to  the sea
surface (F, units w/m2), the heat capacity of
the mixed layer  (He, units joules/[m3*K]),
amount of time the forcing is applied (t, units
seconds), and the depth of the mixed layer (4
units  meters) as follows:

        heat flux (K) = (t/Hc)*F/d

The  net forcing  (F) is a  function of the
increase in forcing over pre-industrial  levels
(Q, units w/m2), the increase in  temperature
of the mixed layer from pre-industrial  levels
(T, units K), and the feedback factor (A, units
w/[m2*K]), which converts forcing to long-run
temperature equilibrium, as  follows:

              F = Q - A*T.

      The   diffusion   of   heat   to   the
thermocline for the specified time period  is
accomplished by dividing the mixed layer and
thermocline into ten vertical  zones  (the  mixed
layer  is  the  top  zone) and estimating the
diffusion  of  heat between  adjacent  zones.
The rate of change in temperature (dT/ds) for
one of the zones (/) is a  function of the
diffusion from the zone above and diffusion
to  the zone below as follows:
       dT/ds = ed/L, * [Ofa-

               (vrv,+1)/DJ,
where ed  is  the  eddy diffusion  coefficient
(m2/s), v, is the temperature of the zone, L, is
the vertical incremental depth of the zone,
and £>[ is the difference between the middle of
zone / and the next deeper zone.  The model
approximates  the  diffusion  over  time  by
dividing the time steps into discrete intervals
and  solving a  set  of simultaneous  linear
equations that approximate the integration of
the change in temperature over  time.  The
value for the eddy diffusion coefficient for the
reference cases was 0.55* 10"4 m2/s and values
ranging from 2*10'5  to  2*10'4  m2/s were
examined.

      The  approaches  used  to  model  the
diffusion of CO2 to the mixed layer and the
thermocline are  similar to  the  approaches
used to model heat.  For diffusion from the
atmosphere to the mixed  layer,  the  flux is
dependent  on the  difference in  the  partial
pressure of CO2. The units for CO2 content
in the ocean mixed layer are moles/m3.  The
flux  of CO2  between  the  ocean  and  the.
atmosphere (Fc,  units moles/m3) is a function
of the atmospheric  concentrations (ate, units
ppm), the solubility of CO2 in sea water  (a,
units   moles/[m3*atm]),    the  current
concentration of CO2 in the mixed layer (cml,
units moles/m3), the piston velocity (pv, units
m/s), the elapsed time (t, units seconds), and
the depth of the mixed layer (d, unit meters):

    Fc = pv * t  * (a*atc*l(T6 - cml) / d.

In the formulation, the solubility of CO2 in
the mixed layer (a) is  calculated as a function
of temperature using the carbonate chemistry
equations  of Takahashi et al. (1980).  The
only differences  in  the approach (from  the
one used for heat) for modeling diffusion to
the  thermocline  are  that   the  operative
variable, vt, represents the CO2 concentration
in  moles/m3   and  the   eddy   diffusion
coefficients are different (ed = l.'7*W4 m2/s).

      The  start of the time horizon for  the
model is 1830, which allows 155 years  for the
model  to initialize  the  starting atmospheric
concentration and heat and carbon content of
the mixed layers and thermocline.  Estimates
of historic  fossil-fuel emissions are based  on
data  from  Rotty and Masters  (1985)  and
estimates of historic emissions from land-use
changes are   based  on  results   from  the
                                           A-67

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Policy Options for Stabilizing Global Climate
MBL/TCM (see LAND USE CHANGES AND
NATURAL EMISSIONS MODULE)  where
different historic estimates are used depending
on  assumptions  on  the  amount  of carbon
stored in the terrestrial biosphere. The model
is calibrated to historic CO2 concentrations
through  implementation  of an  "unknown
sink".   For each  year, prior  to 1985, the
estimated  atmospheric CO2  concentration is
compared  to  historical measurements.   The
unknown, sink  is  set  to  the  difference,
estimated  atmospheric concentration  minus
observed concentration, and  the atmospheric
concentration is reduced by that amount. The
unknown sink is generally assumed to remain
constant,  at   1985  levels,  in  the  future.
Alternatively, it can be specified to increase in
proportion   to    atmospheric   CO2
concentrations or decline over time.

      The model also allows modeling of a
feedback on the eddy diffusion coefficient due
to increased stability of the thermocline as the
temperature increases.  When specified, the
model  makes  the  eddy diffusion  coefficient
inversely proportional to the square root  of
the temperature gradient at the top of the
thermocline.

Alternative CO2/Ocean Uptake Models

      Four  alternative   models  of  ocean
uptake of CO2 were implemented in order  to
test the sensitivity of the CO2 concentrations
to different approaches and formulations. As
with the implemented version  of the  box-
diffusion model, an  unknown  sink  provides
the mechanism for calibrating  the results  of
the model to historic CO2 concentrations.
These models are not closely integrated with
the atmospheric concentration model and do
not   provide   feedbacks   on    realized
temperatures   and  atmospheric  chemistry.
Impacts  of   the  alternative  results  are
measured  only against warming commitment
                                                 and are based only on changes in atmospheric
                                                 concentrations of CO2.

                                                      The first of the models is an alternative
                                                 box-diffusion model. The differences between
                                                 this model and  the one described above is
                                                 that the mixed layer is only 75 meters (instead
                                                 of 110) and the model includes a deep ocean
                                                 component.  The  model captures  all of the
                                                 ocean  physics  with  an   eddy   diffusion
                                                 coefficient and  does not  explicitly capture
                                                 deep  water formation.  In  this  version, the
                                                 eddy  diffusion coefficient can vary with depth
                                                 based on calibration with steady-state carbon-
                                                 14 data.

                                                      The   advective-diffusive   model  is
                                                 structured to be  more realistic   than  the
                                                 simple  diffusive  assumptions  in   the  box-
                                                 diffusion  models.    The surface   ocean is
                                                 divided into cold and warm  components, and
                                                 water downwells directly from the cold  surface
                                                 compartment  into intermediate and  deep
                                                 layers.    The ocean physics are  captured
                                                 primarily  by an advective approach.

                                                      The 12-compartment  regional  model
                                                 divides  both the Atlantic  and  Pacific-India
                                                 oceans into surface, intermediate,  deep, and
                                                 bottom water compartments. The Arctic and
                                                 Antarctic  are divided into  surface and  deep
                                                 water compartments.  The model is calibrated
                                                 against  multiple  tracer distributions.   The
                                                 model  has   both   advective  and   eddy
                                                 diffusivities and a number of differences from
                                                 the other models as a result of  the different
                                                 geometrical configuration.

                                                      The outcrop-diffusion model  allows
                                                 direct ventilation  of the intermediate  and
                                                 deep  oceans at high latitudes by incorporatings
                                                 outcrops  for  the sublayers into   the  box-
                                                 diffusion formulation. This model is the most
                                                 efficient in taking up  CO2.
                                           A-68

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                                                            Appendix A:  Model Descriptions
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                                                           Appendix A:  Model Descriptions
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                                           A-72

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                                    APPENDIX B
                IMPLEMENTATION OF THE SCENARIOS
      This appendix describes in greater detail
the scenarios presented in  Chapter VI.   As
seen in Chapter VI, we have constructed six
scenarios of future patterns of  economic and
technological  development  starting  with
alternative  assumptions about  the rate of
economic growth and the adoption of policies
that influence climatic change (see Table B-
1).  These six scenarios cannot capture all the
possibilities, of course.  Rather, they allow us
to explore  likely climatic outcomes and the
impact  of  strategies   for  stabilizing  the
atmosphere. The sensitivity of the results to a
wide range of specific assumptions has been
tested and is discussed in Appendix C.  In this
appendix a  brief narrative description of each
scenario is  provided first. These  descriptions
are followed by a detailed discussion of the key
assumptions underlying the  scenario results.

DESCRIPTIVE OVERVIEW OF THE
SCENARIOS

      Two   scenarios   explore  alternative
pictures of how the world  may evolve in the
future  assuming that  policy choices allow
unimpeded growth in emissions  of greenhouse
gases  (these are  referred  to  as   the  "No
Response" scenarios).  One of these scenarios,
called  the Rapidly  Changing World (RCW),
assumes rapid economic growth and technical
change; the other, called the Slowly Changing
World (SCW), assumes more gradual change.
In other words we have invented  two futures:
one with relatively  high and robust  economic
growth and the other with a more pessimistic
view   of  the  evolution   of   the   world's
economies.   The  first  world  would likely
illustrate the upper half of the potential range
of future greenhouse gas emissions because, in
general, higher economic activity means higher
total energy use and emissions.  Conversely,
the second world could serve as a  useful guide
to the  lower half of the range. In either case,
our scenarios are first constructed as if there
were  no interventions motivated by  global
climate problems.

      In  constructing  these  two  worlds/
scenarios, we have borne two important ideas
in mind.  First, there  is evidence  that with
more rapid economic growth, energy efficiency
improves  more rapidly  than  with slower
growth (Schurr, 1982).  This occurs because
innovation proceeds more rapidly and because
older, less efficient systems are more rapidly
replaced with new technology. History shows,
for example, that for almost every country,
energy efficiency in  industry increases with
increasing incomes, as sophistication and scale
win  over  brute force.  At the same  time,
higher incomes allow  people to spend  more
money on two key energy-intensive uses, space
conditioning  (heating and  air  conditioning)
and  automobiles.    Thus,  not all  of the
technological  benefits of   rapid  economic
growth put the brakes on overall energy use.
But  more rapid economic growth allows
society to put resources aside to improve the
efficiency of both space comfort and personal
transportation.    Similar  patterns  can . be
expected  in other economic sectors.

      Conversely, slower  economic growth
retards  innovation, in  part  because  both
consumers and producers  do not see bright
economic times that  make innovation  and
expansion  into  new  technologies  useful.
Comfort and mobility still manage to increase
as  important  drivers  of  personal energy
demand, but at a slower rate. When these two
paths are compared, the effect of more rapid
efficiency increases in the higher growth world
is  to narrow the difference in greenhouse gas
emissions; that is, the likely difference between
emissions in the Rapidly and Slowly Changing
Worlds is less than the differences in Grosss
National  Product.  This  result makes  our
scenarios  somewhat more  robust than  one
might otherwise think.

      The second idea concerns energy prices.
In a  world of  high  and  robust economic
growth, which we have assumed in the Rapidly
Changing scenario, energy  demand will likely
increase,  and in the medium term,  so  will
energy prices.    Yet  if  energy  efficiency
increases, then energy costs can increase more
rapidly than the rate of economic growth and
still  not  consume  an increasing share  of
national wealth and income. In other words,
energy prices  can  rise without putting the
                                           B-l

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Policy Options for Stabilizing Global Climate
                                       TABLE B-l

                         Overview of Major Scenario Assumptions
            Slowly Changing World

              Slow GNP Growth
      Continued Rapid Population Growth
        Minimal Energy Price Increases
          Slow Technological Change
          Carbon-Intensive Fuel Mix
            Increasing Deforestation
      Montreal Protocol/Low Participation
      Rapidly Changing World

        Rapid GNP Growth
   Moderated Population Growth
   Modest Energy Price Increases
 Rapid Technological Improvements
  Very Carbon-Intensive Fuel Mix
      Moderate Deforestation
Montreal Protocol/High Participation
           Slowly Changing World
           with Stabilizing Policies

              Slow GNP Growth
      Continued Rapid Population Growth
      Minimal Energy Price Increases/Taxes
        Rapid Efficiency Improvements
      Moderate Solar/Biomass Penetration
             Rapid Reforestation
                CFC Phaseout
      Rapidly Changing World
      with Stabilizing Policies

        Rapid GNP Growth
   Moderated Population Growth
Modest Energy Price Increases/Taxes
Very Rapid Efficiency Improvements
  Rapid Solar/Biomass Penetration
        Rapid Reforestation
          CFC Phaseout
           Rapidly Changing World
          with Accelerated Emissions

             High CFC Emissions
                 Cheap Coal
                Cheap Synfuels
           High Oil and Gas Prices
         Slow Efficiency Improvements
              High Deforestation
               High-Cost Solar
              High-Cost Nuclear
      Rapidly Changing World
  with Rapid Emissions Reductions

           Carbon Fee
         High MPG Cars
     High Efficiency Buildings
    High Efficiency Powerplants
     High Biomass Penetration
        Rapid Reforestation
                                          B-2

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                                                 Appendix B: Implementation of the Scenarios
brakes on economic growth, as long as the
price increases are gradual (CONAES, 1980).
But in a world of sluggish economic growth,
energy demand  rises  more  slowly,  so  that
energy prices would  rise very  little.   This
relationship  is an additional reason why we
believe  that energy efficiency increases more
rapidly in the high-growth  scenarios (RCW)
than in the low-growth scenario (SCW).

      With these ideas in mind, we can build
scenarios of world energy demand by end use
and region as well as levels of other activities
that emit greenhouse gases.  The scenarios are
not exact predictions, but serve  as guides to
the level  of  emissions associated  with  each
important purpose or end use in the worlds we
constructed.

      This approach allows us to compare the
utilization efficiencies that we assume for the
No Response scenarios with those we believe
achievable if more than just market forces
were  acting.     Two  additional   scenarios
(referred  to  as  the   "Stabilizing  Policy"
scenarios) start with the  same economic and
demographic assumptions,  but examine the
effect that  policies could  have on global
warming.   These scenarios are called  the
Slowly  Changing  World   with  Stabilizing
Policies (SCWP), and  the Rapidly Changing
World with  Stabilizing Policies (RCWP).  In
addition, we add a variant of the RCWP case
called the Rapidly Changing World with Rapid
Emissions  Reductions  (RCWR);  for  this
scenario, we  assume more aggressive policies
to contend with global climate change than are
adopted  in  the  RCWP scenario.  A fourth
additional scenario considers the  effect  of
policy  choices  that  directly conflict  with
concerns  about  global  warming  and  that
therefore, would  accelerate emissions; this
scenario is called the Rapidly Changing World
with Accelerated Emissions (RCWA).   This
scenario is more pessimistic than  the RCW
scenario since policy choices increase the rate
of greenhouse gas buildup.

      Using  our  best  information about
technologies  that could become  available, or
technologies  that are already available but not
taken up by the market because  of market
failures  or other  reasons, we can reconstruct
activity  patterns that are still consistent with
our  overriding  economic  assumptions,  but
produce  much lower  (or  higher)  levels of
greenhouse gas emissions.   Key changes are
assumed in energy efficiency, the energy supply
mix, land-clearing rates, and other factors that
might be changed  by government policies or
other means.

      In  other  words, we keep  the  basic
scenarios  but,  for   example,   manipulate
important energy  use  patterns within  these
scenarios. These manipulations can only be
carried out if greenhouse gas emissions in each
scenario are constructed from the bottom up,
i.e., by specifying  the  level of each major-
emitting activity, as well as the emissions per
unit of activity (e.g., total harvested rice paddy
area and  methane emissions per square meter
of paddy).

      Thus, the scenarios we constructed are
a  necessary step  towards  illustrating  both
ranges of greenhouse gas emissions under two
quite  different assumptions about economic
growth, and where there is scope for reducing
emissions through a variety of strategies.  In
the final analysis, our  work can  be turned
around:   we  can consider the  levels of
emissions that under  the  best  and  worst
assumptions about how emissions are coupled
to climatic change leave the world's climate
tolerable.

Scenarios with Unimpeded Emissions Growth

      In  the SCW scenario, we consider the
possibility  that  the  recent experience  of
modest   economic  growth  will   continue
indefinitely, with no concerted policy response
to the risk of climatic change. In this scenario^
we assume   that   the  aggregate  level  of
economic activity  (as  measured  by  GNP)
increases relatively slowly on a global basis.
Per capita income is stagnant for some time in
Africa  and   the   Middle  East  as   rapid
population  growth  continues.     Modest
increases  in  per  capita  income  occur
elsewhere, and per capita growth rates increase
slightly over time in all developing countries as
population growth rates slowly  decline.  The
share of global income going to the developing
world   increases   with   time,   but   not
dramatically.   The  population engaged in
traditional agriculture and shifting cultivation
continues to  increase, as  do  demand for
fuelwood and speculative land clearing.  These
                                            B-3

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 Policy Options for Stabilizing Global Climate
factors lead to accelerated deforestation until
tropical forests are virtually eliminated toward
the middle of the next century.

      In  industrialized  countries  economic
growth is sluggish, although per capita income
reaches about $40,000 by 2100 in the OECD.
Because of slack demand, real energy prices
increase slowly.   Correspondingly, existing
capital stocks turn over slowly and production
efficiency  in agriculture and industry improve
at only a moderate rate. The energy efficiency
of buildings, vehicles, and consumer products
also improves at a slow rate.

      In the RCW scenario, we assume that
rapid economic growth and  structural change
occur and that little attention is given to the
global environment.  Per capita income rises
rapidly in  most regions and consumer demand
for  energy increases, putting upward pressure
on energy prices.  On the other hand, there is
a high  rate  of innovation  in industry, and
capital stocks turn over rapidly, which leads to
an  accelerated reduction in energy required
per unit of industrial output. An increasing
share of energy  is consumed  in the form of
electricity, produced mostly from coal.  The
fraction of global economic output produced
in the developing world increases dramatically
as post-industrial structural  change  continues
in the industrialized  world.  As  educational
and income  levels rise, population growth
declines  more rapidly  than in  the  SCW
scenario.   Deforestation continues at about
current rates, spurred by land speculation and
commercial logging, despite reduced rates of
population growth.  Energy efficiency is not
much of a  factor  in  consumer decisions, as
incomes increase faster than real energy prices.
Private vehicle ownership increases  rapidly in
developing countries while air travel increases
rapidly  in  wealthier ones.   Nonetheless,
significant reductions in energy intensity occur
with technological innovation and  structural
change.

Scenarios with Stabilizing Policies and
Accelerated Emissions

      Three variants of the above scenarios
explore the impact of policy choices aimed at
reducing the risk of global  warming.  These
scenarios,  labelled  Slowly  Changing  World
with  Stabilizing  Policies (SCWP), Rapidly
Changing  World  with  Stabilizing  Policies
(RCWP), and Rapidly Changing World with
Rapid Emissions Reductions (RCWR), start
with  the  same  economic  and  demographic
assumptions  used in  the  SCW and  RCW
scenarios,  respectively,  but   assume  that
government leadership is provided to ensure
that  limiting   greenhouse  gas  emissions
becomes  a   consideration  in  investment
decisions beginning in the 1990s. We assume
that policies  to  promote energy efficiency in
all  sectors succeed in substantially reducing
energy demand relative to  the  No Response
scenarios, and the efforts to expand the use of
natural gas increase its share of primary energy
supply relative to other fossil fuels in the near
term.  Research and  development into non-
fossil  energy   supply  options   such,  as
photovoltaics (solar cells) and biomass-derived
fuels  (fuels made from plant material) assure
that these options are available and begin to
become competitive after 2000.  In addition,
the RCWR case considers  the  imposition of
even  more aggressive policies  (compared to
the RCWP case) such as a  substantial carbon
fee and  rapid reforestation.    In  all three
scenarios, non-fossil energy, sources meet a
substantial fraction of total demand in later
periods.   The Montreal Protocol to reduce
CFC emissions is assumed to be strengthened,
leading to a phaseout  of  fully halogenated
compounds   and   a   freeze   on   methyl
chloroform.   A  global  effort  to reverse
deforestation transforms the biosphere from a
source to a sink for carbon, and technological
innovation and  controls reduce agricultural,
industrial,  and  transportation  emissions  of
greenhouse gases.
                                         x
      While  the general policy assumptions
apply to the SCWP, RCWP, and RCWR cases,
the degree and  speed  of  improvement  are
higher  in  the  Rapidly Changing  variants
because technological innovation and capital
stock replacement are greater in these cases.
In  the long  time frame  of  our analysis,
lifestyles will certainly change,  although  the
policies we consider do not restrict basic living
patterns. For example, energy use in buildings
is  greatly reduced in the  Stabilizing Policy
scenarios   relative  to  the  No  Response
scenarios, but the floor space  available per
person and the  amenity levels provided  are
assumed to be the same.   The technological
strategies  and  policy  options   available  to
                                            B-4

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                                                Appendix B:  Implementation of the Scenarios
achieve the Stabilizing  Policy scenarios  are
discussed in detail in Chapters V, VII, and
VIII.

      The  fourth  policy  case considers a
Rapidly Changing World with  Accelerated
Emissions  (RCWA).    In  this  scenario,
concerns over climate change are not only
ignored,  but  also  other policies  adopted
actually exacerbate the buildup of greenhouse
gas emissions.   For  example,  current U.S.
energy policy seeks to increase coal production
and use to reduce dependence on imported oil
and boost employment; the U.S. Department
of Energy  has made numerous suggestions
concerning various policies to increase the role
of coal in relative and absolute terms (U.S.
DOE,  1987;  National Coal  Council,  1987).
Furthermore,  recent  initiatives  in  utility
regulation  and  alternative  fuels may  also
increase  greenhouse  gas   emissions  (see
CHAPTER VII).

      Improving the efficiency of coal combus-
tion in so-called "clean coal" technologies may
reduce greenhouse gas emissions  relative  to
the current generation of coal-burning  plants.
Over  the long run, however, more efficient
coal-burning   technologies   may   increase
greenhouse  gas  emissions  by  making coal
economically attractive relative to other fuels.
(This  proposition is  tested in the modeling
analysis presented below.) Numerous policy
proposals  have also  been made to increase
U.S. coal  exports  in  order  to improve  the
balance of trade.  A  recent proposal by U.S.
DOE   coal advisory   committee  would  link
exports of  clean-coal  technology   to  an
agreement to purchase U.S. coal, a policy that
might  slow  the  adoption of more efficient
technology for burning less expensive domestic
coal in some developing countries like China
(National Coal Council, 1987).

      The need to consider more carefully the
potential impact of government decisions on
greenhouse warming  is evident from analyses
of two recent policies with ambiguous  impact
on  greenhouse warming.   The Alternative
Motor Fuels Act of 1988 (Public Law 100-494)
creates  incentives for auto manufacturers  to
produce  vehicles  powered  by  methanol,
ethanol, and substitutes for gasoline.  This
program was adopted to lessen dependence on
imported oil and to improve urban air quality.
However,   during   Congressional   debates
concern was expressed  that if methanol were
produced  in large quantities from coal,  the
result  would  be  a  significant  increase  in
greenhouse gas emissions.  Congress therefore
included  provision    for   study   of  this
relationship.     (The  potential  effect   of
accelerated synfuels development is discussed
in APPENDIX C.)

      Another example   of  a policy with
ambiguous, but potentially significant, effects
on greenhouse gas emissions is rule changes
proposed  by the  Federal  Energy Regulatory
Commission (FERC) to facilitate non-utility
power production. The draft  environmental
impact  statement (DEIS)  on  these  rules
concluded that coal-fired technologies have, so
far, played a limited  role  in the development
of independent  power projects relative  to
resource recovery, hydroelectric power, and
natural gas.   As a result  of the  FERC
proposals, coal could assume  a much larger
role   in  the   future  because  of  proposed
elimination of requirements  for cogeneration
incompatible  with the most economic coal
technologies and because larger firms with  the
resources  necessary to undertake large-scale
projects that increase the attractiveness of coal
technologies may find the power market more
attractive.   Alternative  assumptions imply
natural gas will grow much  more than coal,
however (FERC, 1988).

MACROECONOMIC ASSUMPTIONS FOR
THE ATMOSPHERIC STABILIZATION
FRAMEWORK

Population Growth Rates
                                         \
      This section presents the population
assumptions   used  in   the   Atmospheric
Stabilization  Framework.    The population
estimates  for  the  RCW  scenario  were
developed from Zachariah and Vu (1988) of
the World Bank; for the  SCW scenario,
estimates were based on  U.S.  Bureau of  the
Census (1987). These two  sources agree quite
closely on the size of the  world's population
through 2000,  then diverge thereafter due to
different assumptions on the rate at which  the
global population will stabilize. Discussions
with representatives of the U.S. Bureau of the
Census and the World Bank  indicated that
there  is  a very  high degree  of uncertainty
                                            B-5

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Policy Options for Stabilizing Global Climate
concerning  population  trends  in the  next
century due to differing expectations over the
rate at which current population growth rates
will  decline.1   Zachariah  and   Vu  (1988)
assume that  population growth rates  in
developing  countries  will begin  to  decline
markedly   after  2000,   achieving  a   net
reproduction rate of unity in every country by
2040.2 The U.S. Bureau of the Census (1987)
assumes that global population stability will
occur at a later date, with developing countries
experiencing rapid population growth rates
until  the middle of  the  next  century.  The
lower population estimates  from  Zachariah
and Vu (1988) were  used for the RCW to
represent  a more  rapid rate   of  change
consistent with this basic scenario, while the
higher population estimates from the  U.S.
Bureau of the Census (1987) were used for the
SCW to represent future rates  of growth that
are more consistent in the longer term  with
recent trends. These two population estimates
are summarized in Table B-2 for  each of the
nine regions in the Atmospheric Stabilization
Framework.

Economic Growth Rates

      The  primary source for the economic
growth rate estimates was the World Bank
(1987).    In  this report, Gross Domestic
Product (GDP) forecasts were provided for the
1986-1995 period for several different types of
country groups.   Most  countries could  be
classified into one of three general categories:
low income, middle income, or industrialized.
In addition, the World Bank defined several
other more select groups for which separate
growth rates  were estimated, including oil
exporters, exporters of manufactures, highly
indebted countries, and sub-Saharan Africa:

•     Oil Exporters, which included  Algeria,
Arab Republic of Egypt, Cameroon, Ecuador,
Gabon, Indonesia, Iraq,  Islamic  Republic of
Iran,   Mexico,   Nigeria,  Oman,  People's
Republic of the Congo, Syrian Arab Republic,
Trinidad and Tobago, and Venezuela.

•     Exporters   of  Manufactures,   which
included  Brazil, China, Hong Kong, Hungary,
India, Israel, Poland, Portugal,  Republic of
Korea, Romania, Singapore,  and  Yugoslavia.
•     Highly   Indebted   Countries,   which
included Argentina,  Bolivia,  Brazil,  Chile,
Colombia, Costa Rica, Ivory Coast, Ecuador,
Jamaica, Mexico,  Morocco,  Nigeria,  Peru,
Philippines,   Uruguay,  Venezuela,  and
Yugoslavia.

•     Sub-Saharan Africa, which included  all
countries south of the Sahara excluding South
Africa.

      For each of  these groups, the World
Bank  provided  a  range  of  GDP  growth
estimates from 1986-1995. The low estimates
were  used for this analysis  because these
estimates  were  more  in  line  with recent
historical trends and with other forecasts (e.g.,
projected growth from 1986-95 was 3.9% for
developing countries and 2.5% for  industrial
countries).  The GDP assumptions used by the
World  Bank for each of these  groups   is
indicated in Table B-3.

      Since these country groupings did not
match the  regional definitions  used in  the
Atmospheric Stabilization Framework, some
method was required to transform  the World
Bank's  estimates  to be consistent with  the
regions used in  the Atmospheric  Stabilization
Framework.  To  do  this, each  country was
assigned a  GDP  growth rate based on  the
average growth rates  provided in Table B-3.
Generally, if a country fell into one of the four
special categories discussed above (i.e., the last
four groups in Table B-3), the growth rate for
that group was used  for that  country.  If a
country  was  not  part of  one   of  these
groupings, the growth rate for that country's
general category  (i.e.,  low income,  middle
income, or industrialized) was assumed.

      In cases when a country fell into two or
more categories, e.g., oil exporter  and exporter
of manufactures, an  average of the two growth
rates was assumed. The only exception to this
rule occurred when  such averaging would
increase/decrease a country's GDP growth rate
in   a   direction   that  would   seem
counterintuitive.  For example,  if a country
were both sub-Saharan and highly indebted, a
simple average would  have assigned a growth
rate of 3.35%, which would have  increased its
rate of growth  above the rate of growth for
                                            B-6

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                                             Appendix B: Implementation of the Scenarios
                                      TABLE B-2

                         Global Population Estimates:  1985-2100

                                  (millions of people)
United States
OECD Western Europe
OECD Pacific
USSR/Eastern Europe
China/CP Asia
Middle East
Africa
Latin America
South/Southeast Asia

   TOTAL
1985

 239
 430
 144
 416
1140
 111
 570
 402
1417

4869
                                            Slowly Changing World

                                     2000     2025     2050      2075
 268
 462
 158
 457
1351
 181
 886
 577
1925

6265
 297
 482
 164
 514
1638
 359
1679
 787
2731

8651
  299
  466
  158
  533
 1762
  602
 2658
  967
 3359

10804
  296
  461
  159
  545
 1918
  738
 3600
 1129
 3958

12804
 2100

  296
  461
  160
  557
 1942
  781
 3963
 1169
 4166

13495
United States
OECD Western Europe
OECD Pacific
USSR/Eastern Europe
China/CP Asia
Middle East
Africa
Latin America
South/Southeast Asia

   TOTAL
1985

 239
 430
 144
 416
1140
 111
 570
 402
1417

4869
                                            Rapidly Changing World

                                     2000     2025     2050      2075
 262
 458
 158
 454
1408
 172
 871
 533
1859

6175
 285
 483
 166
 500
1727
 277
1498
 720
2534

8190
  280
  478
  165
  521
 1865
  359
 2026
  834
 2999

 9527
  278
  476
  164
  536
 1918
  399
 2336
  874
 3195

10176
 2100

  278
  479
  165
  545
 1932
  411
 2436
  893
 3281

10420
Sources:  U.S. Bureau of the Census (1987) for the Slowly Changing World; Zachariah and
       Vu (1988), for the Rapidly Changing World.
                                         B-7

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Policy Options for Stabilizing Global Climate




                                       Table B-3

                WORLD BANK GDP GROWTH ASSUMPTIONS: 1986-1995

                           (real average annual percent change)




   Country Group                                             GDP Growth Rate
   Low income countries                                             4.6%
   Middle income countries                                           3.6%
   Industrial countries                                                2.5%
   Oil exporters                                                     3.6%
   Exporters of manufactures                                          4.3%
   Highly indebted countries                                          3.5%
   Sub-Saharan Africa                                                3.2%
   Source: World Bank, 1987.
                                          B-8

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                                                Appendix B: Implementation of the Scenarios
other sub-Saharan  countries  because it  is
highly indebted.  Since this assumption seems
implausible, the lower of the  two rates was
assumed.

      Once a GDP growth rate was assigned
to each  country, this growth rate was applied
to the country's 1985 GDP level to determine
the resulting size of its economy in 1995.  The
resulting GDP estimates were then aggregated
according   to  the  nine  regions   in  the
Atmospheric  Stabilization  Framework   to
determine  the  magnitude  of  each  region's
GDP in 1995. This value was compared to the
1985  GDP  estimate  for   that  region   to
determine  the  average  annual real  rate  of
growth  in  GDP over the 1985-1995 period.
The only region for which the World Bank did
not have any estimates was  Eastern Europe/
USSR.  For  this region,  the  World  Bank's
assumption for  middle  income  economies
(3.6% per year) was assumed.

      For  the RCW (SCW) scenario these
initial   values   were  generally  increased
(decreased) by  one  percentage point  for
developing countries, Eastern Europe, and the
USSR   and one-half percentage  point  for
OECD  countries   to reflect  the  greater
uncertainty  regarding  future  growth   in
developing and centrally-planned  economies.
The  growth rates were applied  for the period
1985-2000, and were generally reduced by one-
half  percentage  point each 25-year period,
beginning in 2000, to reflect structural change
and  the decline in population growth rates
over time.   Nonetheless,  GDP  per capita
continues   to   increase   throughout  the
projection period, although the rate of growth
is substantially  lower in  the SCW scenario.
The   economic   growth  assumptions  are
summarized in Table B-4.

Oil Prices

      The oil prices used in this analysis were
taken from U.S. DOE (1988b), which supplied
a  range of oil  price forecasts.   The Middle
Price forecast from U.S. DOE was used for the
RCW scenario (by 2000 the world oil price is
about $32/barrel in  1988 dollars), while the
Low Price forecast was  used  for the SCW
scenario  (oil  prices  by  2000  were about
$26/barrel  in  1988  dollars).  Since U.S. DOE
price forecasts did not extend beyond 2000,  oil
prices were derived from the SUPPLY model
of the Atmospheric Stabilization Framework
(see APPENDIX A); in each scenario prices
escalated about 0.8% annually from 2000-2100.

ENERGY

Energy Demand

      The  energy  demand estimates were
developed using an end-use approach for each
of  the nine  regions  in  the  Atmospheric
Stabilization   Framework.    This  section
presents  the  major  assumptions  used  to
develop these estimates. Two reports provide
the basis for most of these assumptions:

•     Mintzer, I.   1988.   Projecting Future
Energy Demand in Industrialized Countries: An
End-Use  Oriented Approach,  draft,  World
Resources Institute.

•     Sathaye, Jayant A, Andrea N. Ketoff,
Leon J. Schipper, and Sharad M.  Lele, 1988.
An End-Use Approach to Development ofLong-
Term Energy Demand Scenarios for Developing
Countries, draft,  International Energy Studies
Group, Energy Analysis Program, Lawrence
Berkeley Laboratory.

      Mintzer  (1988)  was  used  for   the
industrialized countries, i.e., the U.S.; Canada
and  Western Europe; Japan, Australia, New
Zealand, and other Pacific Rim countries; and
the USSR and Eastern Europe.  Sathaye et al.
(1988) was used  for the developing countries,
i.e., China and other centrally-planned Asian
economies,  the  Middle  East, Africa,  Latin
America, and South and Southeast Asia.  Key
assumptions for determining energy demancL
within each region  for  each  of the major
energy-consuming  sectors  - transportation,
residential,   commercial,   industrial,  and
agriculture - are provided below.

Transportation

      Transportation energy use is expected to
increase over time as population increases and
incomes  rise,  affording  people  a greater
opportunity to purchase their own vehicles and
to use their leisure time to travel.  The types
of vehicles that people use for transportation,
the number of vehicles owned per capita, and
the  distance  travelled  will vary from one
                                            B-9

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Policy Options for Stabilizing Global Climate
                                    TABLE B-4

                              GDP Growth Assumptions

                          (real average annual percent change)
                                         Slowly Changing World

                              1985-2000  2000-2025  2025-2050  2050-2075  2075-2100
U.S.
OECD WESTERN EUROPE
OECD PACIFIC
USSR
CHINA
MIDDLE EAST
AFRICA
LATIN AMERICA
ASIA
2.0
2.0
2.5
2.6
3.5
3.3
3.0
2.7
3.3
1.5
1.5
1.5
2.1
3.0
2.8
2.6-
2.2
2.8
1.0
1.0
1.0
1.6
2.5
2.1
2.1
1.7
2.3
1.0
1.0
•1:0
1.6
2.5
2.1
2.1
1.7
2.3
1.0
1.0
1.0
1.6
2.5
2.1 '
2.1
1.7
2.3
                                         Rapidly Changing World
U.S:  '
OECD WESTERN EUROPE
OECD PACIFIC
USSR
CHINA
MIDDLE EAST
AFRICA
LATIN AMERICA
ASIA
3.0
3.0
3.5
4.6
5.5
4.1
4.5
4.7
'5.3
2.5
2.5
2.5
4.1
5.0
4.6
4.0
4.2
4.8
2.0
2.0
2.0
3.1
4.5
3.6
3.5
3.7
4.3
1.5
1.5
1.5
2.6
4.0
3.1
3.0
- 3.2
3.8
1.0
1.0
1.0
2.1
3.5
2.6
2.5
2.7
3.3
                                       B-10

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                                                 Appendix B: Implementation of the Scenarios
region to the next.  These behavioral factors
were  captured  explicitly in  each  region; key
assumptions on vehicle ownership and amount
of travel are defined in Table B-5. The rate at
which vehicles consume energy is also assumed
to change  over time; these assumptions  on
vehicle  energy  efficiency  for  cars  and  light
trucks are summarized in Table B-6.

Residential and  Commercial Sectors

            Energy use  in the residential and
commercial sectors varies  significantly  from
one region to another  due  to differences in
income levels, climate, extent of infrastructure
development, government policies, available
energy resources, among other  factors. Due to
the vast  differences in energy  usage patterns,
there  are  substantial  differences  in  the
approaches used to determine energy use in
the  industrialized  countries   compared  to
developing countries.   Key assumptions for
each are summarized below.

            For   industrialized   countries,
energy use in the commercial  and residential
sectors   was  modelled as   one  category.
Changes in the amount of energy used in these
sectors  depend  on  several factors, including
the rate of  new  construction, the rate of
retrofitting in existing  buildings, number of
people per household, amount of floor space
per capita, and changes in  energy efficiency
over time.  Key demographic  parameters are
summarized in Table B-7 for the  period from
1985  to 2025;  Table  B-8  summarizes  key
assumptions on energy intensity improvements
in the  residential/commercial sectors  from
1985 to 2025. In industrialized countries after
2025, the  annual rate of  improvement in
energy efficiency (energy/$ GNP) was assumed
to be 0.7-1.9% in the SCW, 0.9-1.9% in the
RCW, and 0.9-1.5%  in the RCWA; in the
Stabilizing Policies scenarios, the annual rate
of improvement in energy efficiency (energy/$
GNP) was assumed to be  0.9-1.9% in the
SCWP,  1.3-2.2% in the RCWP and  1.7-2.7%
in the RCWR.

            Patterns   of   energy   use  in
developing countries are quite different  from
those in industrialized countries  due to such
factors as current reliance on traditional fuels
(e.g.,   biomass),   different  , construction
techniques, and the early stage of development
for these sectors in many developing countries.
Due to reliance  on traditional  fuels in the
residential   sector   in   many   developing
countries, there are also significant differences
between the two  sectors.  Consequently, the
residential and commercial sectors are treated
separately.      Key  assumptions   for   the
residential   sector   through  2025   are
summarized in Table B-9; electricity intensity
assumptions for the commercial sector through
2025 are summarized in Table B-10.  For the
residential/commercial  sectors from  2025 to
2100, annual rates of efficiency improvement
(energy/$ GNP) in the  SCW were assumed to
be 0.3-1.1% and 0.6-1.4% in the RCW;  total
additional overall improvements of 35-55% in
the SCWP  and 35-45% in the RCWP  were
assumed over the period from 2025 to 2100.
For the RCWR case, the annual rate of energy
efficiency gains was increased by 0.6% relative
to the RCWP case over the period  2025 to
2100. The rates of efficiency improvement for
the RCWA case were assumed to occur only
half as rapidly as  in the RCW case; the  rates
were  therefore decreased to 0.2-0.8%  per
annum  for industrialized  countries and  0.3-
0.7% per annum for  developing  countries.
The lower rates of improvement are similar to
assumptions in recent  projections  for  U.S.
DOE's  National  Energy  Policy Plan  (U.S.
DOE 1988b).

Industrial and Agricultural Sectors

            The  amount and type of energy
use devoted to the industrial and agricultural
sectors  vary depending  on  the  stage  of
industrial development for each region, the
age of the capital  stock, the types of industrial
activities, types of commodities produced, etc.
For example, countries  that are just beginning
to industrialize often develop basic, energy-
intensive industries such as petrochemicals or
steel, while  post-industrialized countries are in
the process of reducing their dependence on
these  types  of  industries  as  information
services and other higher value-added activities
become increasingly important.

            For the industrialized countries,
changes in  per capita  consumption of basic
materials are summarized in Table B-ll (all
values are  relative  to  U.S.  consumption in
1985, which is set  to an indexed value of 1.00);
the overall  improvements in  energy efficiency
                                            B-ll

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Policy Options for Stabilizing Global Climate
                                      TABLE B-5



                  Assumptions on Vehicle Ownership and Amount of Travel
Region
Cars and
USA
W. Europe and Canada
OECD Pacific
USSR and E. Europe
Asia
China
Africa
Latin America
Middle East
2025
1985 RCW RCWP SCW
Light Trucks (No. owned/1000 people)
550 645 570 600
360 445 380 420
250 340 280 315
60 270 210 215
5.7 19.8 14 9.5
NA NA NA NA
12 40 38 20
56 214 171 132
43 137 110 75

SCWP

600
420
315
215
8.1
NA
18
120
70
Cars and Light Trucks (km driven/yr/vehicle)
USA
W. Europe and Canada
OECD Pacific
USSR and E. Europe
Asia
China
Africa
Latin America
Middle East
16,000 14,020 13,420 14,040
11,980 11,190 10,440 11,400
10,950 10,900 9,730 10,960
10,080 12,460 13,390 10,640
12,000 8,000 9,000 10,000
NA NA NA NA
18,000 13,714 11,885 15,542
15,000 12,000 12,600 13,200
18,000. 13,000 13,500 15,500
14,040
11,400
10,960
10,640
10,000
NA
14,628
13,200
14,000
Commercial Trucks and Buses (No, owned/1000 people)
USA
W. Europe and Canada
OECD Pacific
USSR and E. Europe
Commercial
USA
W. Europe and Canada
OECD Pacific
USSR and E. Europe
170 190 160 180
43 70 50 65
150 190 160 170
35 80 65 70
Trucks and Buses (km driven/yr/vehicle)
18,770 25,500 25,500 22,640
31,820 37,100 37,100 33,870
13,100 15,380 15,380 13,940
26,170 37,270 37,270 31,800
180
65
170
70

22,640
33,870
13,940
31,800
                                         B-12

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                                              Appendix B:  Implementation of the Scenarios
                                        TABLE B-6

                       Average Fuel Efficiency of Cars and Light Trucks

                                  (kilometers/liter/vehicle)
                                                                 2025
Region                                   1985  RCW  RCWP  SCW SCWP RCWA RCWR


USA                                       7     12      18      11     15     10      20
W. Europe and Canada                       8     11      18      11     15     10      20
OECD Pacific                               8     11      19      11     15     10      21
USSR and E. Europe                        6     10      16       9     13     9      17
Asia                                      10     16      21      13     14     14      22
China                                     NA    NA     NA     NA    NA    NA    NA
Africa                                      8     11      17      10     12     9      18
Latin America                               7     13      19      11     13     11      20
Middle East                                 7     13      17      11     13     11      18
                                         B-13

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Policy Options for Stabilizing Global Climate




                                         TABLE B-7

           Demographic Changes in the Residential Sector for Industrialized Countries1
MODE
Slowfy Changing World Scenarios2
People per Household - 1985
People per Household - 2025
Square Meter per Capita - 1985
Square Meter per Capita - 2025
Rapidly Changing World Scenarios2
People per Household - 1985
People per Household - 2025
Square Meter per Capita - 1985
Square Meter per Capita - 2025
United
States

2.7
2.6
73
78

2.6
2.4
73
109
OECD
Europe/
Canada

2.7
2.7
29
34

2.7
2.4
29
46
OECD
Pacific

3.6
3.5
25
32

3.6
3.0
25
38
Centrally-
Planned
Europe

3.9
3.8
15
24

3.9
3.5
14
28
1 Figures shown are population-weighted averages for the countries in each region.

2 Household size and household area are assumed to remain constant in the two Rapidly
Changing World cases and in the Slowly Changing World cases, respectively.

Sources:  Schipper et al., 1985; United Nations, 1986; Sagers and Tretyakova, 1987a.
                                           B-14

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                                      Appendix B: Implementation of the Scenarios
                                TABLE B-8

                Average Improvements in Energy Intensity in the
            Residential/Commercial Sector in Industrialized Countries
                               (1985 to 2025)
                                  Average Improvement      Average Improvement in
 Scenario                           in Fuel Intensity (%)      Electricity Intensity (%)
RCW
  United States                            39                       -4
  OECD-Europe/Canada                    27                        5
  OECD-Pacific                           27                        5
  Centrally-Planned Europe                 39                      -90

RCWP
  United States                            64                       36
  OECD-Europe/Canada                    62                       40
  OECD-Pacific                           62                       40
  Centrally-Planned Europe                 56                       59

SCW
  United States                            22                       -9
  OECD-Europe/Canada                    24                        5
  OECD-Pacific                           24                        0
  Centrally-Planned Europe                 15                      -73

SCWP
  United States                            35                        4
  OECD-Europe/Canada                    33                       25
  OECD-Pacific                           38                       20
  Centrally-Planned Europe                 44                       44
Sources:  IEA, 1987; Sagers and Tretyakova, 1987a; United Nations, 1987;
         Schipper and Ketoff, 1987.
                                  B-15

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Policy Options for Stabilizing Global Climate
                                              TABLE B-9

                               Key Assumptions in the Residential Sector of
                                 the Developing Countries Through 2025
Parameter
Household Size
(Persons/Household)




Electrification
(Percent of Households
with Electricity)



Biomass Energy Use
(GJ/Capita That Use Biomass
for Cooking and Water
Heating)


Efficiency of Biomass Use
(Percent)




Residential Electricity Use
(kwh/Electricity Capita)




Residential Fuel Use
(GJ/Capita That Use Fuel for
Cooking and Water Heating)



Space Heating
(GJ/Heated Capita)




Year/
Scenario
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
. SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
Centrally-
Planned
Asia
NA

NA
NA
NA
NA
35%

70%
82%
70%
82%
9

6
7
5
6
9%

15%
15%
17%
17%
69

190
227
166
170
3.0

3.0
2.5
3.0
2.5
7.8

6.3
5.1
5.6
3.9
Middle
East
6.0

5.0
4.5
5.0
4.5
65%

85%
95%
85%
95%
8

6
6
4
4
7%

10%
10%
14%
15%
297

412
632
365
474
3.1 .

3.0
5.6
3.0
4.2
NA

NA
NA
NA
NA
Africa
6.0

5.0
4.3
5.0
4.3
25%

40%
55%
40%
55%
10

6
7
5
6
6%

10%
12%
15%
16%
298

396
481
286
298
3.8

4.4
4.3
3.6
3.3
NA

NA
NA
NA
NA
Latin
America
4.5

3.8
3.4
3.8
3.4
78%

92%
98%
92%
98%
13

8
6
. 7
6
6%

10%
12%
12%
14%
308

413
684
359
469
4.4

3.9
5.0
3.9
4.4
NA

NA
NA
NA
NA
South
& East
Asia
5.9

5.4
4.9
5.4
4.9
35%

70%
82%
70%
82%
8

7
8
6
6
8%

12%
12%
16%
16%
136

153
245
134
184
3.0

3.0
2.5
3.0
2.5
12.8

12.2
9.5
11.2
8.0
Sources:  Lang, 1988; Leach, 1987; Bangladesh Statistical Yearbook, 1985; Mu, 1988;
        Trocki et al., 1985; Joshi, 1985.
                                               B-16

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                                              Appendix B: Implementation of the Scenarios
                                       TABLE B-10

                         Key Assumptions  in the Commercial Sector of
                           the Developing Countries Through 2025
2025
Region
Centrally-Planned Asia
Middle East
Africa
Latin America
South and East Asia
1985
NA
110
224
126
205
sew
NA
165
118
114
191
RCW
NA
187
135
101
226
SCWP
NA
143
108
95
178
RCWP
NA
131
80
76
181
Source:  Sathaye et al., 1988.
                                         B-17

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Policy Options for Stabilizing Global Climate
                                          TABLE B-ll

                Per Capita Production of Basic Materials in Industrialized Countries
                                   USA
                OECD
               Europe/
               Canada
             OECD
             Pacific
               Centrally-
               Planned
                Europe
Iron and Steel
               1985
         SCW-2025
         RCW-2025
        SCWP-2025
        RCWP-2025

Non-Ferrous Metal
               1985
         SCW-2025
         RCW-2025
        SCWP-2025
        RCWP-2025

Chemicals
               1985
         SCW-2025
         RCW-2025
        SCWP-2025
        RCWP-2025

Pulp and Paper
               1985
         SCW-2025
         RCW-2025
        SCWP-2025
        RCWP-2025

Stone. Cement, and Glass
               1985
         SCW-2025
         RCW-2025
        SCWP-2025
        RCWP-2025
1.00
1.05
0.76
1.00
0.71
1.00
0.95,
1.19
1.05
1.29
1.00
0.81
1.05
0.81
0.91
1.00
1.29
1.43
1.14
1.29
1.00
0.90
1.09
0.86
1.05
1.31
1.25
1.06
1.18
1.00
1.05
1.00
0.80
1.15
1.40
0.64
0.58
0.68
0.55
0.64
2.01
2.11
2.40
2.01
2.21
1.41
1.49
1.56
1.42
1.49
 2.49
 2.25
 2.01
 2.13
 1.90
 0.93
 0.89
 1.11
 1.02
 1.24
 0.60
 0.54
 0.63
 0.52
 0.60
 1.05
 1.10
.1.25
 1.05
 1.15
 1.77
 1.85
 1.94
 1.77
 1.85
1.62
1.47
1.31
1.31
1.16
0,65
0.75
0.83
0.77
0.90
0.19
0.22
0.24
0.21
0.21
1.11
1.91
2.17
1.64
1.91
1.44
1.30
1.35
1.23
1.30
Per capita production of each commodity is indexed to United States per capita production of
that commodity in 1985.

Source: Mintzer, 1988.
                                            B-18

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                                                Appendix B:  Implementation of the Scenarios
by 2025  are summarized for   the  major
energy-consuming  industries  in  Table B-12.
After 2025 the annual rate of improvement in
energy efficiency (energy/S GNP) was assumed
to range  from 0.3-1.1% in the SCW and 0.6-
1.4% in the RCW. In the Stabilizing Policies
scenarios, total additional improvements of 35-
55% in the SCWP and 35-45% in the RCWP
were assumed over the period from 2025  to
2100.

      For  the  developing  countries,   the
industrial and agricultural sectors were treated
separately through 2025.  The key  energy
parameters  for  the  industrial  sector  are
summarized in Table B-13 for each region and
each  scenario;  the  key  energy  intensity
parameters for the agricultural sector through
2025 are summarized in  Table B-14.  From
2025 to 2100, annual  rates of improvement in
energy intensity were assumed to range from
0.4-1.4% in the SCW and 0.9-2.3%  in  the
RCW in these  sectors.   In  the Stabilizing
Policies   scenarios,   total   additional
improvements of 35-45% were  assumed  to
occur in the SCWP and RCWP scenarios over
the period from 2025 to 2100.  In the RCWR
scenario, annual rates of efficiency  gains for
this sector were assumed  to increase by 0.6%
relative  to   the  RCWP  case,  for  both
industrialized and developing  countries.  The
efficiency gains for  the   RCWA case were
decreased to  half the values of those for  the
RCW scenario and, therefore, ranged from 0.3-
0.7% annually for industrialized countries and
0.4-1.1% annually for developing countries.

Energy Supply

      This section documents the amount of
energy resources available in each of the nine
regions through 2100, the cost of  producing
these resources, and the costs associated with
transporting  fossil  fuel  supplies.    The
combined  impact  of   these   assumptions
establishes the cost framework that determines
the delivered cost of energy to the end-user
and, therefore, the mix of fuels used.

Production Costs for Fossil Fuels

      This section documents the  fossil fuel
resource  estimates used  in the Atmospheric
Stabilization Framework.
      The initial source for the oil and natural
gas resource estimates was ICF (1982).  In this
report oil and natural gas resource estimates
were developed from several sources, and the
extraction  costs  for  these  resources  were
estimated in order to develop extraction cost
curves for these two fossil  fuels.  Since this
was the only readily available public source
that not  only identified the amount of each
resource  available, but also  the cost at which
the   resource   would  be   supplied,  the
information from this report was used in the
Atmospheric  Stabilization   Framework   to
represent oil  and natural  gas  availability
worldwide.  The production  costs for  these
resources were reduced by 0.5% per annum in
order  to  incorporate  assumed   technical
advances.

      The estimates of natural gas resources
in the  USSR   and  Eastern Europe  were
augmented  with   additional   information
contained in EIA  (1986a).  The adjustments
were made because the gas resource estimates
for these countries in ICF (1982) did not
reflect more recent information on the size of
the  resource   base  in   these  countries,
particularly the USSR.

      The  resource data presented in  ICF
(1982) were not disaggregated  by  the nine
regions    utilized   in  the  Atmospheric
Stabilization Framework.  For example, the
gas resource information was provided for the
U.S.,  Canada, Latin America (Mexico  and
Venezuela),  Africa,  Asia,  Middle   East,
Centrally-Planned Economies (CPE), and the
Rest of World (non-CPE).  For regions such
as the U.S., Latin America, Africa, and the
Middle East, the resource estimates were used
as indicated in ICF (1982). For other regions
various methods were employed to reallocate
the  data  according  to  the  Atmospheric
Stabilization   Framework  regions.     For
example, the CPE data was  proportioned
between two regions - E.Europe/USSR and
China/CPE — using each region's percentage
of each resource according to the country-by-
country resource estimates provided in WEC
(1980).  The data  for the Rest of the World
were  proportioned  among  the  remaining
regions - W.Europe/ Canada, OECD Pacific,
and S.  &  S.E.  Asia    —  using  a similar
approach. The natural gas resource estimates
                                           B-19

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Policy Options for Stabilizing Global Climate
                                         TABLE B-12

                     Energy Efficiency Improvement in the Industrial Sector

                         (% improvement by 2025 over 1985 intensities)


United
States
OECD
Europe/
Canada
OECD
Pacific
Centrally-
Planned
Europe
Iron and Steel




Non-Ferrous




Chemicals




sew
RCW
SCWP
RCWP
Metal
sew
RCW
SCWP
RCWP

sew
RCW
SCWP
RCWP
23
23
36
36

18
23
26
30

9
14
22
27
22
22
27
27

18
23
23
27

14
18
18
23
14
18
18
23

9
14
18
25

9
14
18
18
27
36
32
41

23
27
27
32

14
23
18
27
Pulp and Paper




Stone, Clay,




sew
RCW
SCWP
RCWP
and Glass
sew
RCW
SCWP
RCWP
18
18
32
37

18
31
36
54
6
15
14
23

18
28
32
36
14
23
18
27

9
26
18
31
31
39
35
46

18
27
23
41
Projected improvements in efficiency of industrial production assume that only technologies
available commercially today or now in prototype testing will be used between 1985 and 2025.
Estimates of future efficiency improvement vary among scenarios as a function of the assumed
rates of stock turnover and penetration of these new technologies.  Policies are assumed to
accelerate turnover rate of capital stock and thus to improve average efficiency.

Sources: Goldemberg et al., 1987; Leach et al., 1986; Kahane, 1985; IEA, 1987; Sagers and
        Tretyakova, 1987a, 1987b.
                                           B-20

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                    Appendix B: Implementation of the Scenarios
              TABLE B-13

Key Assumptions in the Industrial Sector of
  the Developing Countries Through 2025
Parameter
Industrial Value Added/GDP
(Percent Share)



Fuel Intensity
(TJ/Million Dollars)



Electricity Intensity
(MWh/Million Dollars)



Year/
Scenario
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
1985
2025
sew
RCW
SCWP
RCWP
Centrally-
Planned
Asia
42%
40
40
40
40
59
48
34
43
28
2160
2160
2242
1944
1906
Middle
East
49%
45
50
45
50
13
11
9
10
8
582
611
640
611
611
Africa
38%
33
39
33
39
11
10
11
9
8
790
883
916
818
798
Latin
America
29%
32
38
32
38
26
23
16
19
14
1163
1163
1163
1047
930
South
&East
Asia
32%
35
40
35
40
25
20
18
14
12
955
955
991
860
843
                B-21

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Policy Options for Stabilizing Global Climate
                                       TABLE B-14

                         Key Assumptions in the Agricultural Sector of
                           the Developing Countries Through 2025

Parameter
Year/
Scenario
Centrally-
Planned
Asia
Middle
East Africa
Latin
America
South
& East
Asia
Electric Intensity
(kWh/$1000 Value Added)
Fuel Intensity
(TJ/Million Dollars)
1985
2025
sew
RCW
SCWP
RCWP

1985
2025
sew
RCW
SCWP
RCWP
NA

NA
NA
NA
NA

NA

NA
NA
NA
NA
 58

116
157
113
110

 90

135
180
126
126
23

57
85
52
68

18

35
45
30
35
170

204
238
187
204

 80

 64
 56
 56
 48
202

234
271
222
244

 50

 59
 68
 56
 61
                                         B-22

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                                                 Appendix B: Implementation of the Scenarios
resulting from this approach are provided in
Table  B-15   according  to  the  minimum
extraction cost at which these resources could
be economically produced.3

      A  similar approach was employed for
the oil  resource  curves.   In  ICF  (1982)
resource  estimates were provided for the U.S.,
Canada,   Latin   America   (Mexico   and
Venezuela), Middle East, and the rest of the
world (non-centrally planned economies only).
The U.S., Latin America, and the Middle East
resource  estimates were used as indicated in
ICF (1982).  The resource estimates  for the
rest of the world were proportioned among the
remaining  non-CPE  regions  --  W.Europe/
Canada,  OECD Pacific, S.  & S.E. Asia,  and
Africa using the  same  procedure outlined
above for the gas resource curves.  Data for
centrally-planned economies were not available
from  ICF  (1982),  and the  Africa estimates
were  incomplete.   For these  regions  the
resource  estimates provided in WEC (1980)
were  used.   The oil extraction cost curves
resulting from this approach are provided in
Table B-16 by minimum extraction cost.

      The coal resource estimates were taken
from  WEC (1980).   This  report contained
country-by-country  estimates of indigenous
coal resources, which were developed at the
World Energy  Conference  from information
supplied   by  experts  familiar   with  each
country's resources.    The coal  resource
estimates resulting from this approach  are
provided in Table B-17 by minimum extraction
cost.  The extraction costs were based on the
costs   originally   documented   for   The
IEA/ORAU Long-Term  Global  Energy-CO2
Model (Edmonds and Reilly, 1986).

Gas Flaring Rates

      During the production of oil  and gas
resources some portion of natural gas is either
vented or  flared rather than produced for
commercial use.  The  amount of gas that is
not recovered was  determined  from  EIA
(1986a).   This source provided  country-by-
cduntry estimates of the amount of natural gas
that was  vented or flared in 1984. The total
amount of natural gas vented or flared in each
of the nine regions was determined, and  this
value  was converted to a percentage of total
natural gas production in that region.  This
percentage was assumed to be the amount of
natural gas that was initially flared or vented.

      Over time the value of natural gas will
increase   and  the   market  infrastructure,
including the distribution systems, will become
more highly developed in many regions.  As a
result, we assumed that the amount of venting
or flaring would decrease over time  to a level
equal to the amount of flaring in the U.S.
currently,   i.e.,  0.5% of gross  natural gas
production.4  The rate of decrease was varied
depending  on the  amount  of venting and/or
flaring  occurring   currently,  with  regions
currently  venting   and/or  flaring  a  larger
amount of natural gas assumed to take  a
longer time to achieve the 0.5% level.   For
example, in the Middle East and Africa where
total venting and flaring is over 15%, it was
assumed to take 50 years  to  reach 0.5% of
total production.  For most other regions this
value was assumed to be 10-20 years.

Refinery Efficiencies and Costs

      The  cost of refining is  partially tied to
the  price  of  oil  since about one-third of
refining costs are fuel-related. This cost per
barrel, based on ICF (1984), can be expressed
as:

      $3.63 + Fuel Cost (all costs are in 1988
      dollars)

where Fuel Cost is defined as 0.083 barrels of
residual fuel oil  per  barrel  of  Saudi  light
crude, or about 521,000 Btu of fuel consumed
for each barrel refined (this fuel cost  varies
based on  the  acquisition cost of crude and
resulting residual oil costs).

      From U.S. DOE sources  cited above,
residual oil prices are about 0.95  the price of
crude oil.   Assuming a crude oil price of $20
per barrel  ($0.48 per  gallon)  in 1988 dollars,
the price for residual oil would  be $19 per
barrel ($0.45 per gallon).   The refining cost
equation above becomes:

      $3.63 + [0.083 barrels * 0.95 * $ per
      barrel of crude] = $5.21 per barrel

Each barrel of crude is assumed to contain 5.8
million Btu, or 6.119 gigajoules.  At a cost of
                                            B-23

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Policy Options for Stabilizing Global Climate
                                        TABLE B-15



                       Minimum Extraction Cost Curves For Natural Gas



                                      (1988 $/gigajoule)
Region
 1.02
   TOTAL
2112
3.38
5.58
 7.78
15.64
United States
Western OECD
Eastern OECD
USSR & E. Europe
C-Planned Asia
Middle East
Africa
Latin America
S and E Asia
340
200
14
1000
10
388
40
60
60
594
433
66
2286
276
1401
347
560
154
910
746
111
2583
334
1936
531
673
261
1071
944
129
2711
359
2171
657
718
304
1307
1109
147
2807
377
2315
761
779
348
6117
8085
9064
9950
Sources:  ICF, 1982; EIA, 1986a; WEC, 1980.
                                          B-24

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                                              Appendix B: Implementation of the Scenarios
                                       TABLE B-16

                           Minimum Extraction Cost Curves for Oil
                                     (1988 $/gigajoule)
Region
 2.80
3.00
3.46
4.60
5.76
8.06
10.70
United States
Western OECD
Eastern OECD
USSR & E. Europe
C-Planned Asia
Middle East
Africa
Latin America
S and E Asia
173
201
10
384
112
2928
346
514
105
443
351
12
1225
458
4413
967
539
189
532
461
16
1336
499
4571
.1257
608
246
621
610
19
1440
538
4666
1499
712
293
710
779
23
1710
639
4855
1837
1074
359
1291
881
31
1851
669
5406
2137
3858
439
13276
892
53
2161
915
5760
2546
3863
639
   TOTAL
4773     8597    9526    10398    11986    16563    30105
Sources: ICF, 1982; WEC, 1980.
                                       TABLE B-17
                          Minimum Extraction Cost Curves For Coal
                                     (1988 $/gigajoule)
        Region
         0.70
         0.80
         1.60
         3.20
          TOTAL
         5.40
United States
Western OECD
Eastern OECD
USSR & E. Europe
C-Planned Asia
Middle East
Africa
Latin America
S and E Asia
600
300
120
750
600
1
120
18
180
7964
2459
1891
13536
4054
2
607
121
365
17727
5474
4209
30128
9024
4
1352
269
812
31601
9758
7503
53706
16086
7
2410
480
1447
50613
15629
12018
86017
25764
11
3860
769
2318
         2689   30999    68999   122998   196999
Sources:  WEC, 1980; Edmonds and Reilly, 1986.
                                         B-25

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Policy Options for Stabilizing Global Climate
$5.21 per barrel, the cost of refining crude oil
is $0.85 per gigajoule (1988 dollars).

Hydroelectric Resources

      The  amount  of hydroelectric  power
available  for  development  was  based  on
.estimates  of  the   technical  potential  for
hydropower as presented in WRI (1987).  In
this  report the total amount of hydroelectric
power available in the world was estimated by
country.   These  estimates  were  used  to
establish the  total  amount of hydroelectric
power technically available in each region.

      Within  the Atmospheric  Stabilization
Framework the total amount of this technical
potential that  could be utilized was arbitrarily
limited to  75% of  each  country's technical
potential.     The   reason  for   limiting
hydroelectric  development is based  on  the
argument   that   various   environmental,
economic,, social,  and  political factors will
preclude the development of all hydroelectric
potential.  The realistic level of development
in each country cannot be estimated.  The
75% restriction is arbitrary, but  seems like a
.reasonable  upper    bound  estimate  when
            compared to the U. S. situation.  For example,
            based on information obtained from the U. S.
            Department of the Interior, the United States
            has currently  developed about  50% of its
            hydroelectric potential.    Some  additional
            development in the future is  likely, although
            certain  hydroelectric sites  will  undoubtedly
            never be developed.

                  The rate of hydroelectric development
            allowed  in  the  Atmospheric   Stabilization
            Framework was limited in order  to avoid the
            addition of  an  unreasonable  amount  of
            hydroelectric power within a  very short time
            frame. The allowed rate of development was
            limited to the historical rate of development of
            these   resources  within  each   country,  as
            determined  from WRI  (1987)  and  EIA
            (1986a).  Table B-18   presents  the   1985
            hydroelectric  production  levels  and   the
            technically   feasible  resource  amounts by
            region.   (See  APPENDIX  A  for further
            discussion.)

            Solar Energy Costs

                .  The cost of renewable resources depends
            on many factors, including the current costs of
                                           Table B-18

                                     Hydroelectric Resources

                                  (exajoules delivered electricity)
            Region
1985 Production
            TOTAL
    7.03
    Technical Potential
75%   •          100%
United States
Western OECD
Eastern OECD
USSR & E. Europe
C-Planned Asia
Middle East
Africa
Latin America
S. & E. Asia
1.11
2.75
0.40
0.80
0.32
0.03
0.07
1.09
0.46
1.6
' 3,7
0.6
1.2
3.9
0.2 :
2.4
6.9
4.2
2.1
4.9
0.8
1.6*
5.2
0.3
3.2.
9.2
5.6
24.7
32.9
                                            15-26

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                                                Appendix B:  Implementation of the Scenarios
production,   the  level  to  which  these
production costs will fall as the  technologies
mature, and the rate  at  which commercial
penetration  occurs.   These  factors can  be
varied within  the  Atmospheric  Stabilization
Framework.   To  determine the basic cost
inputs for solar energy resources, information
was obtained from the Solar Energy Research
Institute (SERI) based  on industry data and
U.S.  DOE  technology development  goals.
SERI  indicated  that  the  current  cost  of
electricity from renewables is  about  $0.10-
0.11/kwh (in 1988 dollars, based  primarily  on
the cost of wind generating systems and  recent
solar    thermal  demonstration   projects).
Without a  significant  emphasis on further
research and development, however, this cost
is estimated  to decline only to about $0.08/kwh
in the long run in the No Response scenarios
as  solar  technologies  mature.    In  the
Stabilizing Policies scenarios, the costs decline
to about $0.06/kwh by the year 2030, which is
the level consistent with  the cost objectives
U.S.  DOE  has set for  its solar research
program.  Solar power was assumed to  play a
small role in  the  RCWA case.  The  costs,
therefore, reflect those  of the No Response
scenarios.   The solar  energy costs for  the
RCWR case were assumed to be similar to the
Stabilizing  Policies  scenarios,   declining  to
about S0.06/kwh by 2030.

Nuclear Power Costs

      Nuclear fission is  a technology which is
currently  widely  used  and  growing  in  its
contribution to global  energy supply due  to
completion of powerplants ordered during the
1970s.   However,  high  capital costs and
concerns  about  safety,   nuclear  weapons
proliferation and radioactive waste disposal
have  brought  new orders to a  halt in most
countries. It is technically feasible to expand
the contribution of this energy source beyond
current projections  if  these  problems  are
resolved, and  steps have been taken to deal
with some of  the constraints on the nuclear
power  industry (for  example,  U.S.  DOE
programs  aimed  at  developing   improved
reactor designs).

      The costs associated with nuclear energy
in  the  No  Response  and Policy  scenarios
reflect  these  characteristics  of  the nuclear
industry.  Costs start at 6.1 cents per kwh in
1985 and rise to 7.6 cents per kwh by 2050 for
the  RCW,   SCW  and  RCWA  scenarios,
indicating the constraints faced by the industry.
Costs for the RCWP, SCWP, and  RCWR
scenarios start  at  6.1 cents per kwh in  1985
and decline  to 5.5 cents  per kwh  under the
assumption that the policy programs targeting
the industry's problems are successful.

Biomass Energy Costs and Availability

      The availability and cost of biomass for
commercial energy applications were based on
U.S. DOE (1988a).  There is a substantial
amount of  land  worldwide that  could be
dedicated  to biomass development projects.
For purposes of this analysis, the U.S. DOE
assumed   that  10%  of  total  forest  and
woodland area plus 10% of total cropland area
would  technically  be available for biomass
energy development.    Based on  different
assumptions on the rate of improvement  in
productivity,  energy yields per hectare were
assumed to increase up to about three times
current  levels.  Table B-19 summarizes  the
amount of energy  potentially available from
biomass   under   different   productivity
assumptions, with scenario A assuming a  65%
improvement in  current energy plantation
productivity  estimates, scenario B assuming a
150% improvement, and scenario C assuming
an  improvement  of  over 500%  (a  level
potentially achievable  by 2050).   Although
these  estimates indicate  that about  675 EJ
annually could potentially be developed from
biomass   with   sufficient  research   and
development and commitment of land area, in
all  except one of our  scenarios  the  total
amount of additional energy from biomass was
limited to about 275 EJ (less than the amount
available under scenario  A after subtracting
current levels of biomass consumption). It was
assumed for the RCWR scenario that twice
this amount, or 540  EJ, was available  (an
estimate consistent with  the potential under
scenario B).

      Based on  cost and performance  data
provided in  U.S. DOE (1988a),   the energy
conversion efficiency  for solid  biomass  to
gaseous or liquid fuels was assumed to be  75%
after  2010.   With sufficient  research  and
development, the average  cost of gaseous fuels
from biomass after 2010 was assumed to be
about S4.35/GJ in 1988 dollars on a well-head
                                            B-27

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Policy Options for Stabilizing Global Climate
                                                                    TABLE B-19

                                                   Future World Wide Biomass Energy Potential
Region
World
Africa
U.S./Canada
C. America
S. America
Asia
Europe
USSR
Oceania
Total Land
Area
(10*113)
13081
2966
1839
300
1753
2679
473 '
2227
843
Cropland
(10*ha)
1472
183
236
38
139.
455
140
232
48
Forest &
Woodlands
(lO^ha)
4091
703
591
69
927
• 558
155
928
159
Energy
Plantations1
(106ha)
556
88
83
11
107
101
29
116
21
%Land
Area (Energy
Plantations1
Total Land
Area
4.3%
3.0
4.5
3.7
6.1
3.8
6.1
5.2
2.5
Energy Production
From Biomass (E3)
Potential
1988
50
12.6
3.4
1.2
6.6
21.5
1.7
2.5
0.2
A
338
69
33
8
83
79
12
45
8
B
506
103
49
13
126
118
17
69
13
Cl
675
137
65
17
167
158
23
91
17
1 Assumed area of biomass energy plantations = 10% of total forest & woodland area plus 10% of cropland area.

2 1988 data is estimated actual use; scenarios A, B, and C use the following biomass productivity values (assuming all of the potential energy plantation
hectares shown above are used at these intensive cultivation productivity levels); current energy plantation production/year for the U.S./Canada, Europe,
USSR, & Oceania =  14.8 dry tons/heetare/year _(dt/ha/yr) (7.4 dt/ha/yr in conventional forests); with R&D, assumed energy plantation productivity for
these temperature climate countries are;  scenario A  = 24.7 dt/ha/yr, scenario B = 37.1 dt/ha/yr, scenario C = 49.4 dt/ha/yr,  for Africa, C. & S. America,
and Asia current productivity = approx. 29.7 dt/ha/yr, scenario A assumes 49.4 dt/ha/yr, scenario B = 74.1 dt/ha/^r, and scenario C = 98.8 dt/ha/yr for the
tropical regions.
                                      f
Source : U.S. DOE, 1988a.
                                                                         B-28

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                                                    Appendix B:  Implementation of the Scenarios
equivalent basis; the cost of liquid  fuel (i.e.,
gasoline) after 2010 from biomass was assumed
to be about S6.00/GJ on a refinery gate basis.5
These  values were  used in the SCWP  and
RCWP scenarios.   As   a  result,  biomass
contributes  about 250  EJ  by 2100  in  the
SCWP (about 48% of total primary energy)
and 275 EJ in the RCWP by 2100 (about 32%
of total primary energy).   It  was assumed for
the RCWR scenario that the fixed cost of
converting biomass  to fuel was reduced by a
third of the above values; this resulted in a
biomass contribution of about 470 EJ by 2100.
In the  SCW, RCW, and  RCWA scenarios, it
was  assumed  that  a lack of  research  and
development into biomass energy  potential
and an unwillingness/inability to commit land
for biomass development prevented biomass
from competing with more traditional fuels to
a greater extent.  Nevertheless, biomass  still
makes  some contribution (about 50 EJ in the
SCW and 70 EJ in the RCW and RCWA by
2100, which is 7%, 5%, and 3%, respectively of
total primary energy in the SCW, RCW, and
RCWA scenarios).

Synthetic Fuel Costs

      There   are  several   synthetic   fuel
technologies  that  were included  in  the
Atmospheric    Stabilization    Framework,
including coal gasification and liquefaction, oil
shale development, and tar sands development.
To determine the costs at which energy could
be  supplied  from  these technologies,  two
sources were used:

•     Technical Assessment Guide:  Volume I
- Electricity Supply, Electric Power Research
Institute, 1986.

•     Synthetic  Fuels Report, Pace Engineers,
December 1987.

      The key synthetic fuel technologies and
their associated costs are summarized in Table
B-20. The conversion efficiencies of synthetic
fuel development technologies were based on
Radian (1990), and averaged  about 65%.
These  values were used for  all the scenarios
with one exception; in order to represent the
accelerated development  of synthetic fuels in
the RCWA case, the fixed costs of conversion
were decreased by 50% of their original values.
Transportation Costs in the Atmospheric
Stabilization Framework

      In addition to the costs  of producing
energy,  the   Atmospheric   Stabilization
Framework  contains interregional costs for
transporting   fossil  fuels.    This  section
documents the transportation cost assumptions
made for each fossil fuel in the Atmospheric
Stabilization Framework.

      Oil.  The oil transportation costs  were
developed from ICF  (1979), which estimated
long-term, full cost pricing for oil transporta-
tion.  Actual estimates of transportation  rates
were  not  used because  the  world shipping
markets have  been quite depressed due to
excess shipping capacity.  This  situation has
caused shipping rates in recent years to decline
toward short-term variable costs.  Since the
Atmospheric Stabilization Framework should
reflect long-term, full cost pricing by shippers,
current rate estimates would be inappropriate.
ICF (1979) was designed to reflect transporta-
tion rates in an equilibrium market, i.e., long-
term pricing, including an adequate return on
capital.   Based  on  this  information, oil
transportation costs  were derived from the
following formula:

      Transportation = 0.022 * Price of Crude
         Cost      +  [0.28 per 1000
                    nautical miles]

This equation  is in 1988 dollars, and  assumes
a 120,000 DWT tanker  (a size typically  used
for many  international  shipments, although
not supertanker size). The mileage estimate is
based on the distance one-way fully loaded; the
transportation cost function, however,  includes
the cost of the return trip.

      The   Atmospheric  Stabilization
Framework currently operates with only one
transportation rate assumption for oil.   To
estimate a single rate using the above formula,
a crude price of $20 and a "typical" shipment
from the Middle East to the United States (a
distance of about  12,200 miles) was assumed.
Therefore, the oil transportation costs  between
the Middle East  and  the  U.S. would be
S3.86/barrel in 1988  dollars, or  $0.63  per
gigajoule  (assuming  an energy  content  of
about 6.1 gigajoules per barrel).
                                              B-29

-------
Policy Options for Stabilizing Global Climate
                                          TABLE B-20

                               Cost of Synthetic Fuel Technologies
Technology
Tar Sands3
Oil Shale3
Coal Gasification
Commercially Demonstrated
High Btu Gas «<;
Medium Btu Gas
Facility
Size
50,000b
50,000b

250C
250C
Capital Cost
(1988 S/kw-yr)
2,350
2,800

2,730
2,330
O & M
(1988$/kw-yr)
14.2
14.2

10.6
9.3
     Advanced Gasifier
       Medium Btu Gas

Coal Liquefaction

     Direct
   250C
50,000b
1,700
2,810
 8.0
11.7
3 Within the Atmospheric Stabilization Framework, oil production from tar sands and oil
shale is treated as unconventional oil resources rather than synthetic fuel production.

b Barrels per day.

c Billions of Btus per day.  '*
Source: Pace Engineers, 1987.
                                              B-30

-------
                                                    Appendix B; Implementation of the Scenarios
     Coal.  Coal  transportation costs were
developed  from several         presented in
Coal Transportation:  1984, proceedings from
the Third  International  Coal  Trade   and
Transportation and Handling Conference, held
in  London  on  October  1-3,  1984.    In
particular,  two sources were  used:   Penfold
(1984) and Portheine (1984),

     Based on these sources, the average coal
transportation cost is assumed to be Sl7/ton in
1988 dollars.  At 24 million Btu per ton, or
25.32           per ton, the cost is S0.67 per
        in      dollars.

     Natural Gas.  The transportation costs
for  natural   gas  in   the   Atmospheric
Stabilization Framework are based on the cost
of transporting liquefied natural gas (LNG),
and therefore,  include  not only the cost of
transporting the  LNG  but also the cost of
liquefying  and regasifying  the natural   gas.
     costs were developed      ICF (1982).
la  this report  the         of  liquefying,
transporting, and regasifying natural gas
identified as:

     LNG cost =  $0,7S/mcf for processing
                 H- 15% loss
     Transport =  $0.44/mcf for each  1,000
      cost                 miles round trip
              +      loss

     These      are in  198S dollars.   An
 average wellhead gas price of $0.55 per mcf
 (1988 dollars) and an average distance of 4700
 mite (based on distance from  U.  S.  to
 Europe) was assumed, leading to a transporta-
 tion cost for natural gas of $2.90 per  mcf in
 1988 dollars, or $2.70 per gigajoule.

 Distribution Cost Assumptions For The
 Atmospheric Stabilization Framework

     In addition to the interregional      of
 energy   transportation,   the   Atmospheric
 Stabilization Framework also includes costs for
 toaregional transportation costs (referred to
 s$ distribution costs). These costs are basically
 the costs to transport fossil  fuels  from  the
 mine, wellhead, or port facility to the end user.
 Since the current version of the Atmospheric
 Stabilization Framework can accept only one
value  for  each  fuel,  several  simplifying
ass ympt ions           made,

      Oil.  Two primary sources were used for
estimating the distribution costs for oil:  E1A
(1987a),  which  provided data  on crude oil
prices and various prices for products refined
by the oil industry, and EIA (1986b), which
provided  data  on the  quantity  of products
produced by  refineries.   Using 1985  data, an
average price paid for all oil products by end
users was  estimated.   In  1988  dollars,  this
        price was about $0.91 per gallon.  This
         petroleum product       was  then
compared  to the refiner's  average cost of
production, which was determined by adding
the  refiner's acquisition  cost  for crude oil
(S30.08 per barrel in 1988 dollars) to the cost
for refining  the  crude oil into the various
petroleum products  (estimated at S6.44  per
barrel in 1988 dollars).  The refiner's average
cost would then be $36,52 per barrel in  1988
dollars, or $0.87 per gallon.  The difference
between  these two values ($0,04 per gallon, or
$1.68 per barrel)     assumed to be the cost
of distributing  oil products to the end user.
This distribution  cost  would  be  S0.28  per
gigajoule.

      Natural Gas.  The source used for gas
distribution costs was U.S. DOE (1987).  In
this report the average retail price of gas  was
reported to be $5,15/mcf in 1988 dollars.  The
average wellhead  price was reported to  be
S2.74/mcf.  The difference  between these  two
       is $2.41/ntef (or $2.24 per gigajoule),
      is  the  average cost  of distribution for
natural gas.

      Coal,    The  source  used   for  coal
distribution costs was EIA (1987b).   In  this
report the average F.O.B.  mine price during
1985 was estimated to be  about $27 per ton
(1988 dollars).  The average price paid by all
consumers was about $38 per ton, indicating a
transportation  cost  of about  $11  per  ton.
Assuming a heat content of 22 million Btu per
ton,  or  23.21  gigajoales  per  ton,   the
distribution cost for coal would be $0.47 per
gigajoule.

Generation Efficiency

      In   the   Atmospheric   Stabilization
Framework,  a  number  of input parameters
                                             B-31

-------
Policy Options for Stabilizing Global Climate
define  the  rate  of  change  in  energy
conservation and efficiency.   This  section
presents the major assumptions that have been
made in this area for the electric utility sector.
In  many  instances,  these  input  parameters
have been developed from U.S. sources due to
the lack of readily available data on energy
conservation and efficiency trends in other
parts  of the world.

      The technologies  that  are  used  to
generate electricity differ in their  ability to
convert the fuel supply into useful electrical
energy.    The  efficiencies   of  electrical
generation technologies were determined from
Radian (1990).   In  this report conversion
efficiencies were provided  for  most existing
and   emerging  fossil   fuel    combustion
technologies.

      Radian (1990) also provided information
on  the  current  conversion efficiencies  of
electrical  generation for  different regions of
the world.  These efficiency values differ by
region  due  to  several  factors,  including
differences in fuel quality and  differences in
technological  design  (such   as   operating
pressure or the  inclusion  of  more energy-
efficient reheat technologies).  Over time the
efficiency of electricity generation is expected
to improve as new technologies are developed.
For example, beginning in  1985 we assumed
that electricity  generation in the developing
countries   was   15%   less  efficient  than
generation in the developed countries.  This
differential was  assumed to decline through
2025, at which point generation efficiencies of
new units in the developing countries would
equal generation efficiencies in  the developed
countries. Additionally, generation efficiencies
for  new powerplants were assumed to increase
gradually  over  time.   In the No Response
scenarios,  oil-fired  units  were assumed  to
improve their efficiency to 40% after 2000 and
45%   after 2025  (compared  with  initial
assumptions for the efficiency ratings of new
units  of 35% in  1986).  Most  new gas-fired
units  (combined-cycle) were assumed to  be
45%  efficient  in 1986,  with  no  efficiency
changes thereafter. Goal-fired units were 38%
efficient after 2000 (based on the efficiency of
fluidized-bed combined-cycle units), improving
to an efficiency rating of 44% after 2025.  In
the Stabilizing Policies scenarios,  the rates of
efficiency  improvement  were assumed  to
increase relative  to  the No Response cases,
thus, oil-fired powerplants were 43% efficient
after 2000, and 48% efficient after 2025. Gas-
fired units were  assumed  to  demonstrate a
similar  improvement with a  50%  efficiency
rating after 2025. The efficiency of coal-fired
units in these scenarios changed  from 38%
after 2000 to 47% after 2025.

Emission Control Assumptions

      The   consumption   of  energy  often
generates  a  variety  of   greenhouse  gas
emissions, including CO2, CO, NOX, CH4, and
N2O. The type and amount of greenhouse gas
emissions  will  depend on the combustion
technology and the extent,  if any, of emission
controls.     Emission  rates  for  different
combustion  technologies  were  determined
from Radian (1990)  and Marland  and Rotty
(1984).  In addition, emission factors for N2O
were decreased to remain consistent with more
recent information on N2O formation.  Table
B-21 summarizes the  uncontrolled emission
rates for the major combustion  technologies
(uncontrolled means that no emission controls
are assumed). To reduce the amount of emis-
sions from  different combustion technologies,
however, there are different types of emission
controls that can be  applied.  Table B-22
summarizes the  size of emission  reductions
that could  occur  if various emission controls
were applied to the  technologies in Table
B-21, as determined from Radian (1990).


      In constructing the  scenarios, assump-
tions were  made  about the level of emission
controls that would  be adopted.  In the No
Response scenarios,  the major  assumptions
were:

•     New utility and industrial  coal-fired
boilers  in the industrialized countries  would
use low NOX burners starting  in 1985  (to be
consistent with the New Source Performance
Standard for nitrogen oxides  from boilers);
developing  countries  would  not  use  any
controls.
•     New light-duty gasoline vehicles in the
U.S. use 3-way catalysts by 1985; the rest of
the OECD uses oxidation catalysts on light-
duty gasoline  vehicles; developing  countries
have no emission control devices installed.
                                             B-32

-------
                                                       Appendix B: Implementation of the Scenarios
                                           TABLE B-21

                              Emission Rate Differences by Sector

                                     (grams per gigajoule)*
               Source
                                       Efficiency
C02
CO
CH
N2O
NO
• Electric Utility (g/GJ delivered electricity)
Gas Turbine Comb. Cycle
Gas Turbine Simp. Cycle
Residual Oil Boilers
Coal - F. Bed Comb. Cycle
Coal - PC Wall Fired
Coal - PC Cyclone
Coal - Integrated Gas
42.0
26.4
32.4
35.0
31.3
31.3
27.3
Industrial (g/GJ delivered steam for boilers; energy output
Boilers
Coal-Fired
Residual Oil-Fired
Natural Gas-Fired
Kilns - Coal
Dryer - Natural Gas
Dryer - Oil
Dryer - Coal
. Residential/Commercial (g/GJ energy
Wood Stoves
Coal Stoves
-Distillate Oil Furnaces
Gas Heaters
Wood Boilers
Gas Boilers
Residual Oil Boilers
Coal Boilers
Transportation (g/GJ energy input)
Rail
Jet Aircraft
Ships
Light Duty Gasoline Vehicle
Light Duty Diesel Vehicle
Light Duty Compressed
N. Gas Vehicle

80
85
85
65-75
30-65
30-65
30-65
output)
50
50
75
70
67.5
80.9
84.9
75.9

NA
NA
NA
NA
NA
NA

120,300
191,400
230,000
290,000
330,000
330,000
253,600
for others)

130,000
88,000
57,000
300,000-350,000
75,000-170,000
100,000-240,000
155,000-340,000

[150,000]
198,000
111,000
101,000
[138,000]
61,800
86,000
135,000

69,900
72,800
70,000
54,900
73,750
50,200

70
110
43
NA
42
42
222


110
17
18
75
10
15
170

17,600
3,400
17
13
280
10.6
19
244

570
120
320
10,400
340
4

13
20
2.2
1.8
2.0
2.0
NA


2.9
3.3
1.5
1
1
1
1

70
NA
7
1
21
1.4
1.8
13

13
2
20
36
2
120

20
30
44
40
45
45
51


18
16
3.5
2
NA
NA
NA

NA
NA
NA
NA
6
2.7
14
16

NA
NA
NA
0.5
20
7

400
640
590
690
1,400
2,600
760


390
180
71
500
' ' 52
160
215

190
170
65
61
47
53
183
295

xl,640
290
830
: 400
300
140

*  All emission rates are based on total molecular weight.

NA = Not Available
[ ] =" No Net CO2 if based on sustainable yield

Source:  Radian  Corporation, 1990; except N2O data, which is based on unpublished EPA data.  N2O emission
        coefficients are highly uncertain and currently undergoing further testing and review.
                                              B-33

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Policy Options for Stabilizing Global Climate
                                                                      TABLE B-22

                                                              Emission Control Performance
                                                  Efficiency3
                                                    Loss
         Technology
  CO2
Reduction
                  CO
               Reduction
                                 CH4
                               Reduction
                                                                 NOX
                                                              Reduction
              Date
             Available
         Utility
           Low NOX Burner
                   Coal
                   Coal Tangentially Fired
                   Oil
                   Gas

           Selective Catalytic Reduction
                   Coal.
                   Oil, AFBC
                   Gas

           CO2 Scrubbing
                   Coal
                   Oil
                   Gas

         Industrial Boiler
           Low NOjj Burner
                   Coal
                   Oil
                   Gas

           Selective Catalytic Reduction
                   Coal
                   Oil
                   Gas

         Kilns. Ovens and Dryers
           Low NOX Burner
                   Kilns,  Dryers
 0.25
 0.25
 0.25
 0.25
22.5
16.0
11.3
 0.25
 0.25
 0.25
Negligible
Negligible
Negligible
Negligible
Negligible
Negligible
Negligible
  90
  90
  90
Negligible
Negligible
Negligible
Negligible
Negligible
Negligible
               Negligible
               Negligible
               Negligible
               Negligible
                  8
                  8
                  8
               NA
               NA
               NA
               Negligible
               Negligible
               Negligible
Negligible      Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               NA
                               NA
                               NA
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
                               Negligible
35
35
35
50
                                                                 80
                                                                 80
                                                                 80
NA
NA
NA
35
35
50
                                                  80
                                                  80
                                                  80
                                                  35
1980
1980
1980
1980
              1985
              1985
              1985
2000
2000
2000
1980
1980
1980
                                                                               1985
                                                                               1985
                                                                               1985
                                                                               1985
                                                                          B-34

-------
                                                                                             Appendix B:  Implementation of the Scenarios
                                                      TABLE B-22 (cent.)




                                                 Emission Control Performance
Mobile Source
Selective Catalytic Reduction
Coke Oven
Light Dutv Gasoline Vehicle
Engine Control
Oxidation Catalyst
3-Way Catalyst
Heavy Duty Gasoline Vehicle
Engine Control
Oxidation Catalyst
3-Way Catalyst
Light Duty Diesel Vehicle
Low NOX Control
Heavy Duty Diesel Vehicle
Low NO, Control
Efficiency3
Loss
(%)
1

NA
NA
NA
NA
NA
NA

NA
NA .
CO2
Reduction
(%)
Negligible

-11
-17
-23
-25
-66
-71

Negligible
Negligible
CO
Reduction
(%)
8

36
57
78
35
90
97

11
8
CH4
Reduction
(%)
Negligible

Negligible
33
44
52
70
69

-16
Negligible
NOS
Reduction
' (%)
80

8
23
44
31
33
41

24
41
Date
Available
1979

1968
1975
1980
1978
1985
1998

1985
1987
3 Efficiency loss as a percent of end-user energy conversion efficiency.



Source:  Radian,  1990.
                                                             8-35

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Policy Options for Stabilizing Global Climate
•     Heavy-duty gasoline vehicles in the U.S.
use basic engine controls.

      Emission controls in the No Response
scenarios  were  limited to  controls already
approved or highly likely to be approved under
current  laws or  regulations.  In response to
concerns  over  global  warming,  additional
emission  controls  were   assumed  in  the
Stabilizing Policies scenarios:

•     New utility boilers  in  the  OECD  use
Selective Catalytic Reduction (SCR) beginning
in 2000, while all existing units install low NOX
burners.  In  the rest of the world all new units
use low NOX burners beginning in 2000  and
SCR in 2025, with  50% of all existing units
using low NOX burners beginning in 2000.

•     Industrial  boilers in the OECD install
SCR beginning in 2000; the rest of the world
installs  low  NOX burners  beginning  in 2000
and SCR beginning in 2025.

•     Kilns  and dryers in the industrial sector
in the OECD employ low excess air (LEA) by
2000, with all new facilities  using low NOX
burners beginning in 2000; the  rest of  the
world employs LEA beginning in 2000 and low
NOX burners beginning in  2025.

•     Coke  ovens use SCR beginning in 2000
in the  OECD; the  rest of the world adopts
SCR beginning in 2025.

•     Beginning  in  1985  the   non-OECD
countries  install engine controls on all light-
duty gasoline vehicles, which is intended to
capture some countries  that  adopt catalyst
technology,  while others continue not to  use
any controls.  Beginning  in  2000 all of the
OECD  uses 3-way catalysts on light-duty
gasoline vehicles, oxidation catalysts on all
heavy-duty gasoline vehicles,  and low NOX
controls on heavy-duty diesel vehicles.   The
rest of the world uses oxidation catalysts on
light-duty gasoline vehicles and engine controls
on heavy-duty gasoline vehicles. Beginning in
2025,3-way catalysts are installed on all heavy-
duty gasoline vehicles in the OECD; the  rest
of the world installs 3-way catalysts on light-
duty and heavy-duty gasoline vehicles and  low
NOX controls on heavy-duty diesel vehicles.
Carbon Fees

      Carbon fees  were  imposed  on  the
production  of fossil fuels  in  proportion to
their  CO2 emissions potential  in  order to
reflect a more aggressive response strategy to
reduce the  rate of emissions growth.  The
RCWP and  SCWP scenarios assumed fees of
$25/ton of coal, S4.80/barrel of oil (S0.80/GJ),
and S0.54/GJ for natural gas. The fees for the
RCWR scenario were increased to SlOO/ton of
coal,  $19.20/barrel  of  oil  and S2.16/GJ for
natural gas.

Results of the Energy Scenarios

      This section presents the detailed results
for the No Response and Stabilizing Policies
scenarios,

Energy Prices

      Given  the  level  of energy  demand
resulting  from  the assumptions   discussed
above  and  the  types  of  energy  supplies
assumed   to   meet  this   demand,   the
Atmospheric  Stabilization   Framework
estimates  energy prices.   These prices are
summarized in Table B-23 for oil, natural gas,
and coal for all six scenarios.  These prices
should be viewed as the energy cost to the
marginal consumer to purchase the  energy at
its point of production, i.e.,  at the wellhead or
mine-mouth from the marginal producer  (e.g.,
oil prices  are typically the acquisition cost of
crude from the Middle East),

Energy Use and Emissions

      The following tables present the results
for the SCW  scenario for  each  of the  nine
regions (these tables can be found at the end
of Appendix B following REFERENCES):

•     Table B-24:  Primary Energy Supply;

•     Tables B-25  to B-31: Primary Energy
      Supply by Resource,  i.e., oil,  gas,  coal,
      biomass, hydroelectric,  nuclear,   and
      solar,  respectively;
      Table   B-32:
      Consumption;
Primary   Energy
                                             B-36

-------
                                                          Appendix B:  Implementation of the Scenarios
                                              TABLE B-23

                                              Energy Prices

                                            (1988$/Gigajoule)
YEAR
RCWP
RCW
SCWP
sew
RCWR
RCWA
1985
2000
2025
2050
2075
2100
 3,04
 3.40
 4.42
 4.90
 5.62
 6.44
3.04
4,18
7.06
7.88
8.74
9.50
                                             Crude Oil Prices
  3.04
  3.44
  5.28
  4.68
  5.04
  5.24
3.04
3.82
5.88
6.74
7.86
8.56
  3.04
  3.68
  3.50
  3.88
  4.02
  4.06
  3.04
  5.40
  5.42
  5.88
  6.54
  8.90
1985
2000
2025
2050
2075
2100
                                            Natural Gas Prices
                                                (wellhead)
 1.20
 2.10
 1.04
 1.42
 2.04
 2.76
1.20
2.40
3.82
4.94
6.46
7.34
  1.20
  2.06
  2.04
  1.12
  1.32
  1.44
1.20
2.12
2.96
3.40
4.34
5.28
  1.20
  2.34
  0.46
  0.78
  0.90
  0.94
  1.20
  3.12
  4.28
  4.92
  5.66
  7.92
                                                Coal Prices
                                               (mine-mouth)
1985
2000
2025
2050
2075
2100
 0.70
 0.82
 1.40
 1.24
 1.10
 0.98
0.70
0.66
0.62
0.56
0.80
1.08
  0.70
  0.82
  1.34
  1.24
  1.10
  0.96
0.70
0.66
0,60
0.52
0.54
0.60
  0.70
  1.36
  2.06
  2.58
  2.58
  2.42
  0.70
  0.74
  1.08
  1.28
  1,68
  3.20
                                                  1-37

-------
Policy Options for Stabilizing Global Climate
•    Table   B-33:      Secondary  Energy
     Consumption, broken down into fuel
     versus electricity;

•    Tables B-34 to B-36:  Secondary Fuel
     Consumption  by Type  (i.e., oil, gas,
     solids);

•    Table  B-37:   Residential/Commercial
     Energy Consumption:   Fuel  versus
     Electricity;

•    Table   B-38:      Industrial  Energy
     Consumption: Fuel versus Electricity;

•    Table  B-39:   Transportation  Energy
     Consumption: Fuel versus Electricity;

•    Table  B-40:   Electric Utility Energy
     Consumption;

•    Table   B-41:     Energy  Conversion
     Efficiency   at   Electric   Utility
     Powerplants;

•    Table  B-42:  Synthetic  Production  of
     Oil and Gas;

•    Table B-43:  Energy Used for Synthetic
     Fuel Production by Type;

•    Table  B-44:    CO2  Emissions  from
     Energy Consumption  (in petagrams  of
     carbon);

•    Table B-45: CO Emissions from Energy
     Consumption (in teragrams of carbon);
     and

•    Table  B-46:    NOX  Emissions  from
     Energy Consumption  (in teragrams  of
     nitrogen).

     This same information is provided for
each of the scenarios.  Tables B-47  to B-69
summarize the  RCW  case.   Tables  B-70  to
B-92 summarize the  RCWA case.  Tables
B-93 to B-115  summarize the SCWP case.
Tables  B-116 to B-138 summarize the RCWP
case.  Tables B-139 to B-161 summarize the
RCWR case.
CHLOROFLUOROCARBON AND HALON
EMISSIONS

      The CFC and halon emission estimates
were  based  on Regulatory  Impact Analysis:
Protection of Stratospheric Ozone,  U.S. EPA
(1988), which was developed by U.S. EPA to
support U.S. participation  in the Montreal
Protocol.  Emission estimates from U.S. EPA
(1988) consistent with the Montreal Protocol
were used in the SCW case since the economic
growth rates in the SCW case were similar to
U.S. EPA (1988) assumptions. In the SCW it
was assumed that the U.S. would comply with
the Montreal Protocol 100%, other developed
countries would average  94%  participation,
and developing countries would average 65%
participation.  For the RCW case, the rate of
growth was increased 75% to reflect the higher
economic growth rates.  Also, the rate of
participation was increased to reflect  a higher
rate of technological improvement that would
make it easier to comply with the terms of the
Montreal Protocol, i.e., 100% of the developed
countries and 75% of the developing countries
were assumed to participate.  For the SCWP,
RCWP, and  RCWR  cases,  the Montreal
Protocol   is  strengthened   to  produce a
complete phaseout of CFCs in participating
countries by 2003. Participation rates were the
same for all Stabilizing Policies scenarios, with
100% of the developed countries and 85% of
the developing countries participating.  The
RCWA  case   assumes  a  low  level   of
participation  in and  compliance with  the
Montreal Protocol; the assumptions used in
this case are similar to the "Low Case" analysis
described in U.S. EPA (1988), i.e., 75% of the
developed  countries   and  40%   of   the
developing  countries  were  assumed   to
participate.  The CFC and halon emission
estimates from each of the  six scenarios are
summarized in Table B-162.

DEFORESTATION

      Net carbon  flux  projections  due  to
deforestation and afforestation were based on
a model described by Moore et al. (1981) and
Houghton et al. (1983).  For our  analyses
(which were based on Houghton (1988))  only
                                            B-38

-------
                                                  Appendix B:  Implementation of the Scenarios
                                        TABLE B-162

                           Chlorofluorocarbon Emissions By Scenario

                                         (Gigagrams)
SCENARIO
1985      2000
           2025
           2050
            2075
2100
CFC-11

 sew
 SCWP
 RCW
 RCWP
 RCWA
 RCWR
CFC-12

 sew
 SCWP
 RCW
 RCWP
 RCWA
 RCWR
HCFC-22

 sew
 SCWP
 RCW
 RCWP
 RCWA
 RCWR
CFC-113

 sew
 SCWP
 RCW
 RCWP
 RCWA
 RCWR
363.8
363.8
363,8
363.8
363.8
363.8
 73.8
 73.8
 73.8
 73.8
 73.8
 73.8
150.5
150.5
150.5
150.5
150.5
150.5
419.5
402.9
500.2
491.4
614.6
491.4
206.1
206.1
263,0
263.0
263.0
263.0
121.3
112.7
178.4
174.7
248.6
174.7
393.5
  50.6
450.3
  83.5
857.2
  83.5
407.0
407.0
,830.7
830.7
830.7
830.7
 124.9
   8.8
 170.5
  19.9
 371.7
  19.9
 420.0
  64.5
 508.7
  87.9
1400.0
  87.9
 754.5
 754.5
2425.8
2425.8
2425.8
2425.8
 142.2
  14.0
 195.3
  26.1
 618.7
  26.1
297.4
53.5-
327.1
57.9
1056.4
57.9
426.5
68.5
519.1
91.2 -
1483.1
91.2
879.1
879.1
3124.5
3124.5-
3124.5
3124.5
142.2
14.0
195.3
26.1
618.7
26.1
297.4
53.5
327.1
57.9
1056.4
. 57.9
426.5
68.5
519.1
91.2
1483.1
91.2
879.1
879.1
3124.5
3124.5
3124.5
3124.5
142.2
14.0
195.3
26.1
618.7
26.1
                                            B-39

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Policy Options for Stabilizing Global Climate
the tropical regions were considered since the
net flux of carbon from the temperate regions
was  close to zero for 1980.  Three tropical
regions of the world were evaluated (tropical
America,  Asia, and Africa), two forests types
(closed and open forests), and  two types of
land-use changes (deforestation to permanent
croplands, and afforestation or the formation
of  plantations).   A  low  estimate for  the
amount   of carbon   stored  in   terrestrial
ecosystems  (forests and soils) was used, such
that the net flux of carbon  to the atmosphere
for the base year (1980) is about 0.4 Pg (1 Pg
= 1 petagram = 1015 grams = 109 metric tons
= 1 gigaton = 1  Gt).

      Based  on  Hough ton  (1988),   three
scenarios  for projecting the net flux of carbon
from terrestrial ecosystems from 1980 to 2100
were developed:

•     Scenario 1: Deforestation as a function of
population   size.     In   this   projection
unsustainable agricultural practice  and rapid
population   growth  lead   to  continuously
increasing pressure on tropical forests.  The
rate of deforestation 'is assumed to increase
exponentially, based on population growth in
each of the three tropical  regions, from  11
million ha/yr (1 ha/yr  =  1 hectare per year =
2.461 acres per year)  in 1980 to 34 million
ha/yr in  2047, when  the  available area  of
forests  in Asia  is  exhausted.   The  rate of
establishment of tree plantations in the tropics
is assumed  to be zero.  These assumptions
result  in a rapid increase in  net carbon
emissions from 0.7 Pg  C/yr to more than 2 Pg
C/yr in 2047  before  the  Asian forests  are
exhausted.   Latin  American  and African
forests  are  exhausted  by  2075,  reducing
emissions drastically.  The total net release of
carbon between 1980 and 2100 is 138 Pg C.

•     Scenario  2:  Exponential  increase  in
tropical deforestation.   In this case,.clearing of
forested lands for agriculture, pasture, logging,
and speculation continues, although  at  a
somewhat slower rate than  in Scenario  1
because of improved agricultural practices and
the substitution of modern fuels for traditional
uses  of  wood.    As  a  result, tropical
deforestation increases gradually, reaching 15
million  ha/yr  in   2097.     The  rate   of
establishment of tree plantations in the tropics
again  is   assumed  to  be  zero.    These
assumptions  result  in  emissions  that total
almost the same amount as in  the  previous
case,  although they are spread  out over a
longer period.  Annual emissions are close to
1 Pg C/yr from 2000 to 2100.  The total flux of
carbon between 1980 and 2100 is 118 Pg C.

•     Scenario  3: High  reforestation.   In  the
third case, it is assumed that a combination of
policies succeed in stopping  deforestation by
2025, while more than 1000 million ha  are
reforested  by 2100.   Only  land  that once
supported  forests  and is  not  intensively
cultivated  is assumed  to  be available  for
reforestation. These lands include 85% of the
area currently involved  in shifting cultivation
(370 million  ha), under the  assumption that
this  practice is replaced by sustainable low
input agriculture (Sanchez and Benites, 1987).
In addition,  fallow  agricultural land  in  the
temperate  zone  (250  million ha),  planted
pasture in Latin America (100 million ha), and
degraded land in Africa and Asia (400 million
ha) is assumed to  be reforested.   Of  the
reforested  land,  about 380  million ha  are
assumed to be in plantations; the rest absorbs
carbon at a much lower rate but reaches a
higher level of average biomass.  In this case,
the^biosphere becomes a sink for carbon  by
2000 and reaches its peak absorption  of 0.7 Pg
C/yr before  2025.    The  size  of the sink
gradually declines after 2025 as forests reach
their  maximum size and  extent. This case
results in a total release  of carbon due  to
deforestation   of   12  Pg,   and   a  total
accumulation  of carbon  due to  the  three
reforestation activities of 38 Pg. Therefore the
net accumulation of carbon on land for this
case is 26 Pg.
                                         \
      Scenario 1 was used in the SCW case
and the RCWA case to represent worlds where
population growth remains  quite high and  the
rate of technological diffusion low such that
heavy reliance  on biomass for  cooking and
heating continues. Scenario 2 was used in the
RCW case to represent a world that continues
to  utilize   its  biomass   resources  at   an
unsustainable  rate for many years,  although
the depletion rate is lower  than in Scenario 1
since population growth  is lower  and  the
transformation to more modern fuels occurs
more quickly. Scenario 3 was used in both the
RCWP and SCWP cases to represent a world
committed  to  halting net deforestation,.
                                              B-40

-------
                                                    Appendix B:  Implementation of the Scenarios
including the adoption of agricultural practices
that  do not  require  significant  amounts  of
slash and burn agriculture or land-clearing and
the development of alternative energy sources
for current biomass consumers.  Figure B-l
summarizes   the   CO2   emissions   from
deforestation  (in  terms  of petagrams  of
carbon)  for  these  three  scenarios.    An
additional scenario, Scenario 4 was created for
the RCWR case.  It was similar to Scenario 3
in representing a world committed to halting
net  deforestation,  but  also  assumed  an
increased  uptake  of  CO2 equivalent  to a
maximum of 1 gigaton of carbon  per year.

AGRICULTURE

      As  discussed in Appendix  A,  global
estimates  of  agricultural  production  and
fertilizer consumption were derived from the
Basic Linked System (BLS) at the Center for
Agricultural and Rural Development at Iowa
State University. Data were available from the
BLS  only  through   2050;  therefore,   to
determine values for the 2050-2100 period, the
trends indicated  from the pre-2050 results
were extrapolated to 2100 and adjusted based
on changes in population (see APPENDIX A
for further discussion).

      Two scenarios  were devised for  the
SCW and RCW cases.   Key results for  the
SCW and SCWP cases for each of the  nine
regions  are summarized as follows (tables are
at the end of this document):

•     Table B-163: Production of Wheat;

•     Table B-164: Production of Rice;

•     Table B-165:   Production of Coarse
      Grains;

•     Table B-166: Production of Meats;

•     Table  B-167:    Production   of Dairy
      Products;

•     Table  B-168:   Production  of Other
      Animals (e.g., pork, poultry, eggs, fish);

•     Table B-169: Amount of Fertilizer Use;
      and
•     Table B-170:  Amount of Land  Under
      Rice Cultivation.

   •   The corresponding information for the
RCW, RCWA, RCWP,  and RCWR cases  is
provided in Tables B-171 to B-178.

      The assumptions on grain production,
animal production, and fertilizer use were not
varied from the No Response scenarios to the
Stabilizing  Policies scenarios (e.g., from the
SCW to the SCWP).  Since the  population
estimates were the  same in both cases, we
assumed that basic consumption habits would
not change, i.e., people  would consume the
same types of  foods regardless of policies to
stabilize the atmosphere.  However, we did
assume that policies would be implemented to
reduce  the quantity  of  greenhouse  gas
emissions  from agricultural activities.  Key
assumptions included the following:

•     Changes  in types of  fertilizers and
method of application were assumed to reduce
the quantity of N2O evolved from nitrogenous
fertilizers.  (It  is possible that policies could
also  encourage the development of fertilizers
that would alter the total quantity of fertilizer
required; however,  this  possibility was not
modelled in this analysis.)

•     Changes in rice cultivation practices and
types of rice cultivars were assumed to reduce
the amount of  CH4 from rice production.

•     Changes in meat and dairy  production
techniques, such as  the  use of additives like
methane-inhibiting ionophores, diet changes,
or alterations  in  animal waste  management
methods, were  assumed to reduce the amount
of CH4 from meat and dairy production.

      For all three types of activities, emission
rates were assumed to decline 0^5% per year in
the Stabilizing Policies scenarios and remain
constant in the No Response scenarios.

GREENHOUSE GAS EMISSIONS

      The human activities portrayed  in the
previous tables, including energy  production
and consumption, agricultural activities, CFC
consumption, and other industrial activities,
                                             B-41

-------
   Policy Options for Stabilizing Global Climate
                                FIGURE B>1
           CO2 EMISSIONS FROM TROPICAL DEFORESTATION
                               Global Total
    2.5
     1.5 -
n
X

o
.a

n
o
«
£
n

0>
n
1 •-
•5   0.5

Q.
      o
    -0.5
        i
     -1


      1950
                                      Stabilizing Policy Scenarios
           1980       2010       2040       2070       2100



                           Year
                                  B-42

-------
                                                   Appendix B: Implementation of the Scenarios
cause a number of greenhouse gas emissions.
Additionally, various greenhouse gases are also
produced from natural processes, such as CH4
production from wetlands.   These emission
forecasts are summarized below by scenario for
each major emission category.  For example,
forecasts for the SCW scenario  are (all tables
can be found at the end of this  document):

•     Table B-179:  CO2 Emissions by Type
      of Activity (in petagrams of carbon);

•     Table B-180:  N2O Emissions by Type
      of Activity (in teragrams of nitrogen);
      Table B-181:  CH
      of Activity (in teragrams of CH4);
4 Emissions  by Type
•     Table B-182:  NOX Emissions by Type
      of Activity (in teragrams of nitrogen);
      and

•     Table B-183: CO Emissions by Type of
      Activity (in teragrams of carbon).

      This information is provided for each of
the  scenarios.    Tables  B-184  to B-188
summarize  emissions  from the RCW case,
Tables B-189 to B-193 summarize the RCWA
case, Tables B-194 to B-198 summarize  the
SCWP case, and   Tables  B-199  to B-203
summarize the RCWP case.  Tables B-204 to
B-208 summarize the RCWR case.

REALIZED AND EQUILIBRIUM WARMING

      The  emissions  estimates  for  each
scenario were used to determine the amount
of realized and  equilibrium warming.   The
extent of warming will depend not only on the
amount of greenhouse gas emissions, but also
on  the sensitivity of the climate system to
increases in greenhouse gas concentrations.
As discussed in Chapter III,  the sensitivity of
the climate system is often expressed in terms
of the amount of warming that would result
from   an  equivalent   doubling   of  CO2
concentrations in the atmosphere (typically
expressed  as 2XCO2). There is some debate
over the amount of warming that would result;
in our analyses we have considered a range of
1.5-5.5°C  (see  CHAPTER  HI for  further
discussion of this range).

      Based on the amount of greenhouse gas
emissions and resulting atmospheric concentra-
tions, the  extent of realized and equilibrium
warming  is presented for each scenario for
climate  sensitivities  of  1.5°C,  2.0°C,  3.0°C,
4.0°C,  and  5.5°C.   Table  B-209  presents
realized warming and Table B-210  presents
equilibrium warming  for the six scenarios.
                                            B-43

-------
Policy Options Tor Stabilizing Global Climate
                                            TABLE B-209

                             Realized Warming for l.5°-5.5*C Sensitivities

                                          (Degrees Celsius)
Sensitivity
sew
1.5
2.0
3.0
4.0
5.5
RCW
1.5
2.0
3.0
4.0
5.5
SCWP
1.5
2.0
3.0
4.0
5.5
RCWP
1.5
2.0
3.0
4.0
5.5
RCWA
1.5
2.0
3.0
4.0
5.5
RCWR
1.5
2.0
3.0
4.0
5.5
1985

0.4
0.5
0.6
0.7
0.8

0.4
0.5
0.6
0.7
0.8

0.4
0.5
0.6
0.7
0.8

0.4
0.5
0.6
0.7
0.8

0.4
0.5
0.6
0.7
0.8

0.4
0.5
0.6
0.7
0.8
2000

0.6
0.7
0.9
1.0
1.2

0.6
0.7
0.9
1.0
1.2

0.6
0.7
0.9
1.0
1.2

0.6
0.7
0.9
1.0
1.2

0.6
0.7
0.9
1.1
1.2

0.6
0.7
0.9
1.0
1.2
2025

1.0
1.2
1.5
1.8
2.0

1.0
1.3
1.6
1.9
2.1

0.8
0.9
1.2
1.4
1.7

0.8
1.0
1.3
1.5
1.7

1.2
1.5
1.9
2.1
2.4

0.7
0.9
1.2
1.4
1.6
2050

1.3
1.7
2.2
2.6
3.1

1.6
2.0
2.6
3.0
3.5

0.9
1.1
1.5
1.7
2.1

0.9
1.2
1.6
1.9
2.2

2.3
2.8
3.6
4.2
4.8

0,7
0.9
1.3
1.5
1.8
2075

1.7
2.2
2.9
3.4
4.0

2.3
2.9
3.8
4.4
5.2

0.9
1.2
1.6
1.9
2.3

1.1
1.4
1.9
2.2
2.7

3.7
4.5
5.8
>6.0*
>6.0*

0.7
0.9
1.2
1.5
1.8
2100

2.1
2.6
3.5
4.2
5.0

3.1
3.8
5.0
6.0
>6.0*

1.0
1.2
1.7
2.1
2.5

1.2
1.5
2.1
2.5
3.0

5.0
>6.0*
>6.0*
>6.0*
>6.0*

0.6
0.8
1.1
1.4
1.8
* Estimates of equilibrium warming commitments greater than 6°C represent extrapolations beyond the range tested
in most climate models, and this warming may not be fully realized because  the strength of some positive feedback
mechanisms may decline as the Earth warms.  These estimates are represented by >6°C.
                                                 B-44

-------
                                                      Appendix B:  Implementation of the Scenarios
                                           TABLE B-210

                          Equilibrium Warming for L5°-5.5°C Sensitivities

                                         (Degrees Celsius)
Sensitivity
sew
1.5
2.0
3.0
4.0
5.5
RCW
1.5
2.0
3.0
4.0
5.5
SCWP
1.5
2.0
3.0
4.0
5.5
RCWP
1.5
2.0
3.0
4.0
5.5
RCWA
1.5
2.0
3.0
4.0
5.5
RCWR
1.5
2.0
3.0
4.0
5.5
1985

0.6
0.7
1.1
1.5
2.1

0.6
0.7
1.1
1.5
2.1

0.6
0.7
1.1
1.5
2.1

0.6
0.7
1.1
1.5
2.1

0.6
0.7
1.1
1.5
2.1

0.6
0.7
1.1
1.5
2.1
2000

0.8
1.1
1.6
2.2
3.0

0.8
1.1
1.7
2.2
3.0

0.7
1.0
1.5
2.0
2.7

0.8
1.0
1.5
2.0
2.8

0.9
1.1
1.7
2.3
3.1

0.7
1.0
1.5
2.0
2.7
2025

1.3
1.7
2.6
3.5
4.8

1.4
1.9
2.8
3.8
5.2

0.9
1.2
1.9
2.5
3.4

1.0
1.3
2.0
2.6
3.6

1.8
2.4
3.5
4.7
>6.0*

0.9
1.2
1.7
2.3
3.2
2050

1.8
2.3
3.5
4.7
>6.0*

2.2
2.9
4.3
5.8
>6.0'

1.0
1.4
2.0
2.7
3.7

1.2
1.5
2.3
3.1
4.2

3.3
'4.4
>6.0*
>6.0*
>6.0*

0.8
1.1
1.6
2.1
2.9
2075

2.1
2.8
4.2
5.7
>6.0*

3.0
4.0
6.0
>6.0*
>6.0*

1.1
1.4
2.1
2.8
3.9

1.3
1.7
2.6
3.4
4.7

4.8
>6.0*
>6.0*
>6.0*
>6.0*

0.7
1.0
1.4
1.9
2.6
2100

2.5
3.3
4.9
>6.0*
>6.0*

3.8
5.1
>6.0*
>6.0*
>6.0*

1.1
1.4
2.1
2.8
3.8

1.4
1.8
2.8
3.7
5.0

>6.0*
>6.0*
>6.0*
>6.0»
>6.0*

0.6
0.8
1.3
1.6
2.2
' Estimates of equilibrium wanning commitments greater than 6°C represent extrapolations beyond the range tested
in most climate models, and this warming may not be fully realized because the strength of some positive feedback
mechanisms may decline as the Earth warms.  These estimates are represented by >6°C.
                                               B-45

-------
Policy Options for Stabilizing Global Climate
NOTES

1. The World Bank estimates are very similar
to estimates that could be obtained from the
United Nations due to reliance on the same
data sources.   The  World  Bank  estimates
(Zachariah and Vu, 1988) were chosen since
they  were  the  most   recently  published
estimates available at the time.

2. A net reproduction rate of unity indicates
that people of child-bearing age have children
at a replacement rate; it eventually leads to a
stable population level.

3. Each cost level indicates the cost at which
resources could first be economically extracted.
Not all of the resources available at a specific
extraction  cost  would  be  made  available
immediately since not all potentially economic
resources  are  discovered  immediately  or
produced  instantaneously once  discovered.
See Appendix A for further details.

4.  Flaring was not assumed to  decline any
further  in  the  U.S.  since flaring  occurs
primarily during well testing and maintenance
operations.  Some additional reductions may
be possible, but these potential improvements
in  the  U.S. were  not  assumed to occur.
Additionally, the flaring value for the OECD
Pacific countries was reported to be 0.1%; this
value was not used as a lower bound, however,
because very little natural  gas production
occurs in these countries compared to the size
of the U.S. market.

5.  When  implementing these assumptions, a
small amount of biomass was assumed to be
available at  a lower cost in order, to ensure
that the amount of biomass supplied globally
in the Atmospheric Stabilization Framework
increased  smoothly  rather  than becoming
available immediately once these cost levels
were  reached.   In  this  sense, these  cost
assumptions are average costs for biomass at a
given point  in time, although some biomass
supplies may be available at costs lower than
the average.
6. All participation rates are applied to total
estimated production  for the region; e.g., if
65% of the developing countries participate in
the  Montreal Protocol,  then 65% of the
production was subject to  the terms of the
agreement.
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World Resources:  1987.   International Basic
Books, New York.

Zachariah,  K.C., and M.T. Vu. 1988.  World
Population  Projections,  1987-1988  Edition.
World  Bank, Johns Hopkins University Press,
Baltimore. 440 pp.
United Nations.  1986.  Statistical Yearbook:
1983-84.  United Nations, New York.
                                             B-48

-------
                                                     Appendix B:  Implementation of the Scenarios
sew
REGION
                                           TABLE  B-24

                                     PRIMARY ENERGY  SUPPLY
                                         (Exajoules/Yr)
                               1985
                                           2000
                                                       2025
                                                                  2050
                                                                              2075
TOTAL
                              301.6
                                          364.6
                                                      457.9
                                                                  506.0
                                                                             574.3
                                                                                          2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
63,
47.
8,
81.
25.
23.
16.
20.
14.
,7
.6
,9
.2
.6
.7
.3
.5
.1
58.
51.
11
91
38
49
24
22
16
,7
.8
.8
.3
.2
.0
.1
.9
.8
57.
52.
12.
103.
64.
63.
37.
39.
26.
5
9
8
6
0
4
7
1
9
61.
51.
13.
108.
73.
60.
45,
61.
29.
7
6
9
.4
.4
2
.9
.4
.5
71.
54.
17.
122.
88.
62.
53.
73.
31.
7
3
3
,2
,3
.1
.4
,7
.3
93.6
63.4
23.1
165.9
102.6
50.3
48.4
67.5
36.0
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                               1985
                              117.9
                                           TABLE  B-25

                                       PRIMARY OIL  SUPPLY
                                         (Exajoules/Yr}
                                           2000
                                          129.3
                                                       2025
                                                                   2050
                                                      136.4
                                                                  125.8
                                                                              2075
                                                                              103.7
                                                                                          2100
20.8
11.9
1.1
26.0
5.2
22.4
10.8
14.1
5.6
12.0
9.5
.6
21.8
6.8
46.2
16.9
11.0
4.5
7.3
8.2
.2
17.7
6.8
55.6
20.6
16.2
3.8
7.8
6.1
.0
12.4
5.1
44.2
17.5
29.7
3.0
8.1
4.2
.0
8.0
3.3
30.0
12.6
35.2
2.3
12.0
2.6
.1
5.6
2.6
19.1
8.8
26.3
2.0
                                                                                          79.1
REGION                         1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                          58.6
                                           TABLE B-26

                                       PRIMARY GAS SUPPLY
                                         (Exajoules/Yr)
                                           2000
                                           71.8
                                                       2025
                                                                   2050
                                                       79.9
                                                                   76 ,0
                                                                              2075
                                                                               65.5
                                                                                          2100
16.3
9.7
.7
24.0
.5
1.2
1.3
2.5
2.4
15.5
11.9
1.6
29.2
1.4
2.6
2.5
4.8
2.3
11.6
10.6
1.6
29.4
3.9
6.4
5.1
8.0
3.3
8.1
8.2
1.1
26.4
4.0
12.2
5.8
6.8
3.4
5.3
5.0
.6
13.4
2.7
26.0
5.8
4.7
2.0
4.3
3.5
.4
6.4
1.5
22.6
4.4
2.8
1.2
                                                                                          47.1
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                               1985
                               87.3
                                           TABLE B-27

                                      PRIMARY COAL SUPPLY
                                         (Exajoules/Yr}
                                           2000
                                          114.6
                                                       2025
                                                                   2050
                                                      158.8
                                                                  180.9
                                                                              2075
                                                                              246.6
                                                                                          2100
19,
9,
3,
26,
18,

4,

4,
=s
.4
.4
,9
.7
.9
.0
.0
.6
.4
SSSZSIX
22,
12,
5,
33,
27

4

7
.8
.7
.6
.9
,5
.0
.3
.8
.0
26.
16.
7.
44.
43.

8.
1,
11.
8
.1
,1
4
,4
.0
,2
4
,4
31.
18.
8.
52.
48.

12.
2.
7.
1
1
3
6
7
0
3
1
7
— — — -
40.
23.
10.
80.
62,

19,
3,
5,
szsss
,9
,4
,9
,4
.9
.0
.3
.3
.5
===_
56.
32.
15,
130,
76,

14,
3
5
,8
,5
.4
.4
.1
.0
.2
.4
.4
                                                                                          334.2
                                               B-49

-------
 Policy Options for Stabilizing Global Climate
-SCW
REGION
                               1985
United States                     .0
OECD Europe/Canada                .0
OECD Pacific                      .0
Centrally Planned Europe          .0
Centrally Planned Asia            .0
Middle East                       .0
Africa                            .0
Latin America                     .0
South and East Asia               .0

TOTAL
                                           TABLE B-28

                                     PRIMARY BIOMASS SUPPLY
                                          (Exajoules/Yr)
                                           2000
                                                       2025
                                                                   2050
                                                        7.4
                                                                   25.7
                                                                               2075
                                                                                           2100
.0
.0
.0
.0
.0
.0
.0
.0
.0



1.


1.
2.
1.
6
4
2
1
5
0
4
2
0
2,
1.

3.
1.

5.
7
3,
.1
.5
.7
.8
,8
.0
.0
.5
.3
2
2
1
5
2

7
10
4
.9
.1
.1
.5
.6
.0
.2
.7
.7
3.
2,
1.
7,
3,

9.
13
6
.8
.7
.4
,1
.3
.1
.3
.9
.1
                                                                                           47.7
REGION
United States
OECD Europe/Canada
OECD Pacific /
Centrally Planned Europe
Centrally /Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                           TABLE B-29

                                 PRIMARY HYDROELECTRIC SUPPLY
                                         {,Exajoules/Yr)
                                 1985
                                21.2
                                            20,00
                                                        2025
                                                                    2050
                                            29.6
                                                        45.1
                                                                    59.2
                                                                                2075
                                                                                69.4
                                                                                            2100
3,
8.
1,
2.
1.


3,
1,
,3
.2
.2
,5
.0
.1
.2
.3
.4
3
9
1
3
2


6
2
.8
.6
.3
.1
.3
.2
.4
.3
.6
4,
10,
1,
3,
6.

1.
11,
5,
.3
.6
.3
.6
.4
.4
.3
.3
.9
4.
11.
1.
3.
10.

3.
15.
9.
,6
,0
,4
,7
,0
,6
,2
,3
,4
4.
11.
1.
3.
11.

5.
19.
. 11.
7
,1
4
.7
3
7
3
8
4
4.
11.
1.
3.
11.

6.
20.
12,
,8
,1
,4
,7
.6
,7
.6
.6
,1
                                                                                            72.6
REGION

United  States
OECD Europe/Canada
OECD Pacific
Centrally  Planned Europe
Centrally  Planned Asia
Middle  East
Africa
Latin America
South and  East Asia

TOTAL
                                           TABLE B-30

                                     PRIMARY NUCLEAR SUPPLY
                                          (Exajoules/Yr)
                                 1985
                                 16.5
                                            2000
                                                        2025
                                                                    2050
                                             17.9
                                                        23.8
                                                                    26.2
                                                                                2075
                                                                                33.6
                                                                                            2100
3
8,
2,
2





.8
,4
.0
.0
.0 .
.0
.0
.0
.3
4,
7,
2,
2.





.2
.8
.6
.8
.1
.0
.0
.0
.4
==£3
5,
6,
2,
5,
2



1
.3
.2
.0
.5
.2
.7
.8
.0
.1
=sssst
5.
5.
1.
6.
2.
2.
1.

1,
,2
,3
.7
,2
.5
.1
,4
,0
.8
sxx:
6.
6.
2.
6.
3.
3.
2.

3.
0
,5
2
9
.4
3
0
,0
,3
=SiS=
6.
8.
2.
7.
4.
4.
2.

5,
8
0
8
3
3
,5
9
,3
,3:
                                                                                            42.2
 REGION                           1985

 United  States                      .1
 OECD  Europe/Canada                 .0
 OECD  Pacific                       .0
 Centrally  Planned Europe           .0
 Centrally  Planned Asia             .0
 Middle  East                     !   .0
 Africa                             .0
 Latin America                      .0
 South and^East  Asia               ..0

 TOTAL                             . 1
                                           TABLE B-31

                                       PRIMARY  SOLAR  SUPPLY
                                          (Exajoules/Yr)
                                             2000
                                              1.4
                                                        2025
                                                          6.5
                                                                    2050
                                                                                2075
                                                                     12.2
18.7
                                                                                            2100
.4
.3
.1
.5
/I
.0
.0
.0
.0
1.6
.8
.4
1.9
.8
.3
.3
.0
.4
2
1

3
1
1



.8
.4
.7
.3
.3
.1
.7
.0
.9
3.
2.
1.
4.
2.
2.
1.

2.
8
0
1
3
1
1
2
0
1
5
3
1
5,
3,
3.
2.

3.
.1
.0
.6
,4
,2
3
2
2
9
           27.9
                                                B-50

-------
                                                     Appendix B:  Implementation of the Scenarios
sew
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                           TABLE  B-32

                                   PRIMARY  ENERGY CONSUMPTION
                                         (Exajoules/Yr)
                               1985
                              300.2
                                           2000
                                                       2025
                                                                  2050
                                                                              2075
                                          365.1
                                                      459.1
                                                                  505.5
                                                                              574.4
                                                                                          2100
74
67.
19
71.
23
5
7
15
15
.9
.0
.3
.1
.8
.8
.6
.6
.1
82.
72.
21.
88.
35.
9,
11.
21.
22.
.1
7
,9
,7
.4
,0
,1
.9
.3
86.
72.
21.
105.
60.
17.
20.
36.
38.
7
4
.5
0
.4
.4
.9
.8
,0
84.
71.
22.
103.
70.
25.
30.
45.
52.
,2
.5
,1
.5
.6
.1
.7
,0
.8
85
74
25
106
82
32
44
52
71
.9
.4
.1
.2
.2
.0
.5
.3
.8
92.
81.
30.
114.
92.
39.
54.
54.
91.
.2
.9
.1
.3
.0
.5
.7
.8
.4
                                                                                          650.9
                                           TABLE  B-33

                     SECONDARY ENERGY CONSUMPTION:  FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                               1985
                              194.4
                                        FUEL  CONSUMPTION
                                           2000
                                                       2025
                                                                   2050
                                          232.9
                                                      286.5
                                                                  306.9
                                                                               2075
                                                                              323.8
                                                                                          2100
48.
42.
11.
44.
17.
3.
4.
11,
10.
.2
.4
.9
,6
.0
.9
.7
,3
,4
. 51.
45,
13.
54,
24,
6,
7,
15,
15,
.5
.5
.2
.7
.4
.0
.0
.6
.0
52,
44.
12.
65.
38.
11.
12,
24,
23,
.8
.6
.7
.0
.7
.2
.7
.9
.9
49.
42.
12.
63.
44.
15.
17.
27.
32.
.8
,2
.6
.9
5
.8
,9
.7
5
47,
41,
13,
.60,
47.
18.
23,
29,
42.
.3
.6
.5
.0
.6
.9
.5
.2
.2
46
42,
14
55
48
22
28,
28
51
.1
.7
.9
.9
.1
.7
.4
.2
.2
                                                                                          338.2
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                    ELECTRICITY CONSUMPTION
                               1985
                               32.9
                                           2000
                                           42.3
                                                       2025
                                                                   2050
                                                       57.1
                                                                   65.0
                                                                               2075
                                                                               78.1
                                                                                          2100
8,
8,
2,
8,
1,


1,
1
.4
.0
.4
.4
.8
.5
.8
.3
.3
10.
8.
2.
11.
3.

1.
2.
2,
,0
,9
,8
,0
,2
,9
,2
.1
.2
11.
9.
3.
13.
6.
2.
2.
' 3,
4,
.5
3
.0
,5
.9
,1
,5
.8
.5
	 11.
9.
3.
13.
8.
3.
3.
5,
6.
,7
7
.3
,3
.3
,3
,7
.1 •
.6
12.
10.
3,
14.
10,
4,
5,
6,
9,
.7
.8
.8
.0
.1
.8
,4
.6
.9
13.
12.
4.
14.
11.
6,
7.
7,
13,
,8
,1
,6
.1
.5
.2
.4
,4
.5
                                                                                           90.6
                                    TOTAL ENERGY CONSUMPTION
REGION                         1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                         227.3
                                           2000
                                          275.2
                                                       2025
                                                                   2050
                                                                               2075
                                                     '343.6
                                                                  371.9
                                                                              401.9
                                                                                           2100
56.
50,
14,
53.
18,
4,
5,
12,
11,
.6
.4
.3
.0
.8
.4
.5
.6
.7
61
54
16
65
27
6
8
17
17
.5
.4
.0
.7
.6
.9
.2
.7
.2
64.
53,
15,
78,
45,
13,
15,
28,
28
.3
.9
.7
.5
.6
.3
.2
.7
.4
61,
51,
15,
77,
52,
19
21,
32
39
.5
.9
.9
.2
.8
.1
.6
.8
.1
60,
52.
17,
74.
57,
23.
28,
35,
52.
.0
,4
.3
.0
7
.7
.9
.8
.1
59,
54
19,
70,
59,
28,
35,
35
64
.9
.8
.5
.0
.6
.9
.8
.6
.7
                                                                                          428.8
                                               B-51

-------
 1'olicy Options for Stabilizing Global Climate
.sew
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                           TABLE B-34

                                   SECONDARY OIL CONSUMPTION
                                         (Exajoules/Yr)
                               1985
                              100.6
                                           2000
                                                       2025
                                                                   2050
                                          116.2
                                                      128.1
                                                                  131.9
                                                                               2075
                                                                              147.6
                                                                                           2100
28.
25.
8.
14.
2.
3.
3.
8.
6.
.8
8
0
6
2
4
1
6
1
s 	
29.
27.
8.
19.
3,
5.
4
11.
7.
.9
.0
.4
.1
,0
.3
.2
.4
,9
28
24
7
21
4
9
6
15
9
.4
.9
.5
.7
.5
.0
.9
.6
.6
25.
22.
7
21.
6.
12
8
16
12,
.0
.2
.2
.1
. 4
.4
.8
.3
.5
24.
22.
7,
22,
9,
15,
11,
17
17,
.4
.3
,8
,2
.4
.0
.8
.5
.2
24
23,
9,
23.
14.
19.
15,
ie.
24.
.9
.8
.2
.9
.2
.0
,1
.1
.1
                                                                                          172.3
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South arid East Asia
TOTAL
                                           TABLE B-35

                                   SECONDARY GAS CONSUMPTION
                                         (Exajoules/Yr)
                               1985
                               48.8
                                           2000
                                           53.0
                                                       2025
                                                       65.9
                                                                   2050
                                                                               2075
                                                                   68.7
                                                                               62.7
                                                                                           2100
15.
10.
1.
17.



2.
1.
.6
,3
.3
.1
.3
.5
,4
1
,2
16,
10.
1
18.



2
1
.2
.3
.4
.8
.3
.7
.7
.9
.7
17,
10,
1,
23,

2,
1
6,
2,
.6
.4
.4
.8
.5
.2
.1
.0
.9
17.
10.
1.
23.

3.
1.
7.
3.
5
2
4
1
6
4
5
1
9
15,
9,
1,
19,

3,
1,
6,
4,
.3
.0
.4
.6
.5
.9
.6
.9
.5
13,
8,
1
16,

3
1
5
4,
.5
.3
.3
.2
.5
.7
.8
.8
.8
                                                                                           55.9
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                           TABLE B-36

                                  SECONDARY SOLIDS CONSUMPTION
                                          (Exajoules/Yr)
                               1985
                                           2000
                                                       2025
                                                                   2050
                                                                               2075
                                                                                           2100
3,
6,
2,
12,
14,

1,

3,
45,
.8
.3
.6
.9
.5
.0
.2
.6
.1
.0
5.
8.
3,
16.
21.

2.
1.
5.
63.
,4
2
.4
,8
1
,0
.1
,3
,4
,7
6.
9,
3,
19,
33,

4
3,
11
92
,8
.3
.8
.5
.7
.0
.7
.3
.4
.5
7
9,
4,
19
37

7
4
16
106
.3
.8
.0
.7
.5
.0
.6
.3
.1
.3
7
10
4
18
37

10
4
20
113
.6
.3
.3
.2
.7
.0
.1
.8
.5
.5
7
10,
4,
15
33,

11,
4,
22,
110,
.7
.6
.4
.8
.4
.0
.5
.3
.3
.0
                                                B-52

-------
                                                     Appendix B: Implementation of the Scenarios
sew
                                           TABLE  B-37

               RESIDENTIAL/COMMERCIAL ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                               1985
                               47.9
                                        FUEL  CONSUMPTION
                                           2000
                                           54.6
                                                       2025
                                                                  2050
                                                                              2075
                                                       69.6
                                                                   75.8
                                                                              77.0
                                                                                          2100
11.
12
1.
13,
it.


1.
2
.5
.9
.6
.2
.3
,2
.it
.6
.2
11.
13,
2.
15.
5,


2,
3,
,5
6
,0
,6
.it
.it
.9 .
1
,1
12,
13,
2.
23,
6
1,
2,
3,
5,
,3
.3
,0
,9
.8
.0
.2
.1
.0
12,
12
2.
23,
9.
1
3,
it.
7
.1
.6
,0
.1
.5
.5
,6
,0
.it
10,
11
1,
20,
11,
2
it.
it
9
.6
.it
.9
.3
.5
.0
.9
.5
.9
9
10
2
17
12
2
5
it
11
.6
.8
.0
.3
.it
.5
.9
.7
.9
                                                                                          77.1
                                    ELECTRICITY CONSUMPTION
REGION                         1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                          13.7
                                           2000
                                           17.6
                                                       2025
                                                       26.5
                                                                  2050
                                                                   30.3
                                                                              2075
                                                                              36.9
                                                                                          2100
5
it.
1
1





.2
.5
.1
.3
.2
.1
.3
.5
.5
6,
5.
1,
2,





,2
,0
,it
.2
.5
.2
.5
.8
.8
7.
5.
1.
it.
1.

1.
1.
1.
8
7
,7
7
.it
.7
.2
,5
,8
7.
5.
1.
it.
2.
1.
1,
2.
2.
,9
,9
,9
.6
,0
,1
,9
,1
9
8.
6.
2.
it.
2.
1.
2,
3.
it.
.it
.it
.2
,9
,8
,8
.9
,0
.5
9.
7,
2,
it.
3,
2.
it.
3.
6,
.0
,0
.7
.9
.7
.8
.0
.7
.5
                                                                                          44.3
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    TOTAL ENERGY CONSUMPTION

                               1985        2000         2025
                               61.6
                                           72.2
                                                                   2050
                                                                              2075
                                                       96.1
                                                                  106.1
                                                                             113.9
                                                                                          2100
16,
17,
2,
lit.
it.


2.
2,
:==
.7
.it
.7
.5
.5
.3
.7
.1
.7
=SSSi
17.
18.
3.
17.
5.

1.
2,
3.
===:===
,7
6
.it
,8
,9
,6
.it
9
,9
20.
19.
3,
28,
8,
1.
3,
>t.
6,
,1
.0
,7
.6
,2
,7
.it
.6
.8
20,
18.
3.
27.
11.
2,
5
6,
10.
,0
,5
.9
,7
.5
.6
,5
.1
.3
19,
17.
it.
25,
U.
3,
7,
7,
14,
.0
,8
.1
.2
.3
.8
.8
.5
.it
==SS=
18,
17.
4,
22,
16,
5,
9,
8,
18,
.6
.8
,7
.2
.1
.3
.9
.4
.4
S=s:
                                                                                         121.4
                                               B-53

-------
Policy Options for Stabilizing Global Climate
sew
                                           TABLE B-38

                     INDUSTRIAL ENERGY CONSUMPTION:  FUEL  VERSUS  ELECTRICITY
                                         (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                               1985
                               86.1
                                        FUEL CONSUMPTION
                                           2000
                                          107.3
                                                       2025
                                                                   2050
                                                                               2075
                                                      129.5
                                                                  U0.it
                                                                              137.5
                                                                                          2100
15
13
5
23
11
3
2
5
5.
.6
.9
.4
.7
.5
.0
.1
.5
.4
17,
15,
6,
27,
17,
it.
3,
8,
8,
,9
.2
,0
.3
.1
.5
.0
.0
.3
17,
13,
5,
25,
28,
8,
It.
13,
13,
.7
.1
.2
.it
.2
.1
.7
.4
,7
17
13
5
24
29
11
6
1*
17
.5
.0
.2
.7
.5
.5
.8
.6
.6
16,
12,
5,
21.
27,
12,
a.
13,
20
.2
.7
.3
.5
.it
.0
.2
.8
.it
15.
12.
'5.
18.
22.
11.
9,
11.
20,
. 1.
,6
,3
,1
,2
,1
.1
,3
.9
                                                                                          125.7
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    ELECTRICITY CONSUMPTION
                               1985
                               19.2
                                           2000
                                                       2025
                                                                   2050
                                           24.7
                                                       30.6
                                                                   34.5
                                                                               2075
                                                                               40.7
                                                                                           2100
3.
3.
1.
7.
1,




,2
.5
.3
.1
.6
.4
.5
.8
.8
3
3,
1
8
2


1
1
.8
.9
.4
.8
.7
.7
.7
.3
.4
3.
3.
1.
8.
5.
1.
1.
2.
2,
.7
,6
.3
.8
,5
.4
.3
.3
.7
3
3,
1,
8
6,
2
1
3
3
.8
.8
.4
.7
.1
.2
.8
.0
.7
4,
4.
1.
9,
7,
3,
2,
3
5
.3
.4
.6
.1
.0
.0
.5
.6
.2
4.
5.
1.
9.
7.
3,
3.
3,
6.
,8
.1
.9
.2
.3
.4
.4
.7
.7
                                                                                           45.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    TOTAL ENERGY CONSUMPTION
                               1985
                              105.3
                                           2000
                                          132.0
                                                       2025
                                                                   2050
                                                                               2075
                                                      160.1
                                                                  174.9
                                                                              178.2
                                                                                           2100
18.
17.
6.
30.
13.
3.
2.
6.
6.
3SKS=
,8
,4
,7
,8
.1
,4
,6
.3
,2
21.
19,
7,
36.
19.
5,
3,
9.
9,
.7
,1
.4
.1
.8
.2
.7
.3
.7
21
16
6
34
33
9
6
15
16
.4
.7
.5
.2
.7
.5
.0
.7
.4
SS35S5S
21.
16.
6.
33.
35.
13.
8.
17.
21.
,3
.8
,6
,4
,6
.7
.6
.6
.3
20.
17,
6,
30,
34,
15,
10,
17
25
.5
.1
.9
.6
.4
.0
.7
.4
.6
19,
17,
7,
27,
29,
14,
12,
15,
27
,9
.7
.2
.3
.5
.5
.5
.0
.6
171.2
                                               B-54

-------
                                                     Appendix B:  Implementation of the Scenarios
 SCH
                                           TABLE B-39

                   TRANSPORTATION ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION
                                1985
                                        FUEL CONSUMPTION

                                           2000        2025
                                                                   2050
 REGION
 United  States
 OECD Europe/Canada
 OECD Pacific
 Centrally  Planned Europe
 Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East Asia
                                    ELECTRICITY CONSUMPTION
 1985
======
   .0
   .0
   .0
   .0
   .0
   .0
   .0
   .0
   .0
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2025

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2050

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .0
                                                                               2075
2075

  .0
  .0
  .0
  .0
  .3
  .0
  .0
  .0
  .2
                                                                                           2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
21.
15
4.
7
1

2
A
2
60
.1
.6
.9
.7
.2
.7
.2
.2
.8
.4
22.
16.
5,
11,
1,
1
3,
5.
3.
71.
.1
.7
,2
,8
.9
.1
,1
,5
.6
.0
22,
18.
5,
15,
3,
2,
5,
8,
5
87,
,8
.2
.5
,7
.7
.1
.8
.4
.2
.A
20
16
5
16
5
2
7
9
7
90
.2
.6
.4
.1
.5
.8
.5
.1
.5
.7
20.
17.
6.
18.
8.
4.
10.
10,
11.
109.
5
.5
.3
2
,7
.9
.4
.9
.9
.3
21.4
19.3
7.6
20.5
13.5
9.1
13. A
12.2
18.4
135.4
2100

  .0
  .0
  .0
  .0
  .5
  .0
  .0
  .0
  .3
 TOTAL
 REGION
 United  States
 OECD  Europe/Canada
 OECD  Pacific
-Centrally  Planned Europe
 Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East  Asia

 TOTAL
                                     TOTAL ENERGY CONSUMPTION

                                1985         2000        2025
                                60.A
                                            71.0
                                                                   2050
                                                                               2075
                                                        87.4
                                                                   90.9
                                                                              109.8
                                                                                           2100
21.
15.
A.
7,
1.

2.
4,
2,
SSSS
.1
.6
.9
7
.2
7
.2
,2
.8 •
22
16.
5.
11.
1,
1,
3
5
3
.1
.7
.2
.8
.9
.1
.1
.5
.6
22,
18,
5,
15
3,
2,
5
8
5
===
.8
.2
.5
.7
.7
.1
.8
.4
.2
20,
16,
5,
16,
5.
2.
7.
9
7.
,2
,6
,4
.1
.7
,8
,5
.1
.5
20
17
6
18
9
4
10
10
12
.5
.5
.3
.2
.0
.9
.A
.9
.1
21
19
7
20
14
9
13
12
18
.4
.3
.6
.5
.0
.1
.4
.2
.7
                                                           136.2
                                                B-55

-------
 Policy Options for Stabilizing Global Climate
sew
                                           TABLE B-40

                              ELECTRIC UTILITY ENERGY CONSUMPTION
                                         (Exajoules/Yr)
REGION
                               1985
                                           2000
                                                       2025
                                                                   2050
                                                                               2075
TOTAL
                              105.3
                                          131.9
                                                      168.5
                                                                  185.2
                                                                              215.2
                                                                                           2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
26
24
7
26
6
1
2
4
4
.6
.6
.4
.4
.8
.9
.7
.3
.6
30
27
8
34
11
2
4
6
7
.5
.1
.7
.0
.0
.9
.1
.3
.3
33.
27.
8.
39.
21.
6.
7.
11,
13.
3
4
6
.2
,2
,0
.8
.3
.7
32.
27,
9,
37,
23
9
10
15
19
,7
,8
,1
.2
.9
.3
.8
.3
.1
34.
30.
10.
37.
28,
13,
14.
19
27
1
1
4
3
.0
.1
.9
.8
.5
36.8
33.9
12.5
37.8
31.8
16.7
20.3
22.0
36.9
                                                                                          248.7
                                           TABLE B-41

                 ENERGY CONVERSION EFFICIENCY AT ELECTRIC UTILITY FOWERPLANTS*
                                            (percent)
REGION
                               1985
                                           2000
United 'States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
* Includes transmission and distribution losses
                                                       2025
                                                                   2050
                                                                               2075
                                                                                           2100
31.2
32:.5
32.4
31.4
26.5
26.3
22.2
30,. 2
26.1
32.5
32.5
32.2
' 32.4
29.1
27.6
29.3
33.3
30.1
34.2
33.6
33.7
34.2
32.5
31.7
32.1
33.6
32.8
35.5
35.3
36.3
36.0
33.9
35.5
35.2
33.3
34.6
37.2
35.9
37.5
37.3
36.1
36.6
36.2
33.3
35.6
37.2
36.0
36.0
37.3
36.5
37.1
36.5
33.2
36.3
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                                           TABLE B-42

                              SYNTHETIC PRODUCTION OF OIL AND GAS
                                         (Exajoules/Yr)
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                       OIL FROM SYNFUELS

                                           2000        2025
                                                                   2050
                                                                               2075
                                                                                           2100
.4
.2
.1
.7
.7
.0
.1
.0
.2
2.


A.
3.

1.
1.
1.
3
8
.6
1
.2 .
,0
,5
,9
1
8.
4.
2.
16.
12.

3.
3,
2.
.3
,9
.3
,3
,0
.0
.3
.7
.2
16
9
4
38
21

4
4
2
.9
.8
.7
.4
.8
.0
.9
.2
.3
TOTAL
                                                        2.4
                                                                   15.5
                                                                               53.0
                                                                                          103.0
REGION                         1985
United States                    .0
OECD Europe/Canada               .0
OECD Pacific                     .0
Centrally Planned Europe         .0
Centrally Planned Asia           .0
Middle East                      .0
Africa                           .0
Latin America                    .0
South and East Asia              .0

TOTAL                            . 0
                                       GAS FROM SYNFUELS
                                           2000
                                             .0
                                                       2025
                                                        5.5
                                                                   2050
                                                                   12.9
                                                                               2075
                                                                               16.2
                                                                                           2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
.4
.3
.2
.8
.4
.0
1.1
• 1.6
.7
1.


1.


2.
3.
1.
0
7
4
9
9
0
5
8
7
1.


2.
1.

3.
4.
2.
.3
9
5
5
.3
0
.1
,6
,0
2.
1.

4.
2.

4.
6.
• 3.
,4
6
.8
.8
,4
.0
.6
,7
,0
                                                                                           26.3
                                               B-56

-------
                                                     Appendix B: Implementation of the Scenarios
sew
                                           TABLE B-43

                      ENERGY USED FOR SYNTHETIC FUEL PRODUCTION BY TYPE
                                         (Exajoules/Yr)
REGION                         1985

United States                    .0
OECD Europe/Canada               ,0
OECD Pacific                     .0
Centrally Planned Europe         .0
Centrally Planned Asia           .0
Middle East                      .0
Africa                           .0
Latin America                    .0
South and East Asia              .0

TOTAL                            .0
                                            COAL
                                           2000
                                             .0
                                                      2025
                                                                  2050
                                                        4.0
                                                                   16.1
                                                                              2075
                                                                              67.7
                                                                                          2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
.7
.4
.2
1.1
1.1
.0
.2
.0
.3
2.
1,

4.
4

1


.8
.6
.7
.7
.3
.0
.1
.2
.7
11.
6.
3.
22.
17.

5.

1,
.2
.4
.0
.1
.3
.0
.3
9
.5
24.
14.
6.
56.
33.

6,
1,
2.
.7
,1
,7
,7
,1
,0
,2
.5
.4
                                                                                         145.4
REGION                         1985
TOTAL
United States                    .0
OECD Europe/Canada               .0
OECD Pacific                     .0
Centrally Planned Europe         .0
Centrally Planned Asia           .0
Middle East                      .0
Africa                           .0
Latin America                    .0
South and East Asia              .0
                                           BIOMASS
                                           2000
                                                       2025
                                                                  2050
                                                        7.4
                                                                   25.7
                                                                              2075
                                                                              36.8
                                                                                          2100
0
0
0
0
0
0
0
0
0



1.


1
2
1
.6
.4
.2
.1
.5
.0
.4
.2
.0
2.
1.

3.
1.

5.
7,
3,
.1
,5
7
.8
.8
,0
,0
.5
.3
2
2
1
5
2

7
10
4
.9
.1
.1
.5
.6
.0
.2
.7
.7
3.
2.
1.
7.
3,

9.
13,
6,
.8
.7
,4
,1
.3
,1
,3
.9
.1
                                                                                          47.7
REGION                         1985

United States                    .0
OECD Europe/Canada               .0
OECD Pacific                     .0
Centrally Planned Europe         .0
Centrally Planned Asia           .0
Middle East                      .0
Africa                           .0
Latin America                    .0
South and East Asia              .0

TOTAL
                                             TOTAL

                                           2000
                                                       2025
                                                                   2050
                                                                              2075
                                                                   41.8
104.5
                                                                                          2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
1.


2.
1.

1.
2.
1.
3
8
4
2
6
0
.6
.2
.3
4
3
1
8
6

6
7
4
.9
.1
.4
.5
.1
.0
.1
.7
.0
14.
8.
4.
27.
19.

12.
11.
6,
.1
,5
.1
.6
.9
,0
.5
.6
.2
28.
16,
8.
63.
36.

15,
15,
8,
,5
,8
,1
.8
,4
,1
.5
.4
.5
=ss:
            193.1
                                               B-57

-------
Policy Options  for. Stabilizing (Ilobal Climate
sew
                                           TABLE B-44

                                C02 EMISSIONS FROM FOSSIL FUEL
                                        (Petagrams C/Yr)
REGION
                               1985
                                           2000
                                                       2025
                                                                   2050
                                                                               2075
TOTAL
                                5.1
                                            6.2
                                                        7.6
                                                                    7.9
                                                                                9.0
                                                                                          2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned
Centrally Planned
Middle East
Africa
Latin America



Europe
Asia



South and East Asia
1.3
.9
.3
1.3
.6
.1
.1
.2
.3
1.4
1.0"
.It
1.6
.8
.1
.2
.3
.4
1
1

1
1




.5
.0
.it
.8
.2
.3
.4
.It
.6
1.
1.

1.
1.




4
.0
.4
7
.3
.4
.It
.5
,8
1.
1.

1.
1,



1.
A
.1
. 4
.8
.6
.5
.6
,5
,1
1
1

2
' 1



1
.6
.2
.5
.1
.7
.6
.7
.5
.3
                                                                                           10.
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                           TABLE B-45

                                 CO EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams C/Yr)
                               1985
                              185.8
                                           2000
                                                       2025
                                                                   2050
                                          188.3
                                                      249.5
                                                                  273.6
                                                                               2075
                                                                              342.7
                                                                                          2100
51
it>t
14
31
6
2
8
16
11
.0
.7
.1
.1
.0
.9
.5
.3
.2
29
38
11
47
9
4
12
21
14
.2
.2
.9
.1
.1
.3
.3
.6
.4
30
41
12
62
17
8
22
32
21
.3
.5
.6
.8
.1
.3
.9
.9
.2
26.
38.
12.
64.
24.
11.
29.
35.
30.
.9
.1
,4
.3
.6
,1
.8
,7
7
27.
40.
14.
72.
37.
19.
41.
42.
48.
,3
,2
.4
,3
.3
,3
,3
7
.0
28.
44.
17.
81.
55.
35.
53.
48.
73.
=_:
.5
,1
.2
,2
.9
.6
. 1
.0
.6
                                                                                          437.2
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                           TABLE B-46

                                NOx EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams N/Yr)
                                1985
                                24.2
                                            2000
                                                        2025
                                                                    2050
                                                                               2075
                                            27.9
                                                        32.9
                                                                    34.1
                                                                               37.9
                                                                                           2100
6.
4,
1,
5.
2.


1.
1
.1
.6
.7
.8
.6
.4
.8
.0
.3
5.
4,
1.
7,
3.

1,
1,
'1,
,8
.7
,7
.0
.8
.5
.2
,3
.8
5.
4.
1,
7,
5.
1,
2,
2,
2.
4
.7
.7
.4
.7
.0
,0
2
.8
4.
4.
1.
7.
6.
1.
2.
2.
3.
8
.4
7
0
1
3
6
5
7
4.
4
1
7.
6.
1
3,
• 2,
5,
.8
.6
.9
.0
.6
.7
.4
,8
.1
5.
5
2.,
7
7.
2
4,
' 3
6
.0
.0
.1
.1
.0
.5
.2
.1
.8
                                               B-58

-------
                                                     Appendix B: Implementation of the Scenarios
ROW
                                          TABLE  B-47

                                    PRIMARY  ENERGY  SUPPLY
                                        (Exajoules/Yr)
REGION
                           198;
                                       2000
                                                   20Z5
                                                              2050
                                                                          2075
TOTAL
                          301.6
                                      403.6
                                                  646.2
                                                             926.6
                                                                        1209.6
                                                                                      210D
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
63.
47.
8.
81.
25.
23.
16.
20.
14.
7
6
9
2
6
7
3
5
1
63
55
13
99
46
52
26
25
20
.2
.6
, it
.9
.0
.8
.7
.6
.4
80
66
17
148
114
75
49
62
32
.0
.5
.0
.3
.3
.0
.9
.3
.9
110
74
24
243
181
89
64
93
45
.7
.0
.6
.5
.7
.0
.2
.2
.7
196
91
44
395
183
66
66
94
71
.4
.7
.1
.9
.2
,4
.7
.1
.1
305,
110,
70.
472,
209.
51,
71.
91,
102,
ss=:
7
3
,D
.0
.7
,3
.6
,1
,3
                                                                                    1484.0
REGION
                           1985
                                          TABLE  B-48

                                      PRIMARY OIL  SUPPLY
                                        (Exajoules/Yr)
                                       2000
                                                   2025
                                                              2050
TOTAL
                          117.9
                                      135.1
                                                  156.5
                                                              143.9
                                                                          2075
                                                                         112.4
                                                                                      2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
g~.Ma
20,
11,
1,
26.
5.
22.
10.
14,
5.
soffl
.8
9
1
. 0
2
,4
,8
,1
.6
12
9

22
6
49
17
11
4
.2
.8
.6
.3
.9
.3
.4
.9
.7
9
8

18
7
58
22
27
4
.7
.7
.2
,4
.2
.3
.3
.5
.2
10,
6.

12
5
45
18
41
3
.4
.4
.0
.8
.2
.5
.4
.9
.3
18,
3,

8.
4.
29,
13.
31,
2,
EZD
,4
9
,2
.8
,0
,6
.2
,5
.8
iLjiuim.g3.-n
26.2
2.3
.2
6.4
3.4
18.5
9.5
19.2
2.5
                                                                                      88,2
REGION                     1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                      58.6
                                          TABLE  B-49

                                      PRIMARY GAS  SUPPLY
                                        (Exajoules/Yr)
                                       2000
                                       78.7
                                                   2025
                                                              2050
                                                   97.5
                                                              100.1
                                                                          2075
                                                                          60.2
                                                                                      2100
16,
9,

24,

1,
1,
2,
2,
.3
.7
.7
.0
.5
.2
.3
,5
.4
16,
12,
1,
31.
2,
3.
3.
5,
3,
,0
.4
.8
.2
,1
.3
.2
,7
.0
12,
11,
1
31,
4
14
6
10,
4
,6
.8
.7
,7
.6
.1
.3
.5
.2
8.
8,
1
24,
4,
34,
7
7
2
,8
,4
.1
.6
.2
.8
.8
.5
.9
6
5

12
2
21
5
4
1
.4
.5
.5
.6
.0
.6
.7
.1
,8
Z
3

5
1
10
3
2

.2
.1
.3
.0
.0
.a
.4
.0
.9
                                                                                      28.7
REGION
                           1985
                                          TABLE B-50

                                     PRIMARY COAL SUPPLY
                                        (Exajoules/Yr)
                                       2000
                                                   2025
                                                              2050
TOTAL
                           87.3
                                      136.6
                                                  275.3
                                                              467.2
                                                                          2075
                                                                         713.7
                                                                                      2100
United States
OECD Europe /Can ad a
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
19.
9.
3.
26.
18.

4.

4,
.4
,4
,9
7
.9
.0
o
.6
s.
25,
14
6
39,
34

5,
1
9
.9
.4
.5
.4
.3
.0
.6
.1
.4
42
23
10
83
86

14
3
11
.4
.9
.3
.2
.6
.0
.8
.1
.0
70.
33,
16.
177.
139,

19.
3.
7.
.0
,5
,8
.4
1
,0
.6
.8
.0
144,
51.
34,
331,
123.

17,
3,
8,
-laa—gai
,1
.1
,2
.6
.2
,0
,8
,5
,2
244.5
68.8
58.0
404.8
130.8
.0
19.3
3.8
10.4
wi-TfnfMiiHpaBi
                                                                                     940.4
                                               B-59

-------
Policy Options for Stabilizing Global Climate

RCW
                                          TABLE B-51

                                    PRIMARY BIOMASS SUPPLY
                                        (Exajoules/Yr)
REGION
                           1985
                                       2000
                                                   2025
                                                               2050
TOTAL
                                                   13.A
                                                               A3. 8
                                                                           2075
                                                                           61.7
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
1.


2.


2.
3.
1.
1
8
A
0
9
0
6
9
7
3
2
1
6
3

8
' 12
5
.5
.5
.3
.5
.1
.0
.5
.8
.6
A.
3.
1.
9
A,

12.
18.
7.
.9
,5
.8
.2
.3
.1
.0
.0
.9
5.
3.
2.
10.
A.

13,
19.
8.
A
9
.0
1
.8
.2
.3
.9
.7
                                                                                       68.3
REGION
                           1985
                                          TABLE B-52

                                 PRIMARY HYDROELECTRIC SUPPLY
                                        (Exajoules/Yr)
                                       2000
                                                   2025
                                                               2050
TOTAL
                           21.2
                                       30.2
                                                   A8.7
                                                               63.1
                                                                           2075
                                                                           70.0
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
3
8
1
2
1


3
1
.3
.2
.2
.5
.0
.1
.2
.3
.A
3
9
1
3
2


6
2
.8
.6
.3
.1
.3
.2
.A
.9
.6
A,
10.
1.
3.
6,

1.
1A.
5.
.3
.6
,3
.6
,A
A
.3
.9
.9
A
11
1
3
10

3
19
9
.6
.0
.A
.7
.0
.6
.2
.2
.A
A
11
' 1
3
11

5
20
11
.7
.1
.A
.7
.3
.7
.3
.A
.A
A.
11.
1.
3.
11.

6.
20.
12.
8
1
A
7
6
7
6
6
1
                                                                                       72.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
1985
3.
8.
2.
2,





.8
,A
.0
,0
,0
.0
,0
,0
.3
2000
A. 8
9.1
3.0
3. A
.2
.0
.1
.0
.6
TOTAL
                           16.5
                                          TABLE B-53

                                    PRIMARY NUCLEAR SUPPLY
                                        (Exajoules/Yr)

                                                   2025        2050
                                                    7.6
                                                    9. A
                                                    2.6
                                                    7.0
                                                    6. A
                                                    1.5
                                                    1.8
                                                    1.7
                                                    A. 3
                                                   A2.3        72.6
                                                                           2075
                                                                                       2100
                                       21.2
                                                                          120.3
                                                                                      167.9
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin. America
South and East Asia

TOTAL
                           1985
                                          TABLE B-5A

                                     PRIMARY SOLAR SUPPLY
                                        (Exajoules/Yr)
                                       2000
                                                   2025
                                        1.8
                                                   12.5
                                                               2050
                                                                           2075
                                                               35.9
                                                                           71.3
                                                                                       2100
.5
.3
.2
.5
.2
.0
.0
.0
.1
2.
1.

2.
2.



1,
3
.3
5
,A
.2
,7
.8
,7
,6
A,
2.
1,
6.
7
2
2
2
6
.7
.6
.2
.A
.0
.8
.3
.8
.1
6.
A.
2.
11,
1A,
5,
A,
6,
15
.9
.0
,0
.6
.8
.6
.9
.A
.1
9.
5,
3.
17,
2A,
9.
8,
10,
28,
,6
,7
.0
,9
,7
.0
,3
,9
.8
                                                                                      117.9
                                               B-60

-------
                                                     Appendix B: Implementation of the Scenarios
RCW
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE  B-55

                                  PRIMARY ENERGY CONSUMPTION
                                        (Exajoules/Yr)
                            1985
                           300.2
                                        2000
                                       404.2
                                                    2025
                                                               2050
                                                   647.7
                                                               926.1
                                                                           2075
                                                                         1209.9
                                                                                       2100
7A.
67.
19,
71.
23.
5,
7,
15,
15,
9
,0
,3
. 1
.8
,8
. 6
.6
,1
85.
76,
2A,
96,
A3,
9,
1A
27.
28
.8
.6
.0
.0
.A
.A
.0
.0
.0
102
88
25
115
110
27
37
68
72
.7
.3
.5
.7
.3
.7
.5
.0
.0
112,
96,
31
162
176,
A5
63
105
132
.7
.0
.6
.2
.1
.A
.6
.8
.7
128.
103.
38.
221.
230.
61.
85.
133.
207.
7
1
6
6
5
A
1
9
0
157.
113.
48.
272.
274.
75.
IDA.
155.
283.
I—;
A
9
1
1
0
0
0
5
9
                                                                                     1483.9
                                          TABLE B-56

                    SECONDARY ENERGY CONSUMPTION:  FUEL  VERSUS  ELECTRICITY
                                        (Exajoules/Yr)
                                       FUEL CONSUMPTION
REGION
                            1985
                                        2000
                                                    2025
                                                                2050
TOTAL
                           194.4
                                       251.0
                                                   369.9
                                                               480.5
                                                                           2075
                                                                          540.9
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
48
42
11
44
17
3
4
11
10
.2
.4
.9
.6
.0
.9
.7
.3
.A
52
47
14
57
28
6
8
18
17
.7
.2
.2
.5
.6
.1
.5
.5
.7
57.7
52.6
14.9
66.0
60.9
16.5
21.3
42.0
38.0
58.4
52.9
16.9
82.6
88.0
25.6
32.7
57.7
65.7
55,
50
17,
90,
99
32
39
65
90,
.5
.7
.5
.4
.9
.1
.A
.1
.3
56
51
18
98
104
36
43
70
112
.2
.7
.7
.5
.6
.9
.2
.7
.7
                                                                                      593.2
REGION                      1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                       32.9
                                   ELECTRICITY CONSUMPTION
                                        2000
                                        49.0
                                                    2025
                                                               2050
                                                     3.5
                                                               137.9
                                                                           2075
                                                                          201.0
                                                                                       2100
8.
8.
2.
8.
1.


1.
1.
,4
,0
.A
.A
,8
,5
.8
,3
,3
10
9
3
12
A
1
1
2
3
.9
.6
.1
.6
.2
.0
.7
.8
.1
1A,
11,
3,
15,
15,
3,
A,
a:
10
.7
.7 .
.5
.7
.1
.8
.8
.3
.9
16,
13,
A,
22,
26,
7,
8,
15,
23,
.9
,6
.6
.A
.2
.0
,7
.A
.1
s=s=
19.
15.
5.
30.
Al.
10.
1A.
22.
Al.
0
8
,8
,3
,0
,6
,0
,8
,7
==±=
20.
17.
6.
36.
52.
13.
18.
28.
61.
7
5
8
5
8
8
7
A
1
                                                                                      256.3
REGION
                            1985
                                    TOTAL ENERGY CONSUMPTION

                                        2000        2025
                                                                2050
                                                                           2075
TOTAL
                           227.3
                                       300.0
                                                   AS'S.A
                                                               618.A
                                                                           7A1.9
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
56,
50,
1A,
53
18
A
5
12,
11
.6
.A
.3
.0
.8
.A
.5
.6
.7
63.
56.
17.
70.
32.
7.
10.
21.
20.
,6
,8
,3
,1
,8
,1
,2
,3
,8
72.
6A.
18.
81.
76.
20.
26.
50.
AS,
A
,3
,A
,7
,0
,3
,1
.3
,9
75.
66.
21.
105.
11A.
32.
Al.
73.
88.
3
,5
5
,0
,2
,6
,A
,1
,8
7A.
66.
23.
120.
1AO.
A2.
53.
87.
132.
5
5
3
7
9
7
A
9
0
76.9
69.2
25.5
135.0
157. A
50.7
61.9
99.1
173.8
                                                                                      8A9.5
                                               B-61

-------
Policy Options for Stabilizing Global Climate
RCW
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                            1985
TOTAL
                           100.6
                                           TABLE B-57

                                   SECONDARY OIL CONSUMPTION
                                         (Exajoules/Yr)
                                        2000
                                       120.4
                                                    2025
                                                                2050
                                                   161.4
                                                               209.7
                                                                            2075
                                                                           259.3
                                                                                        2100
28,
25.
8.
14.
2.
3.
3.
8.
6.
:=s:=
=s==
g
.8
.0
.6
.2
.4
.1
.6
.1
=====
=====
29.
26,
8,
20,
3.
5,
4,
13
8
S====
.1
.9
.8
,0
.4
.3
.9
.1
.9
sssssss
29,
29,
9,
25,
7,
12.
11,
24,
13,
S===
.3
,1
.2
,3
.2
.7
,2
.0
.4
29,
28,
10,
32,
13.
19.
16,
34,
25.
,4
,7
,1
,3
.6
.9
.4
.1
.2
29.
28,
10,
38,
23.
25.
20.
41.
41.
,3
.1
.7
.5
.6
.9
.4
.4
.4
=====
30.
30,
11.
46.
37,
30,
24,
47,
62,
,9
.2
,9
,7
,7
,5
.2
.9
.0
                                                                                       322.0
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                            1985
                            48.8
                                           TABLE B-58

                                   SECONDARY GAS CONSUMPTION
                                         (Exajoules/Yr)
                                        2000
                                                    2025
                                                                2050
                                        57.7
                                                    79.4
                                                                93.4
                                                                            2075
                                                                            94.0
                                                                                        2100
fSK=S=
15.
10.
1.
17.



2,
1,
sssss
.6
.3
,3
,1
,3
.5
,4
.1
.2
======
17.
11.
1.
19.



3.
2.
.4
.2
.6
.6
.4
.8
.8
.8
.1
=======
19.
12.
1,
22,

3,
1,
12,
5,
.7
,4
.5
,3
,8
.8
.8
.'0
.1
19,
11.
1,
27,
1.
5,
2.
15.
8.
.3
.8
.8
.1
.2
.7
.6
.5
.4
SS===S=
16
10.
1
28.
1
6
3
15
11
=====
.8
.2
.6
.1
.4
.1
.0
.8
.0
16.
9.
1.
30.
1.
6.
3.
16.
13.
4
8
6
0
6
3
5
3
8
                                                                                        99.3
REGION                      1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                       45.0
                                           TABLE B-59

                                  SECONDARY SOLIDS CONSUMPTION
                                         (Exajoules/Yr)
                                        2000
                                        72.9
                                                    2025
                                                                2050
                                                                            2075
                                                   129.1
                                                               177.4
                                                                           187.6
                                                                                        2100
3
6
2
12
14

1

3
.8
.3
.6
.9
.5
.0
.2
.6
.1
6.
9,
3.
17.
24.

2,
1.
6,
.2
,1
,8
.9
.8
,0
.8
.6
.7
8,
11.
4,
18,
52,

8,
6.
19.
.7
,1
.2
.4
.9
.0
.3
.0
.5
9.
12,
5,
23.
73,

13,
8,
32,
.7
.4
.0
.2
.2
.0
.7
.1
.1
9
12.
5.
23
74.

16
7.
37
.4
.4
.2
,8
.9
.1
.0
.9
.9
8
11
5
21
65

15
6
36
.9
.7
.2
.8
.3
.1
.5
.5
.9
                                                                                       171.9
                                               B-62

-------
                                                    Appendix B:  Implementation of the Scenarios
RCW
                                          TABLE B-60

               RESIDENTIAL/COMMERCIAL ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
                                       FUEL CONSUMPTION
REGION
                            1985
                                       2000
                                                   2025
                                                               2050
TOTAL
                            47.9
                                       56.4
                                                   76.0
                                                               99.9
                                                                           2075
                                                                          113.2
                                                                                      2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
11.
12.
1.
13.
4.


1.
2.
5
.9
6
2
3
2
4
6
2
11.
14.
2
15,
6.

1
2
3.
.6
.6
.2
.0
,1
,4
.0
.3
.2
13.
17.
2.
20.
9.
1.
2.
4.
5.
1
5
3
4
4
5
3
1
4
12.
16.
2.
25.
17.
2.
4.
7.
10.
9
5
7
,6
7
7
2
0
6
11.
14.
2.
27,
23,
3.
5.
9.
15.
.4
5
.7
,3
.7
,8
.5
.0
.3
10.9
13.5
2.8
28.4
25.8
4.5
6.1
10.4
18.2
                                                                                      120.6
REGION
                            1985
                                    ELECTRICITY CONSUMPTION
                                       2000
                                                   2025
                                                               2050
                                                                           2075
TOTAL
                            13.7
                                        19.7
                                                   37.3
                                                               56.4
                                                                           81.8
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
5.2
4.5
1.1
1.3
.2
.1
.3
.5
.5
6.
5.
1.
2.



1.
1.
,6
4
.5
7
.5
2
7
.0
.1
10.
7.
2.
6.
2.
1.
2.
2.
3.
1
8
0
1
.0
1
0
4
.8
11
8
2
8
4
2
3
5
8
.4
.6
.7
.8
.5
.3
.9
.3
.9
12.
9.
3,
11.
8,
4.
6.
9,
17.
.4
.4
,3
.7
,5
,0
:s
.0
.0
13.
10.
3.
13.
12.
5.
8,
12.
26.
.2
.0
.8
,9
,9
.9
.9
.5
.1
                                                                                      107.2
REGION
                            1985
                                    TOTAL ENERGY CONSUMPTION
                                       2000
                                                   2025
                                                               2050
TOTAL
                            61.6
                                        76.1
                                                  113.3
                                                              156.3
                                                                           2075
                                                                          195.0
                                                                                       2100
United States
OECD Europe/Canada
,OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
16
17
2
14
4


2
2
.7
.4
.7
.5
.5
.3
.7
.1
.7
18,
20,
3.
17.
6,

1.
3.
4,
=====
.2
,0
.7
.7
.6
.6
.7
.3
.3
23
25
4
26
11
2
4
6
9
===
.2
.3
.3
.5
.4
.6
.3
.5
.2
24
25
5
34
22
5
8
12
19
.3
.1
.4
.4
.2
.0
.1
.3
.5
23,
23,
6.
39,
32,
7,
12,
18,
32,
;=:=
.8
,9
.0
.0
,2
.8
.0
.0
.3
24.1
23.5
6.6
42.3
38.7
10.4
15.0
22.9
44.3
                                                                                      227.8
                                               B-63

-------
Policy Options for Stabilizing Global Climate
RCW
                                           TABLE  B-61

                     INDUSTRIAL ENERGY CONSUMPTION:  FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                            1985
TOTAL
                            86.1
                                        FUEL CONSUMPTION
                                        2000
                                       122.0
                                                    2025
                                                                2050
                                                                            2075
                                                   182.6
                                                               233.3
                                                                           240.3
                                                                                        2100
15.
13.
5.
23.
11.
3,
2,
5.
5,
6
9
A
7
5
,0
,1
. 5
,A
20,
16,
6,
29,
20
A
3
10
10
.0
.1
.6
.5
.A
.7
.9
.2
.6
20.
13.
5.
25.
A5.
12,
9.
25.
25,
9
5
5
0
7
A
,2
,3
.1
21,
14
6
30
58
18
1A
31
39
.A
.5
.2
.1
.2
.0
.2
.A
.3
19
14
6
30
5A
20
16
31
' 46
.9
.5
.3
.6
.6
.2
.2
.2
.8
19,
14,
6,
29,
43,
19,
15
28
48
.A
,2
,3
,5
.3
.6
.9
.A
.0
                                                                                       22A . 6
REGION                      1985
United States
OECD Europe/Canada
OECD Pacific       ;
Centrally Planned Europe
Centrally Planned Asia
Middle 'East
Africa
Latin America
South and East Asia
TOTAL                       19.2
                                    ELECTRICITY CONSUMPTION

                                        2000        2025
                                                                2050
                                        29.3
                                                    51.0
                                                                80.9
                                                                            2075
                                                                           117.8
                                                                                        2100
3,
3,
1
7
1




.2
.5
.3
.1
.6
.A
.5
.8
.8
4,
A,
1,
9,
3,

1
1,
2
.3
,2
.6
.9
.7
.8
.0
.8
.0
A.
3.
1.
9.
12.
2,
2,
5,
7,
6
9
,5
,6
,9
,7
,8
,9
,1
5,
5
1
13
21
A
A
10
1A
,5
.0
.9
.6
.3
.7
.8
.1
.0
6
6
2
18
31
6
7
13
24
=====±!
.6
.A
.5
.6
.6
.6
.5
.8
.2
=====
7.
7.
3.
22,
38.
7.
9.
15.
3A.
:s=ss=:ss
,5
,5
,0
.6
,3
,9
,8
,8
2
ss:;
                                                                                       1A6.6
REGION
                            1985
                                   TOTAL ENERGY CONSUMPTION
                                        2000
                                                    2025
                                                                2050
TOTAL
                           105.3
                                       151.3
                                                   233.6
                                                               31A.2
                                                                            2075
                                                                           358.1
                                                                                        2100
^United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
18.
17.
6.
30.
13.
3.
2.
6,
6.
==S=
8
A
7
.8
.1
4
,6
,3
.2
2A.
20,
8,
39,
2A
5,
A,
12,
12
.3
,3
.2
.A
.1
.5
.9
.0
.6
=S=KS
25.
17.
7.
3A.
58.
15.
12.
31.
32,
5
A
0
,6
6
1
0
,2
,2
:s==;
26,
19,
8.
A3.
79,
22,
19,
Al,
53
,9
,5
,1
.7
,5
.7
.0
.5
.3
s==±
26
20
8
A9
86
26
23
A5
71
.5
.9
.8
.2
.2
.8
.7
.0
.0
26.9
21.7
9.3:
52.1
81.6
27.5
25.7
AA.2
82.2
                                                                                       371.2
                                                B-64

-------
                                                     Appendix B:  Implementation of the Scenarios
_RCW
                                           TABLE B-62

                    TRANSPORTATION ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
                                        FUEL CONSUMPTION
 REGION
                             1985
                                        2000
                                                    2025
                                                                2050
                                                                            2075
 TOTAL
                             60.4
                                         72.6
                                                   111.3
                                                               147.3
                                                                           187.4
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
21.
15.
4.
7.
1.

2,
4.
2.
1
6
,9
,7
2
.7
.2
.2
.8
21
16,
5
13
2
1
3
6
3
.1
.5
.4
.0
.1
.0
.6
.0
.9
23.
21.
7.
20.
5.
2.
9.
12.
7.
7
6
1
6
8
6
8
6
5
24.
21
8
26
12
4.
14
19
15
.1
,9
.0
.9
.1
.9
.3
.3
.8
24
21
8
32
21
8
17
24
28
.2
.7
.5
.5
.6
.1
.7
.9
.2
25.9
24.0
9.6
40.6
35.5
12.8
21.2
31.9
46.5
                                                                                       248.0
                                    ELECTRICITY CONSUMPTION
 REGION                      1985

 United States                 .0
 OECD Europe/Canada            .0
 OECD Pacific                  .0
 Centrally Planned Europe       .0
 Centrally Planned Asia        .0
 Middle East                   .0
 Africa                        .0
 Latin America                 .0
 South and East Asia           .0

 TOTAL                         .0
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2025

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .0
2050

  .0
  .0
  .0
  .0
  .4
  .0
  .0
  .0
  .2
2075

  .0
  .0
  .0
  .0
  .9
  .0
  .0
  .0
  .5

 1.4
2100

  .0
  .0
  .0
  .0
 1.6
  .0
  .0
  .1
  .8

 2.5
 REGION
                             1985
                                     TOTAL  ENERGY CONSUMPTION

                                         2000        2025        2050
                                                                            2075
 TOTAL
                             60.4
                                         72.6.
                                                    111.5
                                                                147.9
                                                                           188.8
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
21.
15,
4 .
7.
1.

2,
4
2,
;=s=
.1
,6
,9
,7
.2
.7
.2
.2
.8
-— —
~= —
21
16
5
13
2
1
3
6
3
.1
.5
.4
.0
.1
.0
.6
.0
.9
23.
21.
7.
20.
6.
2.
9,
12.
7.
7
6
.1
6
.0
.6
,8
,6
.5
s==
24
21
8
26
12
4
14
19
16
.1
.9
.0
.9
.5
.9
.3
.3
.0
24.
21,
8,
32,
22.
8,
17,
24,
28,
.2
,7
.5
.5
.5
.1
.7
,9
.7
25.9
24.0
9.6
40.6
37.1
12.8
21.2
32.0
47.3
                                                                                       250.5
                                                B-65

-------
Policy Options for Stabilizing Global Climate
RCW
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                           TABLE B-63

                              ELECTRIC UTILITY ENERGY CONSUMPTION
                                         (Exajoules/Yr)
                            1985
                           105.3
                                        2000
                                       152.9
                                                    2025
                                                                2050
                                                   263.5
                                                               387.4
                                                                            2075
                                                                           545.2
                                                            2100
26
24
7
26
6,
1
2
4
4
.6
.6
.4
.4
.8
.9
.7
.3
.6
==:=
33.
29.
9,
38,
14.
3.
5,
8.
10,
2
,4
,7
,5
,8
,2
,4
,4
,3
43
34
10
45
"45
11
14
24
33
.1
.6
.2
.9
.8
.1
.7
.9
.2
47.
38.
12
61,
74,
19,
24
44
64.
,0
.8
.8
.6
.1
.8
.7
.0
.6
51
44
15
81
110
29
38
63
112
.1
.0
.7
.0
.6
.2
.0
.4
.2
56.
49,
18,
98
142
38
50
78
165
0
,1
.4
.6
.9
.0
.7
.4
.2
                                                                                       697.3
                                           TABLE B-64

                 ENERGY CONVERSION EFFICIENCY AT ELECTRIC UTILITY POHERPLANTS*
                                           (percent)
REGION
                            1985
                                        2000
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
* Includes transmission and distribution losses
                                                    2025
                                                                2050
                                                                            2075
                                                                                        2100
31.
32.
32.
31.
26.
26.
22.
30.
26.
,2
,5
,4
,4
,5
,3
,2
,2
.1
33.
32,
30.
32,
28,
28,
29,
32,
30,
.1
.7
.9
.7
.4
.1
,6
.1
.1
34.
33.
34.
33.
32,
33,
32.
33.
32,
,1
,5
,3
,8
.8
.3
,7
,3
,8
36.
35,
36,
36,
35,
35,
35,
35,
35,
.0
.3
.7
.4
.5
.4
.6
.0
.6
37
35
36
37
37
36
37
36
37
.2
.7
.9
.5
.2
.3
.1
.0
.1
37,
35,
37.
37.
36.
36.
36.
36.
36.
.0
,8
,0
,1
,9
.3
9
2
9
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
                                           TABLE B-65

                               SYNTHETIC PRODUCTION OF OIL AND GAS
                                         (Exajoules/Yr)
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  :===
  .0
                                       OIL FROM SYNFUELS

                                        2000        2025
                                                                2050
                                                                            2075
                                                                                        2100
3.
1,

6.
6',




.1
.8
,8
,1
.2
.0
.8
.2
.8
13.
5.
3.
32.
24.

2.
2.
1.
1
,7
2
,7
.9
,0
,7
.5
,9
35
12
8
81
29

3
2
1
.6
.8
.5
.8
.3
.0
.3
.2
.5
70.
20.
16.
116.
35.

3.
2.
2.
0
0
7
1
8
0
6
5
0
                                                    19.8
                                                                86.7
                                                                           175.0
                                                                                       266.7
 REGION
                            1985
 United States                .0
 OECD Europe/Canada           .0
 OECD Pacific                 .0
 Centrally Planned Europe     .0
 Centrally Planned Asia       .0
 Middle East                  .0
 Africa                       .0
 Latin America                .0
 South and East Asia          .0

 TOTAL
                                       GAS FROM SYNFUELS
                                        2000
                                                    2025
                                                    10.1
                                                                2050
                                                                28.5
                                                                            2075
                                                                            72.4
                                                                                        2100
.0
.0
.0
.0
.0
.0
.0
.0
.0



1.


1.
•2.
1.
8
6
3
5
8
.0
,9
,9
,3
2.
1,

5,
2.

5,
7,
3
.5
.7 „-
.8
,1
.8
.0
.0
.3
.3
S=S5
9.
4.
2.
21.
8.

8,
11,
5,
7
,6
,7
,0
,4
,0
,6
.9
.5
===
21.
7,
5,
36,
12.

10,
13
6
,8
7
,6
.8
9
.1
,0
.1
.•4
±=;
                                                                                       114.4
                                               B-66

-------
                                                     Appendix B:  Implementation of the Scenarios
RCH
                                           TABLE  B-66

                       ENERGY USED FOR SYNTHETIC  FUEL  PRODUCTION  BY  TYPE
                                         (Exajoules/Yr)

                                             COAL
 REGION
                            1985
                                        2000
                                                    2025
                                                                2050
                                                                            2075
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia
 TOTAL
 REGION
 United -States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
BIOMASS
2000
.0
.0
.0
.0
.0
.0
.0
.0
.0
L, .
2,
1.
9.
9.

1.

1.
30,

202
1.


2,


2,
3.
1,
.7
.6
. 1
.2
.6
.0
.6
.3
,2
,3

>5
.1
,8
.A
.0
.9
.0
.6
.9
7
                                                               129.9
                                                                2050
                                                                           309.6
                                                                            2075
                                                    13.A
 2100

131.6
 37.0
 31.3
217.9
 70. A
   .0
 10.A
  2.1
  5.6

506.3
                                                                                        2100
                                                                            61.7
                                                                                        68.3
 REGION
                            1985
 United States                .0
 OECD Europe/Canada           .0
 OECD Pacific                 .0
 Centrally Planned Europe     .0
 Centrally Planned Asia       .0
 Middle East                  .0
 Africa                       .0
 Latin America                .0
 South and East Asia          .0

 TOTAL
                                            TOTAL
                                        2000
                                                    2025
                                                    A3.7
                                                                2050
                                                               173.7
                                                                            2075
                                                                           371.3
                                                                                        2100
0
0
0
0
0
0
0
0
0
5.
3.
1.
11.
10,

A,
A.
2,
,8
.A
.5
.2
.5
.0
.2
.2
.9
22,
11
6
55,
Al,

1A,
13,
7
.9
.8
.0
.8
.8
.0
.0
.9
.5
67
25
16
153
57

19
19
11
.A
.7
.6
.1
.8
.1
.7
.5
.A
137
AO
33
228
75

23,
22,
1A.
.0
.9
.3
.0
.2
.2
.7
.0
.3
                                                                                       57A.6
                                               B-67

-------
Policy Options for Stabilizing Global Climate
RCW
                                           TABLE B-67

                                C02 EMISSIONS FROM FOSSIL  FUEL
                                        (Petagrams C/Yr)
 REGION
                            1985
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia
 TOTAL
                             5.1
                                        2000
                                                    2025
                                                                2050
                                                                            2075
                                         7.0
                                                    11.2
                                                                15.6
                                                                            20.5
                                                                                       2100
1


1





.3
.9
.3
.3
.6
.1
.1
.2
.3
1
1

1
-• 1




.5
.1
.4
.8
.0
.2
.3
.3
.5
1
1

2
2



1
.8
.3
.4
.0
.3
.5
.7
.9
.3
2.
1.

2.
3.


1.
2.
0
4
5
9
6
7
9
4
1
2
1

4
4

1
1
3
.5
.6
.7
.5
.4
.9
.2
.7
.1
3,
1.
1
5.
4.
1.
1
1
4
5
.8
.0
, 7,
.9
.0
.4
.8
.1
                                                                                        25.0
                                           TABLE B-68

                                 CO EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams C/Yr)

 REGION                     1985        2000         2025         2050         2075         2100

 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

,,T0TAL                     185.8       197.6        334.9        477.5        636.0        862.7
51
44,
14,
31,
6,
2
8
16
11,
.0
.7
,1
.1
.0
.9
.5
.3
.2
28,
37.
12.
51,
10.
4.
14,
23.
15,
.0
.7
.3
,9
.2
.0
.4
.6
.6
31.
49.
16.
81.
26.
10.
38.
49,
30.
5
3
2
5
.9
,5
8
7
7
32.
50.
18,
106,
53,
19,
56,
76.
64,
.2
.1
.1
.8
.5
.7
.6
.0
,5
32
49,
19,
129,
91,
32
70
97,
113,
.5
.8
.5
.0
.5
.0
.3
.9
.5
35.
54,
22.
160,
145,
50,
84,
125.
184.
,1
,9
.1
,8
,4
,2
.1
,.3
,9
 REGION
                                           TABLE B-69

                                NOx EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams N/Yr)
                            1985
                                        2000
                                                    2025
                                                                2050
 TOTAL
                            24.2
                                        31.0
                                                    47.0
                                                                62.7
                                                                            2075
                                                                            77.5
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
6.
4,
1.
5.
2.


1,
1.
,1
,6
.7
.8
,6
,4
,8
.0
.3
=±s —
6.
4.
1.
7.
4.

1.
1.
2.
0
8
8
7
7
6
.5
.6
,3
6.
5,
2.
8.
10.
1,
3,
4.
5,
.3
,6
.0
.5
.2
,5
.6
.0
,4
6,
5,
2,
10
14,
2,
5,
6
9
.2
.9
,3
.6
.3
.3
.2
.3
.5
- — ss
6
6
2
12,
17,
3
6
8
14,
.5
.0
.6
.9
.5
.1
.6
.1
.2
==:=
7.2
6.5
3.0
15.2
19.4
4.0
7.5
9.6
19.1
                                                                                        91.5
                                               B-68

-------
RCWA
                                                     Appendix B:  Implementation of the Scenarios
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                             1985
                            301.6
                                          TABLE B-70

                                    PRIMARY ENERGY SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                                     2025
                                                                 2050
  2075
                                        432.9
                                                    972.2
                                                               1607.6
                                                                           2261.6
              2100
63
47
8
81
25
23.
16
20
14
.7
.6
.9
.2
.6
.7
.3
.5
.1
69,
56.
13.
113.
56,
48.
26.
28,
20.
,3
.5
.3
.5
,1
.4
.7
.6
.5
130.
86.
27.
305.
219.
57.
56.
50.
36.
,4
.9
.5
.8
.7
.9
.4
.8
.8
218
124
46
669
301
53
78
67
47
.4
.6
.9
.0
.7
.6
.7
.6
.1
391.
203
84
982.
333
47
80
75
61
.1
.5
.9
.6
.4
.8
.6
.8
.9
744.
205.
184.
930,
222,
61,
66.
99.
79.
.3
.4
.9
.8
.5
,2
.1
.3
.7
                                                                                      2594.2
REGION
United .States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia ..

TOTAL
                             1985
                            117.9
                                          TABLE B-71

                                      PRIMARY OIL SUPPLY-
                                        (Exajoules/Yr)
                                         2000
                                        126.7
                                                     2025
                                                                 2050
                                                    110.9
                                                                 97.9
                                                                             2075
                                                                             80.4
                                                                                        2100
20.
11.
1.
26,
5.
22.
10.
14.
5,
,8
,9
,1
,0
,2
,4
.8
,1
,6
12.
9,

22
6.
44,
13
12,
4
.5
.5
.6
.1
.9
.0
.8
.7
.6
7.
7.

15.
6.
41.
14.
14.
3.
,0
,3
.2
,5
.1
,9
,7
,7
,5
5,
5,

11,
4.
32,
18,
17,
2,
.2
.7
.0
.5
.8
.8
.2
.1
.6
4
3

7
3
25
13
19
1
.9
.8
.0
.9
.3
.7
.2
.7
.9
9,
3,

7,
3.
29,
11.
32,
2,
.3
.0
.0
.0
.2
.3
.9
.5
.5
                                                                                        98.7
REGION
                             1985
                                          TABLE B-72

                                      PRIMARY GAS SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                                     2025
                                                                 2050
TOTAL
                             58.6
                                         84.8
                                                     94.1
                                                                 67.2
                                                                             2075
                                                                             44.0
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
16.
9.

24.

1.
1.
2.
2.
.3
.7
7
.0
,5
,2
.3
,5
,4
17.
13.
1.
30.
2.
4.
4.
7.
2.
.1
.6
,9
,2
.8
.2
.3
.8
.9
12.
12.
1,
27.
4,
14,
7,
9,
4
,9
,1
.7
.5
,8
.8
.0
.0
.3
8
7

12
3
17
6
7
2
.1
.6
.7
.9
.5
.5
.9
.1
.9
ssssst •
2.
4,

8.
1,
15,
4,
3,
1,
.6
,5
.5
.4
.9
.9
.8
.8
.6
4.0
3.1
.5
13.1
1.1
19.5
3.6
2.0
1.0
                                                                                         47.9
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                '        87.3
                                          TABLE B-73

                                      PRIMARY COAL SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                        171.9
                                                     2025
                                                                 2050
                                                                             2075
                                                    666.0
                                                               1284.9
1914.7
                                                                                         2100
19,
9,
3,
26,
18,

4

4,
.4
.4
.9
.7
.9
.0
.0
.6
.4
31.
15.
6.
54.
44.

8.
1.
9.
8
2
8
8
0
0
2
2
9
98.
46.
21.
249.
196.

28.
5.
18.
8
9
6
5
7
0
9
6
0
191
90
41
623
270

39
8
20
.2
.1
.5
.7
.3
.0
.9
.2
.0
366.
169.
78.
936,
288.

43,
8,
23.
.4
,6
,4
,0
,7
.1
.0
.7
.8
706.
163.
175.
858.
139.

20.
4.
11.
3
9
2
3
9
0
8
2
6
                                                                                       2080.2
                                               B-69

-------
 Policy Options for Stabilizing (Global Climate
 RCWA
 REGION
 United  States
 OECD  Europe/Canada
 OECD  Pacific
 Centrally  Planned Europe
 Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East  Asia

 TOTAL
                              1985
                                          TABLE B-74

                                     PRIMARY BIOMASS.SUPPLY
                                         (Exajoules/Yr)
                                          2000
                                                     2025
                                                                 2050
                                                      18.5
                                                                  43.6
                                                                             2075
                                                                             52.1
                                                                                         2100
0
0
0
0
0
0
0
0
0
I.
1.

2.
1.

3.
5,
2.
5
1
5
7
3
0
.6
,4
.4
3.
2.
1.
6.
3.

8.
12.
5.
5
5
.2
5
1
,0
.5
.7
.6
4.
3.
1.
7.
3.

10.
15.
6.
1
0
5
7
7
1
1
2
7
5.
3.
2.
10,
4

13
19
8
A
,9
,0
,1
.8
.2
.3
.9
.7
                                                                                         68.3
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
 Ce'ntcally  Planned  Europe
'Centrally  Planned  Asia
 Middle East
 Africa
 Latin America
 South and  East Asia

 TOTAL
                                         TABLE  B-75

                                 PRIMARY  HYDROELECTRIC  SUPPLY
                                        (Exajoules/Yr)
                              1985
                              21.2
                                          2000
                                          30.2
                                                      2025
                                                                  2050
                                                      48.7
                                                                  63.1
                                                                             2075
                                                                              70.0
                                                                                         2100
3,
8,
1,
2.
1,


3.
1
.3
,2
.2
.5
.0
.1
.2
.3
.4
3.
9,
1,
3,
2,


6.
2,
.8
.6
,3
,1
,3
,2
.4
.9
.6
4.
10.
1.
3.
6.

1,
14
5.
.3
.6
.3
.6
.4
.4
.3
.9
.9
4,
11,
1,
3,
10

3,
19.
9.
.6
.0
.4
.7
.0
.6
.2
.2
.4
4,
11.
1,
3.
11.

5.
20,
11,
.7
.1
.4
.7
.3
.7
.3
.4
.4
4.
11.
1.
3.
11.

6.
20.
12.
.8
1
4
7
.6
7
6
6
.1
                                                                                         72.6
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
                              1985
                              16.5
                                           TABLE  B-76

                                      PRIMARY  NUCLEAR  SUPPLY
                                         (Exajoules/Yr)
                                          2000
                                          18.8
                                                      2025
                                                                  2050
                                                                             2075
                                                      31.4
                                                                  43.8
                                                                              83.9
                                                                                         2100
3.
8.
2.
2.





.8
.4
.0
.0
.0
.0
.0
.0
.3
===
3
8
2
3





.9
.5
.7
.1
.1
.0
.0
.0
.5
5.
8.
2.
6,
4,


1,
2,
.4
.5
.1
.3
.0
.8
.8
.1
.4
4
7
1
9
8
2
1
2
5
.9
.1
.8
.1
.5
.3
.7
.8
.6
6,
10,
2,
15
20
4
3
6
13
9
.4
.7
.6
.2
.4
.5
.6
.6
==;=
11.
18.
4.
30.
49,
9,
7
16,
35,
.6
,1
,8
,9
.6
,2
,9
.1
.1
s=:
                                                                                         183.3
 REGION                       1985

 United States.                  .1
 OECD Europe/Canada             .0
 OECD Pacific                   .0
.Centrally Planned Europe       .0
 Centrally Planned Asia         .0
 Middle East                    .0
 Africa                         .0
 Latin America                  .0
 South and East Asia            .0.

 TOTAL
                                           TABLE B-77

                                      PRIMARY SOLAR SUPPLY
                                         (Exajoules/Yr)
2000

  .2
  .1
  .0
  .2
  .0
  .0
  .0
  .0
  .0
                                                      2025
                                                                  2050
                                                                              2075
                                                                                         2100
.5
.4
.1
.7
.4
.0
.1
.1
.3



1.
1.



1,
,9
6
3
.6
.5
,4
,3
.5
.0
1.
1.

3.
4.


1.
2.
5
.1-
4
3
3
9
7
,4
.9
2.
2.
1,
. 7,
12.
2.
2,
4.
8.
9
,3
,0
,7
.3
,3
.0
.0
.7
                                                       2.6
                                                                   7.1
                                                                              16.5
                                                                                          43.2
                                                B-70

-------
                                                     Appendix B: Implementation of the Scenarios
RCWA
                                          TABLE  B-78

                                  PRIMARY ENERGY CONSUMPTION
                                        (Exajoules/Yr)
REGION
                             1985
                                         2000
                                                     2025
                                                                2050
                                                                            2075
TOTAL
                            300.2
                                        432.7
                                                    970.5
                                                               1607.3
                                                                          2261.8
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
74
67
19
71
23
5
7
15
15
.9
.0
.3
.-1
.8
.8
.6
.6
.1
91.
81.
24.
113,
45.
9.
13.
26.
28
.2
,2
,9
.0
,9
.1
,1
.3
.0
154.
128.
40.
233.
• 170.
32.
44.
79.
87.
2
9
0
1
0
,5
3
9
6
198
163.
55.
406
319
59
77
144
182
.9
.6
.3
.8
.9
.0
.2
.5
.1
248.
194.
69.
561.
480,
87.
107,
205.
307.
,2
.5
.7
,4
.7
.2
.4
.4
.3
317.9
193.0
91.3
587.1
539.5
104.4
116.4
238.0
406.1
                                                                                      2593.7
                                           TABLE B-79

                       SECONDARY ENERGY CONSUMPTION: FUEL  VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION '                      1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                       194.4
                                        FUEL CONSUMPTION
                                         2000
                                                     2025
                                                                 2050
                                                                            2075
                                        264.0
                                                    493.8
                                                                752.8
                                                                           950.8
                                                                                        2100
48,
42.
11.
44,
17,
3.
4,
11,
10,
,2
.4
.9
.6
.0
.9
.7
.3
.4
54.
49.
14.
65.
30,
5.
8,
18,
17,
.9
,3
,5
.8
,2
.9
,0
,0
,4
77.
71.
20.
108.
79.
19.
23.
48.
44.
2
3
8
6
.1
8
6
6
.8
89.
83.
26.
159.
142,
36.
40,
82,
92,
.8
.5
.4
.1
.9
.2
.2
.2
.5
93.
86,
28,
195,
191,
52.
51,
108,
143,
.3
.7
.4
.6
,9
,1
,5
,0
.3
87.
79.
26.
201.
180.
58.
51.
109.
165.
7
3
9
2
9
,8
9
2
.9
                                                                                       961.8
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        32.9
                                    ELECTRICITY CONSUMPTION
                                         2000
                                                     2025
                                                                 2050
                                         53.9
                                                    124.7
                                                                220.6
                                                                            2075
                                                                            351.6
                                                                                        2100
8.
8.
2.
8,
1.


1,
1,
.4
.0
,4
.4
.8
.5
.8
,3
.3
11
10
3
15
4
1
1
2
3
.8
.5
.4
.3
.5
.0
.5
.7
.2
21.
17.
5.
29,
19.
4,
4,
•9.
13.
,2
,2 .
.4
.2
,6
.4
,8
.8
.1
26.
22.
7.
47.
46.
8.
9.
20.
31,
3
8
.7
,2
,1
,6
,7
.8
.4
30,
27,
9,
67,
89
13.
16
34
61
,7
.6
.7
.5
.6
.7
.7
.6
.5
30
29
10
78
127
17
21
46
91
.5
.3
.3
.4
.8
.7
.9
.9
.•6
                                                                                       454.4
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                            227.3
                                     TOTAL ENERGY CONSUMPTION

                                         2000        2025
                                                                 2050
                                                                            2075
                                        317.9
                                                    618.5
                                                                973.4
                                                                           1302.4
                                                                                        2100
56.
50.
14.
53.
18.
4.
5.
12.
11.
6
4
,3
0
.8
.4
,5
.6
.7
66.
59.
17,
81,
34,
6.
9,
20
20,
.7
.8
.9
.1
.7
.9
.5
.7
.6
98
88
26
137
98
24
28
58
57
.4
.5
.2
.8
.7
.2
.4
.4
.9
116
106
34
206
189
44
49
103
123
.1
.3
.1
.3
.0
.8
.9
.0
.9
124.
114.
38.
263.
281.
65.
68,
142,
204,
,0
,3
,1
,1
,5
.8
,2
.6
.8
118,
108.
37.
279.
308.
76
73
156
257
.2
.6
.2
.6
.7
.5
.8
.1
.5
                                                                                      1416.2
                                               B-71

-------
Policy Options for Stabilizing Global Climate
RCWA
                                          TABLE B-80

                                   SECONDARY OIL CONSUMPTION
                                        CExajoules/Yr)
REGION                       1985
United States
OECD Europe/C,anada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                       100.6
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
                                        112.A
                                                    229.0
                                                                352.5
                                                                            AA3.7
                                                                                         2100
28.
25.
8.
1A.
2
3
3
8
6
.8
,8
.0
.6
.2
.A
.1
.6
.1
27
25.
8.
19
2
5
A
11
7
,9
.6
.0
.3
.8
.0
.A
.8
.6
AO.
AO.
12.
38.
10.
17,
1A.
33.
21,
5
.9
.7
,0
.0
.1
,A
.8
.6
A6.
A7,
16.
55,
23,
31,
2A,
57,
A8,
,5
,7
.7
,9
,3
,2
,A
.9
.9
A5.
A7,
17,
65,
38.
AA,
30.
7A.
80.
.6
.A
.6
,7
.5
.A
.1
.2
.2
A2.
AA.
17,
69,
50,
A9
31
7A
101
.A
,3
.1
.A
.1
.1
.6
.5
.3
                                                                                        A79.8
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East     \
Africa
Latin America
South and East 'Asia
sg—=:—;jig=;=s=is===:====—=:a:===
TOTAL
                             1985
                                          TABLE B-81

                                   SECONDARY GAS CONSUMPTION
                                        (Exajoules/Yr)
                             A8.8
                                         2000
                                         63.2
                                                     2025
                                                                 2050
                                                                             2075
                                                    10A.8
                                                                157.3
                                                                            21A.9
                                                                                         2100
15.6
10.3
1.3
17.1
.3
.5
.A
2.1
1.2
19.1
12.1
1.6
22. A
.3
.9
.7
A.I
2.'0
26.3
16. A
2.2
38.7
1.1
2.7
1.8
10.3
5.3
31.9
20.0
2.8
61. A
2.7
5.0
3. A
18.0
12.1
36. A
23.1
3.5
8A.5
A. 9
7.7
5.5
27.0
22.3
36.1
22.2
3.5
9A.7
6.1
9.7
6.7
29.8
28.7
                                                                                        237.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-82

                                 SECONDARY SOLIDS CONSUMPTION
                                         (Exajoules/Yr)
                             1985
                             A5.0
                                         2000
                                         88. A
                                                     2025
                                                                 2050
                                                                             2075
                                                     160.0
                                                                2A3.0
                                                                            292.2
                                                                                         2.100.
3.
6.
2.
12,
H,

1

3
.8
.3
.6
.9
.5
.0
.2
.6
.1
7,
11.
A,
2A,
27,

2,
2,
7,
,9
.6
.9
.1
,1
.0
.9
.1
.8
10
1A.
5.
31,
68,

7
A
17
.A
.0
.9
.9
.0
.0
.A
.5
.9
11.
15.
6.
/Al.
116,

12.
6.
31,
A
,8
9
.8
,9
,0
,A
.3
.5
11.
16.
7,
A5,
1A8

15
6
AO
.3
.2
.3
.A
.5
.0
.9
.8
.8
9.
12.
6.
37.
124.

13.
A.
35.
.2
.8
.3
,1
7
.0
,6
9
9
                                                                                        2AA.5
                                                B-72

-------
                                                     Appendix B: Implementation of the Scenarios
RCHA
                                          TABLE  B-83

                RESIDENTIAL/COMMERCIAL ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        47.9
                                        FUEL CONSUMPTION
                                         2000
                                                     2025
                                                                2050
                                                                            2075
                                         62.2
                                                    111.A
                                                               172.A
                                                                           233.1
                                                                                        2100
11.
12.
1.
13.
4.


1.
2.
5
9
6
2
3
2
4
6
2
12
15
2
17
7


2
3
.6
.6
.3
.3
.1
.A
.9
.5
.5
18.
2A,
3.
33
15
1,
2
5
7
.6
,0
.A
.A
.2
,5
.3
.6
.A
22.
27.
A.
51.
32.
3,
A.
10,
16,
,1
, A
.A
.7
.2
,1
.A
.9
.2
2A.
29.
5.
68.
50.
5.
6.
16.
26.
3
5
1
3
A
1
7
9
8
22
26
A
71
A8
6
6
18
31
.7
.3
.7
.7
.6
.1
.8
.2
.1
                                                                                       236.2
REGION
                             1985
                                    ELECTRICITY CONSUMPTION
                                         2000
                                                     2025
                                                                2050
                                                                            2075
TOTAL
                             13.7
                                         21.3
                                                     53.3
                                                                88.6
                                                                           136.5
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
5
A
1
1.





.2
.5
.1
.3
.2
.1
.3
.5
.5
7
5
1
3



1
1
.2
.8
.6
.1
.6
.2
.6
.0
.2
1A,
10.
2,
10.
3.
1,
2.
3
5,
.5
.9
.9
.1
,2
.1
.0
.3
.3
17.
13.
A.
16.
8.
2.
A.
7,
13.
,8
,8
,1
,2
.7
,5
.2
.9
,4
— _ — ;
20
16
5
22
19
A
7
14
27
.A
.0
.1
.6
.2
.A
.A
.3
.1
19.5
16.1
5.1
2A.8
29.1
5.8
9. A
19.5
39.9
                                                                                       169.2
REGION
United States
OECD Europe/Canada
OECD Pacific
-Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                             61.6
                                    TOTAL ENERGY CONSUMPTION
                                         2000
                                                     2025
                                                                2050
                                                                            2075
                                         83.5
                                                    16A.7
                                                               261.0
                                                                           369.6
                                                                                        2100
16,
17,
2.
1A.
A,


2
2
.7
.A
.7
.5
.5
.3
.7
.1
.7
19.
21.
3.
20,
7,

1,
3,
A,
,8
.A
.9
,A
,7
.6
.5
.5
.7
33
34
6
A3
18
2
A
8
12
.1
.9
.3
.5
.A
.6
.3
.9
.7
39,
Al,
8.
67.
AO.
5,
8,
18,
29,
.9
.2
.5
.9
.9
.6
.6
.8
.6
44.
A5,
10,
90,
69.
9.
1A.
31,
53,
.7
.5
.2
.9
.6
,'5
.1
.2
.9
42.
42,
9,
.96,
77,
11,
16,
37,
71,
,2
.4
.8
.5
.7
.9
.2
.7
.0
                                                                                       405.4
                                               B-73

-------
Policy Options for Stabilizing Global Climate
RCWA
                                          TABLE B-8A

                     INDUSTRIAL ENERGY CONSUMPTION: FUEL  VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        86 .1
                                       FUEL CONSUMPTION
                                         2000
                                                     2025
                                                                 2050
                                        130.6
                                                    250.9
                                                                388.A
                                                                            2075
                                                                            490.8
                                                                                        2100
15.
13.
5,
23.
11.
3,
2
5
5
.6
.9
, A
.7
.5
.0
.1
.5
.A
21.
17,
6.
35.
21,
A,
3,
9.
10.
,6
,5
.9
.8
.1
,5
,5
.6
.1
30...
21.
9.
50.
57.
15.
9.
28.
28.'
6
8
0
9
1
2
7
0
6
36.
27,
11,
72,
95.
26.
17.
A6.
55,
,3
,6
.6
.A
.0
.7
,1
.0
,7
39,
30,
13,
88
115.
37
23.
60.
82.
.7
,9
.0
.0
.3
.3
.3
.8
.5
37.
27.
11 '.
85,
9A,
38,
22,
56,
85 ,
.1
.2
,8
.9
.9
.9
.2
.5
,5
                                                                                       460.0
                                    ELECTRICITY CONSUMPTION
REGION

United States
OECD Europe/Canada      ^
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle-East
Africa
Latin America
South and East Asia
                             1985
                                         2000
                                                     2025
                                                                 2050
                                                                            2075
                                                                                        2100
3.
3.
1.
7.
1.




2
5
3 „
1
.6
4
,5
,8
.8
4.
4,
1.
12,
3,


1,
2,
.6
.7
.8
.2
.9
.8
.9
.7
.0
6.
6.
2.
19.
16.
3,
2.
6,
7.
,7
,3
5
,1
,2
,3
,8
,5
,7 -.
8,
9
3,
31
36.
6,
5.
12.
17.
.5
,0
.6
.0
.9
.1
.5
.9
.7 ,
10
11
A
4A
69
9
9
20
33
.3
.6
.6
.9
.5
.3
.3
.3
.9
11.
13.
5.
53,
96,
11,
. .12.
27,
50.,
.0
.2
.2
.6
.9
.9
.5
.3..
.8
TOTAL
                             19.2
                                         32.6
                                                     71.1
                                                                131.2
                                                                            213.7
                                                                                       282.4
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin .America
South and East Asia
TOTAL                       105.3
                                    TOTAL ENERGY CONSUMPTION
                                         2000
                                        163.2
                                                     2025
                                                                 2050
                                                    322.0
                                                                519.6
                                                                             2075
                                                                            704.5
                                                                                        2100
18,
17.
6.
30.
13.
3.
2.
6.
6,
,8
,4
,7
,8
,1
,4
,6
,3
,2
26,
22,
8
48,
25
5,
4,
11,
12,
.2
.2
.7
.0
.0
.3
.A
.3
.1
37.
28.
11.
70.
73.
18.
12.
34.
36.
3
,1
,5
,0
,3
,5
,5
.5
,3
44,
36,
15.
103.
131.
32.
22.
58.
73,
.8
.6
.2
.A
,9
.8
.6
.9
,4
50,
42,
17.
132.
184.
46.
32.
81.
116.
.0
.5
,6
.9
.8
.6
.6
.1
.4
48,
40,
. 17,
, - 139,
191,
50,
. 34,
83,
136',
..1
.i4
.0
,5.
.'8
.8
.7
.8
.3
                                                                                       742.4
                                               B-74

-------
                                                     Appendix B:  Implementation of the Scenarios
RCWA
                                          TABLE B-85

                   TRANSEORTATION ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
                                       FUEL CONSUMPTION
 REGION
                             1985
                                         2000
                                                     2025
                                                                 2050
 TOTAL
                             60.4
                                         71.2
                                                    131.5
                                                                192.0
                                                                             2075
                                                                            226.9
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
21.
15.
4.
7,
1.

2
it.
2.
.1
,6
.9
.7
.2
.7
,2
.2
.8
20
16
5
12
2
1
3
5
3
.7
.2
.3
.7
.0
.0
.6
.9
.8
28
25
8
24
6
3
11
15
a
.0
.5
.4
.3
.8
.1
.6
.0
.8
31.
28
10
35
15
6
18
25
20
.4
.5
.4
.0
.7
.4
.7
.3
.6
29
26
10
39
26
9
21
30
34
.3
.3
.3
.3
.2
.7
.5
.3
.0
27.9
25.8
10.4
43.6
37.4
13.8
22.9
34.5
49.3
                                                                                        265.6
                                    ELECTRICITY CONSUMPTION
 REGION                       1985

 United  States                   .0
 OECD  Europe'/Canada              .0
 OECD  Pacific                    .0
 Centrally  Planned Europe        .0
 Centrally  Planned Asia          .0
 Middle  East                     .0
 Africa                          .0
 Latin America                   .0
 South and  East Asia             .0

 TOTAL
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2025

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .1
 2050
=IS::SS535=
   .0
   .0
   .0
   .0
   .5
   .0
   .0
   .0
   .3
2075

  .0
  .0
  .0
  .0
  .9
  .0
  .0
  .0
  .5
 ==;=5=
 1.4
2100

  .0
  .0
  .0
  .0
 1.8
  .0
  .0
  .1
  .9

 2.8
 REGION                       1985
 United  States
 OECD  Europe/Canada
 OECD  Pacific
 Centrally  Planned Europe
-Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East  Asia
 TOTAL                       60.4
                                    TOTAL ENERGY CONSUMPTION

                                         2000        2025
                                                                 2050
                                                                             2075
                                         71.2
                                                    131.8
                                                                192.8
                                                                            228.3
                                                                                         2100
21.
15.
4.
7.
1

2.
4.
2.
.1
.6
.9
,7
,2
.7
.2
.2
.8 •
20.
16.
5.
12.
2.
1.
3,
5.
3.
.7
.2
.3
,7
.0
.0
,6
.9
.8
28.
25.
8.
24.
7.
3.
11.
15.
8.
,0
.5
.4
.3
,0
.1
.6
.0
.9
31.
28.
10.
35.
16,
6.
18
25.
20,
.4
.5
.4
.0
.2
.4
.7
.3
.9
29
26,
10
39
27
9
21
30
34
.3
,3
.3
.3
.1
.7
.5
.3
.5
27
25
10
43
39
13
22
34
50
.9
.8
.4
.6
.2
.8
.9
.6
.2
                                                                                        268.4
                                                B-75

-------
Policy Options for Stabilizing Global Climate
RCWA
REGION
                                          TABLE B-86

                              ELECTRIC UTILITY ENERGY CONSUMPTION
                                        (Exajoules/Yr)
                             1985
                                         2000
                                                     2025
                                                                 2050
TOTAL
                            105.3
                                        168.6
                                                                591.
                                                                             2075
                                                                            900.1
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
26.
24.
7,
26,
6.
1.
2.
4.
4,
.6
.6
,4
,4
,8
.9
,7
,3
,6
36
31
10
47
15
3
5
8
10
.3
.8
.4
.1
.8
.2
.1
.3
.6
60
49
15
84
59
12
14
28
39
.8
.9
.6
.1
.1
.7
.6
.9
.1
70,
62.
20,
124,
123.
22.
26
56,
84
,9
.0
,6
,6
.5
,8
.4
.6
.0
78.
72.
24.
170.
228,
35
43
91
157
.4
.2
.7
,7
.1
.0
.0
.0
.0
78.6
77.9
26.8
200.7
327.6
45.6
56.9
123.0
235.5
                                                                                       1172.6
                                          TABLE B-87

                 ENERGY CONVERSION EFFICIENCY AT ELECTRIC UTILITY POWERPLANTS*
                                           (percent)
REGION
                             1985
                                         2000
United States  .
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
  Includes transmission and distribution losses
                                                     2025
                                                                 2050
                                                                             2075
                                                                                         2100
31
32
32
31
26
26
22
30
26
.2
.5
.4
.4
.5
.3
.2
.2
.1
32.
32.
32.
32,
29.
31
29
32
30
.5
.7
.7
.3
.1
.2
.4
.5
.2
34.
34.
34
34
33
34.
32
34
33
.9 .
.5
.6
.7
.0
.6
.9
.3.
.2
37
36
37
37
37
37
37
36
37
.0
.8
.4
.8
.3
.7
.5
.7
.3
39.
38
39.
39,
39,
39,
38,
38,
39
.2
.4
.3
.4
.2
.1
.8
.1
.2
38,
37.
38,
39,
39.
38,
38.
38.
38.
,9
.7
.8
.1
.0
.8
,7
.2
,9
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                                          TABLE B-88

                              SYNTHETIC PRODUCTION OF OIL AND GAS
                                        (Exajoules/Yr)
TOTAL
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
                                      OIL FROM SYNFUELS
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
                                                                                         2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
24,
11.
5.
62,
49,

6,
1
4
.8
,8
,4
,7
.4
.0
.7
.2
.4
51.
24,
11,
168,
73,

9
1
5
.7
.4
.2
.6
.0
.0
.9
.3
.2
97.
45.
20.
248.
76.

9,
1,
5.
3
.1
.8
,7
.6
.0
,9
,5
.9
190.
44,
47,
231
37

6
1
3
.2
.2
.2
.3
.8
.•0
.0
.7
.4
                                           .0
                                                    166.4
                                                                345.3
                                                                            505.8
                                                                                        561.8
REGION                       1985

United States                  .0
OECD Europe/Canada             .0
OECD Pacific                   .0
Centrally Planned Europe       .0
Centrally Planned Asia         .0
Middle East                    .0
Africa                         .0
Latin America                  .0
South and East Asia            .0

TOTAL                          .0
                                       GAS FROM SYNFUELS
                                         2000
                                                     2025
                                                     59.1
                                                                 2050
                                                                185.3
                                                                             2075
                                                                            319.8
                                                                                         2100
,0
.0
.0
.0
.0
.0
.0
.0
.0
7.
4.
1,
19,
14,

4
• 4,
3
.8
.0
.9
.0
.3
.0
.7
.4
.0
25.
12.
5.
78.
34.

11.
10.
6,
3
6
9
9
,4
,0
,1
,5
,6
56.
27.
12.
143.
45.

13,
12,
8.
9
1
6
,1
,1
,0
,9
.6
.5
114.
28.
28.
141.
25.

12.
15.
&,
6
5
9
8
A
,1
,8
,0
1
                                                                                        375.2
                                                B-76

-------
                                                     Appendix 1$:  Implementation of the Scenarios
RCWA
                                          TABLE B-89

                       ENERGY USED FOR SYNTHETIC FUEL PRODUCTION  BY  TYPE
                                        (ExajouLes/Yr)
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Pla
Centrally Pla
Middle East
Africa
Latin America
TOTAL



in ad a

med Europe
med Asia



- Asia

1985
.0
.0
.0
.0
.0
.0
.0
.0
.0
COAL
2000
.0
.0
.0
.0
.0
.0
.0
.0
.0


2025
47
22
10
119
94

13
2
8
.3
.4
.4
.4
. 1
.0
.9
.7
.6


2050
111
52
24
364
157

23
4
11
.6
.6
.2
.0
.8
.0
.3
.8
.7


2075
226
104
48
579
178

26
5
14
.6
.9
.5
.0
.6
.0
.6
.4
.7


2100
451
104
111.
548.
89.

13.
2.
7
.1
.7
.9
.2
.3
.0
.3
.7
.4
                               .0
                                           .0
                                                                750.0
                                                                           1184.3
                                                                                       1328.6
REGION                       1985

United States                  .0
OECD Europe/Canada             .0
.OECD Pacific                   .0
Centrally Planned Europe       .0
Centrally Planned Asia         .0
Middle East   .                 .0
Africa                         .0
Latin America                  .0
South and East Asia            .0

TOTAL                          . 0
                                           BIOMASS

                                         2000        2025
                                                     18.5
                                                                 2050
                                                                 43.6
                                                                             2075
                                                                             52.1
                                                                                        2100
0
0
0
0
0
0
0
0
0
1,
1.

2.
1.

3,
5.
2.
.5
.1
.5
,7
.3
,0
,6
,4
,4
3.
2.
1.
6.
3.

8.
12.
5.
.5
.5
.2
.5
,1
.0
.5
,7
.6
4
3
1
7
3

10
15
6
.1
.0
.5
.7
.7
.1
.1
.2
.7
5.
3.
1
10
4

13
19
8
.4
.9
.9
.1
.8
.1
.2
.9
.7
                                                                                        68.0
                                            TOTAL
REGION    -                   1985

United States                  .0
OECD Europe/Canada             .0
OECD Pacific                   .0
Centrally Planned Europe       .0
Centrally Planned Asia         .0
Middle East                    .0
Africa                         .0
Latin America                  .0
South and East Asia            .0

TOTAL
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                                     2025
                                                                 2050
                                                                             2075
                                                                                        2100
48,
23.
10.
122,
95,

17,
8,
11,
.8
.5
,9
.1
,4
,0
,5
.1
.0
115.
55.
25.
370.
160.

31.
17.
17.
.1
.1
.4
,5
.9
,0
.8
.5
,3
230.
107,
50.
586.
182.

36.
20.
21.
.7
,9
.0
.7
.3
,1
.7
.6
.4
456
108
113.
558,
94.

26
22
16
.5
.6
.8
.3
. 1
.1
.5
.6
.1
                                                    337.3
                                                                793.6
                                                                           1236.4
                                                                                       1396.6
                                               B-77

-------
 Policy Options for Stabilizing Global Climate
.RCHA
                                          TABLE B-90

                                 C02 EMISSIONS FROM FOSSIL FUEL
                                       (Petagrams C/Yr)
REGION
                             1985
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
TOTAL
                              5.1
                                          7,8
                                                     19.8
                                                                 34.6
                                                                             49.6
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned
Centrally Planned
Middle Ea'st
Africa
Latin America



Europe
Asia



South and East Asia
1.3
.9
.3
1.3
.6
.1
.1
.2
.3
1.6
1.2
.4
2.2
1.1
.2
.3
.3
.5
3.
2,

5,
4.


1
1.
.1
.3
.8
.2
.2
.6
.9
.1
.7
4
3,
1.
10
7.
1
1
2
3
.4
.2
.2
.1
.8
.0
.4
.1
.4
6
it
1
14
11
1
2
3
5
.1
.1
.6
,5
.1
.5
.0
.1
.7
8
3
2
14.
10
1.
1.
3
7,
.9
.8
.4
.2
.8
.7
.9
.5
.0
                                                                                         54.4
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-91

                                 CO EMISSIONS FROM FOSSIL FUEL
                                       (Teragrams C/Yr)
                             1985
                            185.8
                                         2000'
                                        195.4
                                                     2025
                                                                 2050
                                                    399.7
                                                                631.6
                                                                             2075
                                                                            789.8
                                                                                         2100
51.0
44.7
14.1
31.1
6.0
2.9
8.5
16.3
11.2
27.6
37.3
12.1
51.5
10.2
4.0
14.1
23.1
15.4
37.7
58.6
19.4
97.8
32.9
12.3
45.9
58.9
36.1
42.8
65.8
24.0
142.7
73.4
25.6
73.8
99.8
83.7
41.2
61.4
24.2
161.9
119.1
38.8
85.4
119.9
137.9
40.9
60.1
24.7
178.2
160.1
54.6
90.6
136.2
197.6
                                                                                        942.9
REGION
                                          TABLE B-92

                               NOx EMISSIONS FROM FOSSIL FUEL
                                       (Teragrams N/Yr)
                             1985
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
TOTAL
                             24.2
                                         33.7
                                                     66.7
                                                                107.3
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
6.
4.
1.
5.
2.


1.
1.
,1
,6
.7
.8
.6
,4
.8
.0
,3
6,
5,
2,
9,
5.

1.
1.
2
.4
.2
.0
.1
.0
.5
.4
.6
.4
9
8
3
15
14
1
4
4
6
,1
.2
.0
.0
.0
.9
.1
.9
.6
10.
10.
4.
23.
25.
3.
6.
9.
13.
9
2
0
5
9
4
7
2
4
12.
11.
4.
30.
38.
5.
8.
12.
21.
5
1
6
8
3
0
.7
.7
.9
14.4
10.6
5.2
31.9
39.8
6.0
9.1
14.5
29.3
                                                                                        160.8
                                               B-78

-------
Policy Options  for Stabilizing Global Climate
SCWP
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-97

                                    PRIMARY BIOMASS SUPPLY
                                        (Exajoules/Yr)
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
                                              2000
                                                          2025
                                                                      2050
                                                .0
                                                          34.5
                                                                     155.7
                                                                                  2075
                                                                                             2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
2.
2.
1.
5.
2.

6.
10.
4.
8
0
0
1
4
0
7
,1
A
12,
8,
4,
23.
10

30,
45
19,
,4
.9
.5
.1
.9
.3
.3
.4
.9
16
11
5
30
14

39
59
26
.3
.7
.9
.5
.4
.5
.9
.8
.3
19.
14.
7.
36.
17.

48.
72.
31.
7
1
1
8
4
5
2
.3
7
                                                                                 205.3
                                                                                            247.8
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America '
South and East Asia
                                          TABLE B-98

                                 PRIMARY HYDROELECTRIC SUPPLY
                                        (Exajoules/Yr)
                                  1985
TOTAL
                                  21.2
                                              2000
                                              29.3
                                                          2025
                                                                      2050
                                                          43.7
                                                                      55.7
                                                                                  2075
                                                                                  62.9
                                                                                              2100
3.
8,
1,
2.
1,


3,
1.
,3
.2
,2
,5
,0
.1
.2
.3
.4
3.
9.
1.
3.
2.


6.
2.
8
6
.3
,1
,3
.2
4
,0
,6
4.
10.
1.
3.
6.

1.
9.
5.
3
6
3
6
,4
,4
,3
9
,9
4,
11,
1,
3,
10,

3
11,
9,
,6
.0
.4
.7
.0
.6
.2
.8
.4
4,
11,
1,
3.
11,

5
13,
11
,7
.1
.4
.7
.3
.7
.3
.3
.4
4.
11.
1.
3.
11.

6.
12.
12.
8
1
4
7
6
7
6
6
1
                                                                                              64.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-99

                                    PRIMARY NUCLEAR SUPPLY
                                        (Exajoules/Yr)
                                  1985
                                  16.5
                                              2000
                                              18.1
                                                          2025
                                                                      2050
                                                          25.5
                                                                      32.8
                                                                                  2075
                                                                                  38.0
                                                                                              2100
3.
8,
2.
2,





,8
.4
,0
.0
.0
.0
.0
.0
.3
4.
7.
2.
3.





7
3
5
1
1
0
0
0
4
6.
5.
2.
6.
2.



1
0
6
1
,2
,6
,8
9
.0
,3
6
4
2
8
4
2
2

2
.5
.8
.2
.2
.0
.6
.0
.0
.5
6.
5,
2,
8,
4,
3,
2,

3
,8
.2
.5
.6
.8
.5
.7
.0
.9
7.
5.
2.
8,
5,
3,
2.

5
,1
,5
,9
.6
.2
.9
.9
.0
.0
                                                                                              41.1
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-100

                                    PRIMARY SOLAR SUPPLY
                                         (Exajoules/Yr)
1985

   .1
   .0
   .0
   .0
   .0
   .0
   .0
   .0
   .0

   .1
                                              2000
                                                          2025
                                                                      2050
                                                                                  2075
                                                                                              2100
6
3
2
6
2
0
0
0
0
3.
1.

3,
1,




,2
,3
8
.7
,6
.6
.7
.0
.9
6.
2.
1.
8.
4.
2.
2.

2.
4
4
7
1
0
.6
,0
,0
,5
6.
2.
1.
7.
4.
3.
2.

3,
0
3
,8
,5
,2
,1
.4
.0
,4 '
5
2
1
6
4
3
2

3
.6
.2
.8
.7
.1
.1
.3
.0
.9
                                                1.9
                                                          12.8
                                                                      29.7
                                                                                  30.7
29.7
                                                B-80

-------
                                                     Appendix B: Implementation of the  Scenarios
SCWP
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                           TABLE B-101

                                   PRIMARY  ENERGY CONSUMPTION
                                         (Exajoules/Yr)
                                  1985
                                 300.2
                                             2000
                                                         2025
                                                                     2050
                                                                                 2075
                                             335.9
                                                         394.7
                                                                    479.7
                                                                                501.9
                                                                                             2100
74
67
19
71
23
5
7
15
15
.9
.0
.3
.1
.8
.8
.6
.6
.1
lit
66
19
80
33
8
10
20
21
.3
.8
.9
.6
.9
.8
.1
.4
.1
71
62
18
83
54
15
19
33
36
.3
.3
.5
.6
.2
.3
.2
.4
.9
73.
62.
20.
91.
65.
25.
34.
49.
56.
7
8
5
2
1
9
9
4
2
68
60
21
85
67
29
45
54
69
.6
.9
.3
.0
.7
.2
.1
.9
.2
68
61
22
81
67
30
49
54
77
.3
.5
.9
.7
.0
.0
.9
.7
.2
                                                                                            513.2
                                          TABLE  B-102

                     SECONDARY ENERGY  CONSUMPTION:  FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                       FUEL  CONSUMPTION
                                  1985         2000
                                 194.4
                                             212.2
                                                         2025
                                                                     2050
                                                                                 2075
                                                         242.0
                                                                    276.0
                                                                                277.8
                                                                                             210.0
48.
42.
11.
44.
17.
3,
4
11
10
.2
.4
.9
.6
.0
.9
.7
.3
.4
45
42.
11
49
23
5
6
14
14
.1
.0
.9
.1
.4
.7
.3
.4
.3
42.
38.
11.
50.
34.
9.
11.
21.
23.
1
.8
.0
.1
,7
.7
,2
.0
.4
42.
38.
11.
52.
37.
16.
17.
26.
32.
.9
.7
.5
.4
.8
.4
.2 -
.3 .
.8
39.
36,
11.
47,
38,
17,
21.
26,
39,
.0
.2
.8
.2
.0
.9
.6
.8
.3
38
36,
12
44
36
18
23
24
43
.3
.2
.7
.4
.1
.5
.1
.2
.0
                                                                                            276.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
 ELECTRICITY CONSUMPTION

1985        2000         2025

 8.4
 8.0
 2.4
 8.4
 1.8
 1.3
 1.3
                                                                     2050
                                                                                 2075
                                                                                             2100
9.
8.
2.
10.
3.

1.
2.
2.
7
3
6
4
1
,9
,2
,0
,1
9.
.7,
2,
11,
6,
2.
2
3
4
.9
.9
.5
.3
.2
.0
.1
.3
.1
9.
7.
2.
11.
8.
3.
3.
3,
6.
9
6
8
8
4
4
6
9
3
9,
7
2.
11
9
4
4
4
8
.4
.6
.9
.2
.3
.1
.9
,4
.2
9.
7.
3,
10,
9,
4,
5,
4,
9
,2
.5
,1
.3
.4
.2
.3
.2
.3
                                  32.9
                                              40.3
                                                          49.3
                                                                      57.7
                                                                                  62.0
                                                                                             62.5
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                   TOTAL ENERGY CONSUMPTION
                                  1985
                                 227.3
                                              2000
                                             252.5
                                                          2025
                                                                      2050
                                                         291.3
                                                                     333.7
                                                                                  2075
                                                                                 339.8
                                                                                             2100
:==:
56
50
14
53
18
4
5
12
11
.6
.4
.3
.0
.8
.4
.5
.6
.7
54
50
14
59
26
6
7
16
16
.8
.3
.5
.5
.5
.6
.5
.4
.4
52.
46,
13,
61.
40.
11.
13
24
27
.0
.7
.5
.4
.9
.7
.3
.3
.5
S=S=:BS
52,
46.
14.
64.
46,
19,
20,
30,
39,
.8
.3
,3
.2
.2
.8
.8
.2
.1
48
43
14
58
47
22
26
31
47
.4
.8
.7
.4
.3
.0
.5
.2
.5
ssss
47.
43.
15.
54.
45.
22.
28.
28.
52.
,5
,7
,8
,7
,5
,7
,4
,4
,3
S3S3S
                                                                                             339.0
                                               B-81

-------
Policy Options  for Stabilizing Global Climate
SCHP
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                          TABLE B-103

                                  SECONDARY OIL CONSUMPTION
                                        (Exajoules/Yr)
                                  1985
                                 100.6
                                              2000
                                                          2025
                                                                      2050
                                             107.3
                                                         113.3
                                                                     130.2
2075
                                                                                 134.8
                                                                                              2100
28
25
8
14
2
3
3
8
6
.8
.8
.0
.6
.2
.4
.1
.6
.1
26.
25
7
17
2
5
3
10
7
.4
.1
.8
.6
.9
.1
.8
.7
.9
23.
22
6
18
4
7
6
13.
11
.0
.5
.7
.4
.5
.6
.2
.4
.0
21.
21
7
19.
6
12.
9.
16.
16
.7
.3
.3
.1
.8
.4
.3
.1
.2
19,
19,
7,
18,
8,
13.
. 11.
16,
19,
.7
.8
,5
,2
.5
..6
,5
.2
.8
20
. 20
.. • 8
•19
11
.14
13
15
,23
.3
...5,
...4--
:. 4r
.4;
,6
.2
.2
.5
                                                                                             146.5
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                          TABLE B-104

                                  SECONDARY GAS CONSUMPTION
                                        (Exajoules/Yr)
                                  1985
                                  48.8
                                              2000
                                              47.6
                                                          2025
                                                                      2050
                                                                                  2075
                                                          62.6
                                                                      81.4
                                                                                  78.2
                                                                                              2100
15,
10.
1,
17,



2.
1.
,6
,3
,3
,1
.3
.5
,4
,1
,2
14.
9.
1.
16.



2.
1.
,2
,7
,2
,8
.3
.6
,6
,6
.6
15.
10.
1.
20.

2.
1.
5.
4.
,7
,6
.7
,3
,8
,1
,5
,9
.0
18.
12.
2.
24
1
4
2
8
6
.5
.9
.0
.4
.3
.0
.8
.6
.9
16.
11.
2.
21.
1.
4.
3,
8.
8.
.8
.9
.0
.3
.3
.3
.6 .
.8
.2
•15.
11
2.
18
1.
. 3,
, ,, 3.
7.
8,
.6
.3
.0
.6
.3
.9
.6
.6
.7
                                                                                              72.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-105

                                 SECONDARY SOLIDS CONSUMPTION
                                        (Exajoules/Yr)
                                  1985
                                  45.0
                                              2000
                                              57.3
                                                          2025
                                                                      2050
                                                          66.1
                                                                      64.4
                                                                                  2075
                                                                                  64.8
                                                                                              2100
3,
6,
2,
12,
14,

1,

3,
.8
.3
.6 .
.9
.5
.0
.2
,6
.1
4.
7,
2.
14.
20.

1,
1,
4,
.5
.2
,9
.7
.2
.0
.9
.1
.8
3.
5.
2.
11.
29.

3.
1.
8.
,4
.7
.6
,4
,4
.0
,5
.7
.4
2
4
2
8.
29.

5.
1.
9,
.7
.5
.2
.9
.7
.0
.1
.6
.7
2,
4.
2.
7.
28.

6.
1.
11.
,5
.5
.3
7
2
0
5
.8
.3
. 2.
.4.
2,
6,
.. . 23,,

6,
1,
10
.4
.4
.3
,4
,4
.0
.3
.4
.8
                                                                                              57.4 .
                                               B-82

-------
                                                     Appendix B: Implementation of the Scenarios
SCWP
                                          TABLE B-106

              RESIDENTIAL/COMMERCIAL  ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                       FUEL CONSUMPTION

                                  1985         2000
                                  A7.9
                                                         2025
                                                          56.2
                                                                     2050
                                                                     6A.7
                                                                                 2075
                                                                                             2100
11.
12.
1.
13.
A.


1.
2.
.5
9
.6
2
3
.2
.A
,6
,2
10
13
1
12
5


2
3
.1
.3
.7
.9
.3
.A
.9
.2
.1
10,
11.
1.
15.
6.
1.
2.
3
A
.3
.7
.5
.A
.1
.0
.1
.2
.9
10.
11.
1.
16.
7 c
1.
3.
A.
7.
.7
.5
.6
.A
.7
.8
.A
,5
,1
9
10
1
1A
8
2
A
A
8
.2
.0
.6
.1
.7
.2
.5
.9
.7
3.
' ' 9.
1
12
8
2.
A
A
9
.2
.0
.5
.1
.9
.3
.A
.6
.1
                                                                                             60.1
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                   ELECTRICITY  CONSUMPTION
                                  1985
                                  13.7
                                              2000
                                                         2025
                                                                     2050
                                                                                 2075
                                              16.A
                                                          21:9
                                                                     25.2
                                                                                 27.1
                                                                                             2100
5
A.
1.
1.





.2
.5
.1
.3
.2
.1
.3
.5
.5
6
A
1
2





.0
.A
.2
.0
.5
.2
.5
.8
.8
6,
A.
1,
3,
1.


1.
1.
,7
.6
.3
.8
.2
.6
.9
.2
.6
6.
A.
1.
3.
1.
1.
1.
1.
2.
.7
.3
.5
.9
.8
,1
.6
,7
.6
6.
A.
1.
3.
2.
1,
2.
2,
3.
.2
.1
,5
.7
.3
,5
.3
.0
.5
5,
3
1
3
2
1
2
2
A
.9
.9
.6
.3
.7
.8
.5
.1
.1
                                                                                             27.9
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    TOTAL ENERGY  CONSUMPTION
                                1985
                                61.6
                                            2000
                                            66.3
                                                        2025
                                                                   2050
                                                        78.1
                                                                               2075
                                                                               91.0
                                                                                           2100
16.
17.
2.
1A.
A.


2.
2.
7
A
7
5
.5
3
7
1
7
16
17
2
1A
5

1
3
3
.1
.7
.9
.9
.8
.6
.A
.0
.9
17.
16.
2,
19
7.
1.
3
A
6
.0
.3
.8
.2
.3
.6
.0
.A
.5
17
15
3
20
9
2
5
6
9
.A
.8
.1
.3
.5
.9
.0
.2
.7
15.
1A.
3.
17.
11.
3.
6.
6.
12.
A
1
.1
,8
.0
.7
.8
,9
,2
1A.
12.
3.
15.
11.
A.
6.
6.
13.
.1
.9
.1
.A
.6
.1
,9
.7
,2
                                                                                           88.0
                                               B-83

-------
Policy Options for Stabilizing Global Climate
SCWP
REGION
                                           TABLE B-107

                     INDUSTRIAL ENERGY CONSUMPTION:  FUEL  VERSUS  ELECTRICITY
                                         (Exajoules/Yr)
                                                                      2050
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia


1985
15
13
5
23
11
3
2
5
5
.6
.9
.4
.7
.5
.0
.1
.5
.4
FUEL CONSUMPTION
2000
16.6
14.5
5.8
26.2
16.6
4.4
2.8
7.7
8.1

2025
13.7
11.6
4.7
21.3
25.5
7.1
4.4
11.1
13.4
TOTAL
                                  86.1
                                             102.7
                                                         112.8
                                                                      18.1
                                                                     130.4
                                                                                  2075
                                                                                              2100
                                                                                 125.8
                                                                                              19.2
                                                                                             110.3
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    ELECTRICITY CONSUMPTION

                                  1985        2000 c       2025
                                  19.2
                                                                      2050
                                              23.9
                                                          27.4
                                                                      32.4
                                                                                  2075
                                                                                  34.7
                                                                                              2100
3.
3.
1
7
1.




.2
.5
.3
.1
.6
.4
.5
.8
.8
3.
3.
1,
8.
2.


1.
1.
7
.9
4
.4
,6
.7
.7
.2
.3
3,
3,
1,
7,
5,
1.
1,
2,
2,
.2
.3
.2
.5
.0
.4
.2
,1
.5
3.
3.
1.
7,
6.
2.
2,
2,
3,
.2
,3
,3
,9
.5
,3
,0
.2
,7
3.
3.
1.
7.
6.
2.
2.
2.
4.
2
5
,4
.5
8
.6
.6
4
7
3,
3,
1,
7,
6.
2.
2.
2.
5.
.3
.6
.5
.0
,4
.4
.8
,1
.1
                                                                                              34.2
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                   TOTAL ENERGY CONSUMPTION
                                  1985
                                 105.3
                                              2000
                                             126.6
                                                          2025
                                                                      2050
                                                         140.2
                                                                     162.8
                                                                                  2075
                                                                                 160.5
                                                                                              2100
18.
17.
6.
30.
13.
3.
2.
6.
6.
8
4
7
8
1
4
6
3
2
20.
18.
7,
34.
19.
5.
3,
8
9
.3
,4
.2
.6
.2
.1
.5
.9
.4
16.
14.
5.
28.
30.
8.
5.
13.
15.
9
.9
9
8
.5
5
.6
.2
.9
18,
15.
6,
29,
31,
14.
9,
16.
21.
,2
.6
,2
,5
.8
,5
.0
,2
,8
17.
15.
6.
26.
29.
14.
11.
15.
24.
0
3
3
1
4
6
1
9
8
16,
15,
6.
22.
23.
12.
11.
12.
24.
,3
,0
,3
,9
7
2
0
,8
,3
                                                                                             144.5
                                               B-84

-------
                                                     Appendix B: Implementation of the Scenarios
SCWP
                                          TABLE  B-108

                  TRANSPORTATION  ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
FUEL CONSUMPTION
1985
21
15
4
7
1

2
4
2
.1
.6
.9
.7
.2
.7
.2
.2
.8
2000
18
14
4
10
1

2
4
3
.4
.2
.4
.0
.5
.9
.6
.5
.1
2025
18
15
4
13
3
1
4
6
5
.1
.5
.8
.4
.1
.6
.7
.7
.1
2050
17.
14.
5.
14.
4.
2,
6.
7
7
.2
.9
.0
.4
.8
.4
.8
.8
.6
2075
16,
14
5,
14
6
3
8
8
10
.0
.4
.3
.5
.7
.7
.6
.4
.5
2100
17
15
6
16
9
6
10
8
14
.1
.8
.4
.4
.9
.4
.5
.9
.7
                                  60.4
                                              59.6
                                                          73.0
                                                                     80.9
                                                                                 88.1
                                                                                            106.1
                                   ELECTRICITY  CONSUMPTION
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
TOTAL
2025

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
2050

  .0
  .0
  .0
  .0
  .1
  .0
  .0
  .0
  .0

  .1
2075

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .0

  .2
 2100

   .0
   .0
   .0
   .0
   .3
   .0
   .0
   .0
.   .1

   .It
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                   TOTAL  ENERGY  CONSUMPTION
                                  1985
                                  60.4
                                              2000
                                              59.6
                                                          2025
                                                                     2050
                                                                                 .2075
                                                          73.0
                                                                      81.0
                                                                                 88.3
                                                                                             2100
21.
15.
4.
7.
1.

2.
it.
2:
,1
6
.9
,7
.2
,7
.2
.2
,8
18.
14.
it
10.
1,

2.
4.
3.
,4
.2
.4
.0
,5
,9
.6
.5
.1
18.
15.
4.
13.
3.
1.
4.
6.
5.
1
5
8
4
1
6
7
7
1
17
14
5
14
4
2
6
7
7
.2
.9
.0
.4
.9
.4
.8
.8
.6
16.
14.
5,
14,
6.
3,
8.
8.
10,
.0
.4
.3
.5
.9
.7
.6
.4
.5
17
15,
6.
16,
10
6,
10,
8,
14,
.1
.8
.4
.4
.2
.4
.5
.9
.8
                                                                                            106.5
                                               B-85

-------
Policy Options for Stabilizing Global Climate
SCHP
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-109

                             ELECTRIC UTILITY ENERGY CONSUMPTION
                                        CExajoules/Yr)
                                  1985
                                 105.3
                                              2000
                                                          2025
                                                                      2050
                                             123.6
                                                         144.0
                                                                     165.2
                                                                                  2075
                                                                                 173.8
                                                                                              2100
26,
24.
7.
26.
6.
1.
2.
4,
4,
,6
,6
4
,4
8
,9
.7
.3
,6
29
24
8.
31
10
3
3
6
6
.3
.8
.0.
.4
.5
.0
.7
.0
.9
28,
22,
7,
32.
18.
5,
6,
9,
12,
,5
.9
,3
,2
,7
,6
.4
,9
,5
27.
22,
7,
33.
24.
9,
10,
11.
18,
,7
,0
,9
.0
.5
.4
.4
,8
,5
25.
21.
8.
30.
26.
11,
13.
13,
23.
8
8
1
3
,2
,1
,7
.3
.5
25,
21,
8
28,
26
11
14
12
26
.2
,9
.6
.4
.6
.4
.9
.6
.4
                                                                                             176.0
                                          TABLE B-110

                ENERGY CONVERSION EFFICIENCY AT ELECTRIC UTILITY POWERPLANTS*
                                          (percent)
REGION
                                  1985
                                              2000
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
  Includes transmission and distribution losses
                                                          2025
                                                                      2050
                                                                                  2075
                                                                                              2100
31.
32.
32.
31.
26.
26.
22.
30.
26.
,2
,5
,4
,4
,5
,3
,2
.2
,1
33.
33.
32.
32.
29.
26,
29.
33.
31.
,4
,5
,5
,8
,5
,7
,7
,3
,9
34
34,
35,
34,
32,
35.
32,
33,
33,
.7
.1
.6
.8
.6
.7
.8
.3
.6
35
35
35
35
33
36
36
33
34,
.4
.0
.4
.5
.9
.2
.5
.1
.1
37.
34.
37,
37.
35.
36.
36,
33,
35.
,2
,9
,0
,0
,9
,0
.5
,1
.3
36.
34.
37.
36.
35.
36.
36.
33.
35.
5
7
2
6
,7
0
,2
.3
2
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                          TABLE B-lll

                             SYNTHETIC PRODUCTION OF OIL AND GAS
                                        (Exajoules/Yr)

                                      OIL FROM SYNFUELS

                                  1985        2000        2025        2050
  .0          .0
  .0          .0
  .0          .0
  .0          .0
  .0          .0
  .0          .0
  .0          .0
  .0          .0
  .0          .0
                                    .0          .0          .0        44.5
                                                                                  2075
                                                                                              2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
3.6
2.5
1.3
6.6
3.. 1
.0
8.7
13.0
5.7
6.7
4.8
2.4
12.5
5.9
.2
16.3
24.5
10.8
9.4
6.7
3.4
17.5
8.3
.3
22.8
34.2
15.0
                                                                                  84.1
                                                                                             117.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                       GAS FROM SYNFUELS
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                              2000
                                                          2025
                                                          26.0
                                                                      2050
                                                                      72.6
                                                                                  2075
                                                                                  70.4
                                                                                              2100
0
0
0
0
0
0
0
0
0
2
1

3
1

5
7
3
.1
.5
.7
.9
.8
.0
.1
.6
,3
5,
4,
2,
10,
5,

14,
21,
9,
.8
.1
.1
.8
.1
,2
,1
.1
,3
5.
4,
2,
10,
4,

13,
20,
9
.6
.0
.0
.5
.9
.2
.7
.5
.0
5
3
2
10
4

13
20
8
.5
.9
.0
.3
.8
.2
.4
.2
.9
                                                                                              69.2
                                               B-86

-------
                                                     Appendix  B:  Implementation of the Scenarios
 SCWP
                                         TABLE B-112

                       ENERGY USED FOR SYNTHETIC FUEL PRODUCTION BY TYPE
                                        (Exajoules/Yr)
 REGION

 United States
 OECD- Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
• Africa
 Latin America
 South and East Asia
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                            COAL
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2025

  .0
  .0
  .0
  .0
  .1
  .0
  .0
  .0
  .0
2050

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2075

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
2100

  .0
  .0
  .0
  .0
  .1
  .0
  .0
  .0
  .0
 TOTAL
 REGION

 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                          BIOMASS
                                              2000
                                                          2025
                                                                      2050
                                                                                  2075
                                                                                              2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
2,
2.
1,
5.
2,

6.
10,
4.
,8
.0
.0
.1
.4
.0
.7
.1
.4
12
8.
4
23
10

30
45
19
.4
.8
.5
.1
.9
.3
.3
.4
.9
16.
11
5
30
14

39
59
26
.3
.7
.9
.5
.4
.5
.9
.8
.3
19.
14.
7.
36.
17

48.
72
31.
.7
.1
.1
.8
.4
.5
.2
.3
.7
 TOTAL
                                                          34.5
                                                                     155.6
                                                                                 205.3
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
-Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
                                            TOTAL
                                              2000
                                                          2025
                                                                      2050
                                                                                  2Q75
                                                                                              2100
0
0
0
.0
o •
0
0
0
0
2
2
1
5
2

6
10
4
.8
.0
.0
.1
.5
.0
.7
.1
. /t
12,
8,
4,
23.
10,

30,
45,
19,
,4
.8
.5
.1
.9
,3
.3
.4
.9
16,
11.
5
30
14.

39.
59.
26
.3
.7
.9
.5
.4
.5
.9
.8
.3
19.
14,
7,
36,
17,

48,
72,
31,
,7
,1
.1
.8
.5
.5
.2
,3
.7
                                                          34.6
                                                                                 205.3
                                                                                             247.9
                                                B-87

-------
 Policy Options for Stabilizing Global Climate
-SCWP
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-113

                               C02 EMISSIONS FROM FOSSIL FUEL
                                        (Petagrams C/Yr)
                                  1985
                                   5.1
                                              2000
                                                          2025
                                                                      2050
                                               5.6
                                                           5.5
                                                                       4.2
                                                                                  2075
                                                                                   3.3
                                                                                              2100
1


1





.3
.9
.3
.3
.6
.1
.1
.2
.3
1.2
.9
.3
1.4
.8
.1
.2
.2
.4
1


1
1




.0
.8
.3
.2
.0
.2
.2
.3
.5
.8
.7
.2
.9
.9
.3
.0
-.1
.5
.6
.6
.2
.6
.8
.4
-.0
-.3
.5
.5
.5
.2
•• .'5
.7
.4
-.1
~* . 6
.5
                                                                                               2.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-114

                                CO EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams C/Yr)
                                  1985
                                  185.8
                                              2000
                                              135.5
                                                          2025
                                                                      2050
                                                         102.1
                                                                      64.6
                                                                                  2075
                                                                                  69.7
                                                                                              2100
51.
44,
14.
31.
6.
2.
8.
16.
11.
.0
,7
.1
.1
.0
.9
.5
.3
.2
24.
32.
10.
29,
6,
2,
7
12,
9.
.4
.4
,1
,9
,2
,6
.5
.9
.5
14
12
3
26
8
3
9
13
10
.1
.4
.8
.7
.4
.3
.5
.2
.7
12.
10.
3.
11.
6.
2.
5.
6.
6.
3
9
.7
.3
,0
.0
.6
,3
.6
11.
10.
3.
11.
7.
2.
7.
6.
8.
5
5
.9
,2
.3
.9
.0
,7
.8
12,
11,
4
12,
9.
4,
8
7
11.
.2
.4
.7
.4
.3
.7
.3
.0
.7-
                                                                                              81.6
 REGION
 United  States
 OECD  Europe/Canada
 OECD  Pacific
 Centrally  Planned Europe
 Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East Asia

 TOTAL
                                          .TABLE B-115

                               NOx EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams N/Yr)
                                   1985
                                  24.2
                                              2000
                                                          2025
                                                                      2050
                                              24.6
                                                          22.0
                                                                       18.3
                                                                                  2075
                                                                                  18.2
                                                                                              2100
6,
4.
1.
5.
2,


1,
1,
,1
,6
.7
,8
.6
.4
.8
.0
.3
5
4
1
6
3

1
1
1
.1
.0
.5
.2
.5
.5
.0
.1
.6
3
2

4
4

1
1
2
.2
.6
.9
.7
.4
.7
.5
.7
.3
2
2

3
2

1
2
2
.7
.4
.9
.1
.4
.7
.8
.1
.1
2.
2.

2.
2.

1.
2.
2.
4
3
9
9
4
8
9
1
4
2
2
1
3
2
1
2
2
2
.5
.4
.0
.0
.6
.0
.1
.1
.9
                                                                                              19.
                                                B-88

-------
                                                     Appendix B:  Implementation of the Scenarios
RCWP
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                             1985
                            301.6
                                         TABLE  B-116

                                     PRIMARY ENERGY SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                        353.0
                                                     2025
                                                                 2050
                                                    526.3
                                                                680.4
                                                                            2075
                                                                           790.2
                                                                                        2100
63
47
8
81
25
23
16
20
14
.7
.6
.9
.2
.6
.7
.3
.5
.1
52
47
11
86
41
48
22
23
19
.1
.7
.1
.0
.7
.2
.8
.7
.7
48
45
12
93
87
63
55
72
47
.7
.9
.6
.4
.0
.5
.6
.1
.5
59.
50,
16.
118.
122.
56.
80.
102.
7/t
z^Zi
.8
,4
.1
.8
.1
.5
.1
.3
.3
71
55
18
133
142
51
94
123
99
.0
.9
.8
.3
.8
.1
.5
.3
.5
77.
57.
20.
139,
152.
52.
98,
134,
119,
;=:
.9
.5
,8
,6
.3
.4
,0
.1
.4
                                                                                       852.0
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                            117.9
                                          TABLE B-117

                                      PRIMARY OIL SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                                     2025
                                                                 2050
                                        123.3
                                                    117.9
                                                                 91.8
                                                                            2075
                                                                            57.4
                                                                                        2100
20.8
11.9
1.1
26.0
5.2
22.4
10.8
14.1
5.6
11.6
8.8
.6
20.9
6.5
45.2
15.1
10.3
4.3
5.9
7.2
.2
16.2
6.5
52.4
16.5
9.6
3.4
3.5
5.8
.0
12.0
5.1
37.4
16.6
8.8
2.6
2.0
3.6
.0
7.2
3.1
23.4
10.8
5.7
1.6
2.3
2.2
.0
4.4
1.8
16.3
6.9
8.8
1.1
                                                                                        43.8
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        58.6
                                          TABLE B-118

                                      PRIMARY GAS SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                                     2025
                                                                 2050
                                         71.9
                                                     61.6
                                                                 48.4
                                                                            2075
                                                                             45.9
                                                                                        2100
16.
9.

24.

1.
1.
2.
2.
3
7
7
,0
.5
.2
.3
.5
,4
15.
11.
1.
28.
1,
2.
2.
4,
3,
,3
.6
.6
.4
9
,8
.6
.6
,1
7.
6.
1.
25.
4,
8.
2.
3,
2,
.8
.5
.1
,6
.4
.2
.0
,3
.7
4.
4.

24.
3.
8.


1.
4
1
5
0
6
9
4
7
8
5.
5.

15.
2.
12.
1.
2.
1,
1
.5
.1
.0
.3
,8
,2
.1
.8
4.
5.

8.
• 1.
17,
3.
5,
1.
,8
,1
.0
,1
.3
,5
,0
.5
,4
                                                                                        46.7
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        87.3
                                          TABLE B-119

                                      PRIMARY COAL SUPPLY
                                        (Exajoules/Yr)
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
                                        105.2
                                                    107.3
                                                                122.0
                                                                            140.2'
                                                                                        2100
19.
9,
3
26
18

4

4
.4
.4
.9
.7
.9
.0
.0
.6
.4
16.
10.
4.
29.
30.

4.
1.
8.
.0
.4
.9
.4
.2
.0
,5
.1
.7
11
6
3
17
49

6
2
10
.4
.3
.4
.2
.7
.0
.5
.1
.7
14
5
3
20
59

8
3
6
.4
.9
.4
.3
.1
.0
.5
.6
.8
19
6
3
30
63

10
2
4
.1
.2
.7
.8
.2
.0
.4
.6
.2
•SSTTTT
23.
6.
4.
38.
62.

11.
1.
3.
0
9
7
8
8
0
5
6
2
                                                                                        152.5
                                               B-89

-------
 Policy Options For Stabilizing Global Climate
-RCWP
 REGION                       1985
 United States                   .0
 OECD  Europe/Canada              .0
 OECD  Pacific   '     •           .0
 Centrally Planned Europe        .0
 Centrally Planned Asia         .0
 Middle East                     .0
 Africa                         .0
 Latin America                   .0
 South and East  Asia            .0

 TOTAL  '                        .0
                                           TABLE  B-120

                                      PRIMARY BIOMASS SUPPLY
                                          (Exajoules/Yr)
                                          2000
                                                      2025
                                                     135.8
                                                                 2050
                                                                             2075
                                                                215.
                                                                            272.6
                                                                                         2100
0
0
0
0
0
0
0
0
0
10.
7.
3.
20,
9,

26.
39,
17.
.8
.7
.9
,2
.5
.3
.4
.6
.4
17
12.
6
32,
15

41
62
27
.1
.2
.2
.0
.1
.5
.9
.8
.6
21
15,
7
'••'• 40
19,

53
79
34
.7
.5
.8
.5
.1
.6
.0
.5
.9
21,
15.
7.
•'• 40,
" 19:

53,
79
34,
.7
:5
.8
.5
.1;
.6
.0
.5
.9
                                                                                        272.6
 REGION
                                           TABLE  B-121

                                   PRIMARY  HYDROELECTRIC SUPPLY
                                         (Exajoules/Yr)
                              1985
                                          2000
                                                      2025
                                                                 2050
 TOTAL
                              21.2
                                          31.9
                                                      53.4
                                                                  66;9
                                                                             2075
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
3,
8.
1.
2.
1,


3,
1.
,3
.2
.2
.5
.0
.1
.2
.3
.4
3.
9.
1.
3.
2.


7.
2.
9
7
3
2
6
2
5
7
8
SS=
4.
10.
1.
3.
7.

1.
16.
6.
4 '
.8
:3
.7
,6
,5
7
,5
.9
===
4.
11.
1,
3,
10,

4,
20.
10.
.7
,0
.4
,7
.8
.6
.2
.0
.5
4.
11.
1,
3.
11

6
20
11
.7
.1 '
.4
.7
.5
.7
.2
.6
.9
=S5SS
4.8
11.1
1.5
3.7
11.6
.7
7.0
20.7
12.4
                                                                                         73.5
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
                              1985
                              16.5
                                           TABLE  B-122

                                      PRIMARY  NUCLEAR SUPPLY
                                         (Exajoules/Yr)
                                          2000
                                          18.4
                                                      2025
                                                                 2050
                                                                             2075
                                                      31.2
                                                                  70.6
                                                                            110.2
                                                                                         2100
3.
8.
2.
2.





,8
4
0
0
.0 •
,0
.0
,0
.3
4.
6,
2.
3.





,7
9
,5
.4
.2
,0
.1
,0
.6
5.
5.
1.
6,
5.
1.
1,

3,
,2
.8
,9
,2
.5
.1
.3
.5
.7
7.
7.
2.
13.
14.
4.
4.
3.
12.
9
,6
.6
.5
,3
.6
.3
.2
,6
9;
9,
3.
19,
23,
7,
6,
6.
24,
.8 '
,7
,4
,2
.2
.2
.9
.8
.0
11.
12.
4.
24.
31.
9.
9.
10,
37,
,9
.0
;2
.7
.2
.7
.3
,1
.2
                                                                                        150.3
 REGION                       1985

 United States                  .1
 OECD Europe/Canada             .0
 OECD Pacific      '             .0
 Centrally Planned Europe       .0
 Centrally Planned Asia         .0
 Middle East                    .0
 Africa                         .0
 Latin America                  .0
 South and East Asia            .0

 TOTAL            .              .1
                                           TABLE B-123

                                      PRIMARY SOLAR SUPPLY
                                         (Exajoules/Yr)
2000

  .6
  .3
  .2
  .7
  .3
  .0
  .0
  .0
  .2

 2.3
                                                      2025
                                                                  2050
                                                                             2075
                                                                                         2100
3.
1.

4.
3.
i;
1.

2.
2
6
8
3
8
0
2
5
7
7,
3
2,
13,
14,
4.
4,
3,
12,
.8
.8
.0
.3
.1
.5
.2
.2
.4
8
4
2
16
20
6
6
6
21
.6
.3-
.4
.9
.4
.4
.0
.0
.1
=:=3
9,
4,
2,
19
24
7,
7
7
29
.4
,7
.6
.4
.5
.6
.3
.9
.2
                                                      19.1
                                                                  65.3
92.1
           112.6
                                                B-90

-------
                                                     Appendix B:  Implementation of the Scenarios
RCWP
REGION
                                          TABLE B-124

                                   PRIMARY ENERGY CONSUMPTION
                                        CExajoules/Yr)
                             1985
                                         2000
                                                    2025
                                                                2050
                                                                            2075
TOTAL
                            300.2
                                        353.2
                                                    526.7
                                                               680.0
                                                                           789.3
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
74.
67.
19.
71.
23.
5.
7.
15.
15.
9
0
3
1
8
8
6
6
1
71.
64
20,
84
40
9
12
24
26
.8
.1
.1
.8
.4
.3
.2
.5
.0
71
62
19.
92.
90
24
34
64
67
.2
.6
,7
.4
.7
.2
.0
.7
.2
69
60.
20
111
128
35
51
89
114
.2
.9
.5
.2
.0
.2
.0
.9
.1
67.
60.
21.
125,
152,
40,
62
103
155,
,6
,9
.3
,0
,2
.7
.7
.6
.3
68.9
62.2
22.3
131.6
164.6
43.0
67.9
107.1
185.9
                                                                                       853.5
                                          TABLE B-125

                     SECONDARY ENERGY  CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
REGION
                             1985
TOTAL
                            194.4
                                        FUEL CONSUMPTION
                                         2000
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
48
42.
11.
44
17
3
4
11
10
.2
.4
.9
.6 .
.0
.9
.7
.3
.4
42.3
40.1
12.2
50.3
26.7
5.?
7.4
16.8
16.4
                                        218.1
                                                    2025
                                                   286.6
                                                                2050
                                                               329.7
                                                                            2075
                                                                           341.8
                                                                                        2100
39.
35.
11.
49.
50.
14,
16,
35,
34,
.1
.2
.1
,4
.9
,5
.5
.1
.8
33
30.
10
53
64
19
21
43
53.
.4
.1
.2
.9
.3
.4
.6
.3
.5
29,
27.
9.
55.
68.
19,
23,
43,
65.
.2
,0
.7
.4
,3
.9
.6
.7
.0
27
25
9.
53
67
18
23
40
68
.6
.4
.4
.5
.0
.3
.4
.6
.4
                                                                                       333.6
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                                    ELECTRICITY CONSUMPTION

                                         2000         2025
                                                                2050
                                                                            2075
                                                                                        2100
8
8
2
8
1


1
1
32
.4
.0
.4
.4
.8
.5
.8
.3
.3
.9
9.
8.
2.
11.
4.
1.
1.
2.
2.
43.
8
0
6
4
.0
.0
4
.6
.9
.7
10.
8,
2.
13,
12,
3,
3,
6,
9,
71.
.4
,8
.7
.4
.8
.4
,8
.7
.7
.7
11.
9.
3.
17.
21.
5,
6.
10,
19,
104,
.3
.6
.1
.9
.2
.5
.6
.6
.0
.8
12
10
3
21
28
7
9
14
29
137
.0
.5
.5
.8
.7
.5
.3
.0
.7
.0
12.
11.
3.
24.
33.
8.
11.
16.
39.-
161.
8
4
9
5
3
8
1
4
3
5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                            227.3
                                    TOTAL ENERGY  CONSUMPTION
                                         2000
                                        261.8
                                                     2025
                                                                2050
                                                                            2075
                                                    358.3
                                                               434.5
                                                                           478.8
                                                                                        2100
56.
50.
14.
53.
18.
4.
5.
12,
11,
.6
.4
.3
,0
,8
.4
,5
,6
,7
52.
48,
14,
61,
30.
6.
8,
19,
19,
,1
,1
.8
.7
,7
,9
.8
.4
.3
49.
44.
13.
62.
63.
17.
20.
41.
44,
.5
.0
.8
,8
.7
,9
.3
,8
,5
44,
39,
13,
71,
85,
24,
28,
53,
72,
.7
.7
.3
.8
.5
.9
.2
.9
.5
41.
37.
13.
77.
97.
27.
32.
57.
94,
.2
.5
.2
.2
.0
.4
.9
J
.7
40
36
13
78,
100,
27,
34,
,57.
107
.4
.8
.3
.0
.3
.1
.5
.0
.7
495.1
                                               B-91

-------
 Policy Options for Stabilizing Global Climate
-RCWP
REGION
United  States
OECD Europe/Canada
OECD Pacific
Centrally  Planned Europe
Centrally  Planned Asia
Middle  East
Africa
Latin America
South and  East Asia

TOTAL
                              1985
                                           TABLE B-126

                                    SECONDARY OIL CONSUMPTION
                                          (Exajoules/Yr)
                             100.6
                                          2000
                                         108.5
                                                     2025
28.
25.
8.
14.
2.
3.
3.
8,
6.
8
8
0
6
2
4
. 1
6
,1
24.
23.
7.
17,
3.
5.
i, c
12,
9,
.6
.7
,9
,7
.3
.3
.4
.5
,1
19
19
6
16
7
10
9
20
16
.2
.2
.9
.7
.4
.8
.4
.9
.5
                                                     127.0
                                                                 2050
                                                                132.0
                                                                             2075
                                                                            132.6
                                                                                         2100
14.
14.
5.
16,
9.
14.
10,
23,
24,
,0
,3
,7
,1
,8
,0
. 4
,7
,0
11.
12.
5,
16,
11.
14,
10.
22,
28,
.6
,0
,1
,2
.9
,1
,4
,8
,5
11.
11.
5,
18,
15.
13,
10,
21,
32
,5
5
.0
,2
,1
,2
.6
.8
.2
                                                                                        139.1
REGION                        1985
 United  States
 OECD  Europe/Canada
 OECD  Pacific
 Centrally  Planned Europe
 Centrally  Planned Asia
 Middle  East
 Africa
 Latin America
 South and  East  Asia
 TOTAL                         48.8
                                           TABLE B-127

                                    SECONDARY GAS CONSUMPTION
                                          (Exajoules/Yr)
                                          2000
                                                     2025
                                                                 2050
                                                                             2075
                                          48.9
                                                      86.4
                                                                 107.5
                                                                            112.6
                                                                                         2100
15.6
10.3
1.3
17.1
.3
.5
.4
2.1
1.2
13.3
9.5
1.3
17.9
.4
.6
.8
332
1.9 .
17.7
12.0
2.0
24.9
1.9
3.7
2.9
12.5
8.8
17.2
11.8
2.2
30.1
2.9
5.4
4.8
17.7
15.4
15.3
10.8
2.1
30.9
3.3
5.8
5.7
18.9
19.8
13.6
9.5
1.8
26.3
3.3
5.1
5.3
16.9
18.7
                                                                                        100.5
                                           TABLE B-128

                                   SECONDARY  SOLIDS CONSUMPTION
                                         (Exajoules/Yr)
 REGION                        1985
 United  States
 OECD  Europe/Canada
 OECD  Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle  East
 Africa
 Latin America
 South and East  Asia
 TOTAL                         45 .0
                                          2000
                                                     2025
                                                                 2050
                                          60.7
                                                      73.2
                                                                 90.2
                                                                             2075
                                                                             96.6
                                                                                         2100
3,
6,
2,
12.
14,

1,

3
.8
.3
.6
.9
.5
.0
.2
.6
.1
4,
6.
3.
14.
23.

2,
1,
5,
.4
.9
,0
.7
.0
,0
.2
.1
.4
2.
4,
2,
7
41,

4,
1,
9
.2
,0
,2
,8
.6
,0
.2
.7
.5
2,
4.
2.
7.
51.

6,
1.
14,
.2
.0
,3
.7
.6
.0
.4
.9
.1
2
4
2
8
53

7
2
16
.3
.2
.5
.3
.1
.0
.5
.0
.7
2,
4,
2.
9.
48.

7.
1.
17.
.5
,4
,6
,0.
,6
0
5
9
5
                                                                                         94.0
                                                B-92

-------
                                                    Appendix B:  Implementation of the Scenarios
RCWP
                                          TABLE B-129

               RESIDENTIAL/COMMERCIAL  ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                         (Exajoules/Yr)
                                        FUEL CONSUMPTION
REGION
                             1985
                                         2000
                                                    2025
                                                                2050
TOTAL
                             47.9
                                         47.5
                                                    54.5
                                                                            2075
                                                                            78.4
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
11.
12.
1.
13.
4.


1.
2,
. 5
.9
.6
.2
.3
.2
.4
.6
.2
7
12
1
13
5


2
3
.9
.4
.7
.0
.7
.4
.9
.3
.2
8
9
1
15
7
1
2
3
5
.1
.4
.2
.5
.8
.2
.1
.9
.3
7.
8,
1.
18.
13.
2.
3.
6
9
.8
.5
.3
.0
.1
.0
.5
.2
.4
6
7
1
18
17
2
4
7
12
.9
.6
.2
.3
.5
.4
.4
.6
.5
6.
6.
1.
16.
19.
2.
4.
7.
13.
0
6
0
8
8
5
5
6
7
                                                                                        78.5
REGION
                             1985
                                    ELECTRICITY CONSUMPTION
                                         2000
                                                    2025
                                                                2050
TOTAL
                             13.7
                                         16.4
                                                    26.7
                                                                            2075
                                                                            50.2
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
5
4
1
1





.2
.5
.1
.3
.2
.1
.3
.5
.5
5.
4.
1,
2.




1
.9
.0
.1
.3
.5
.2
.5
.9
•°»
6
5
1
5
1

1
1
3
.5
.2
.3
.3
.4
.8
.3
.8
.1
7.
5,
1.
7.
3.
1.
2.
3,
6.
.0
.4
.5
.0
.0
,5
.4
.4
.6
7
5
1
8
5
2
3
5
11
.3
.7
.7
.4
.0
.4
.6
.1
.0
7.6
6.1
1.9
9.3
7.0
3.1
4.5
6.5
15.2
                                                                                        61.2
REGION
                            1985
                                    TOTAL  ENERGY CONSUMPTION
                                        2000
                                                   2025
                                                               2050
TOTAL
                            61.6
                                        63.9
                                                    81.2
                                                              107.6
                                                                           2075
                                                                          128.6
                                                                                       2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
16
17
2
14
4


2
2
.7
.4
.7
.5
.5
.3
.7
.1
.7
13
16
2
15
6

1
3
4
.8
.4
.8
.3
.2
.6
.4
.2
.2
14
14
2
20
9
2
3
5
8
.6
.6
.5
.8
.2
.0
.4
.7
.4
14.
13.
2,
25,
16.
3,
5.
9.
16.
.8
.9
.8
.0
.1
.5
.9
.6
.0
14
13
2.
26.
22
4
8
12
23
— sssssi — =
.2
.3
.9
.7
.5
.8
.0
.7
.5
13.
12.
2.
26.
26.
5.
9.
14.
28.
.6
,7
.9
.1
.8
,6
.0
.1
,9
==:
                                                                                      139.7
                                               B-93

-------
Policy Options for Stabilizing Global Climate
RCWP
                                          TABLE B-130

                     INDUSTRIAL ENERGY CONSUMPTION:  FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        86.1
                                       FUEL CONSUMPTION
                                         2000
                                                     2025
                                                                 2050
                                        112.9
                                                    160.8
                                                                194.7
                                                                             2075
                                                                            195.7
                                                                                         2100
15
13
5
23
11
3
2
5
5
.6
.9
.4
.7
.5
.0
.1
.5
.4
17,
14.
6,
27,
19,
4
3,
9
10
,3
.8
.2
,6
.3
.6
,6
.5
.0
16.
13,
5.
22,
38.
11,
7,
21,
24.
.4
,0
.5
,2
.9
,2
,7
.8
.1
15,
12
5,
24,
45,
14
11,
27,
36
.4
.7
.5
.8
.5
.9
.5
.6
.8
13.
11.
5.
25.
43.
14,
12.
26,
42,
8
,9
4
.5
,0
.4
.7
, 5
,5
12,
10,
5,
22,
35,
11,
11,
21,
39
.7
.9
.0
.2
.5
.4
.6
.8
.7
                                                                                        170.8
REGION
                             1985
                                    ELECTRICITY CONSUMPTION
                                         2000
                                                     2025
                                                                 2050
                                                                             2075
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
3
3
1
7
1




19
.2
.5
.3
.1
.6
.4
.5
.8
.8
.2
3.
4.
1.
9.
3.


1.
:t
27,
9
0
.5
1
,5
.8
,9
,7
,9
,3
3.
3.
1.
8.
11.
2.
2.
4.
6.
44.
9
6
4
1
2
,6
.5
.9
,5
,7
4.
4.
1.
10.
18.
4,
4,
7,
12,
66,
,3
,2
,6
,9
,0
,0
,2
,2
,2
.6
4,
4.
1,
13,
23,
5
5
8
18,
86
.7
.8
.8
.4
.3
.1
.7
.9
.4
.1
5.2
5.3
2.0
15.2
25.7
5.7
6.6
9.9
23.6
99.2
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                       105.3
                                    TOTAL ENERGY CONSUMPTION
                                         2000
                                        140.2
                                                     2025
                                                                 2050
                                                    205.5
                                                                261.3
                                                                             2075
                                                                            281.8
                                                                                         2100
18
17
6
30
13
3
2
6
6
.8
.4
.7
.8
.1
.4
.6
.3
.2
21,
18,
7.
36,
22.
5,
it
11,
11.
.2
,8
.7
,7
.8
.4
,5
.2
,9
20.
16.
6.
30.
50.
13.
10.
26.
30.
3
6
9
3
1
8
2
7
6
19,
16.
7.
35.
63.
18.
15.
34.
49,
,7
.9
,1
.7
.5
.9
,7
.8
.0
18,
16,
7,
38,
66,
19,
18.
35
60,
.5
.7
.2
.9
.3
.5
.4
.4
.9
17
16
7
37
61
17
18
31
63
.9
.2
.0
.4
.2
.1
.2
.7
.3
                                                                                        270.0
                                                B-94

-------
                                                     Appendix B: Implementation of the Scenarios
RCWP
                                           TABLE  B-131

                      TRANSPORTATION ENERGY CONSUMPTION:  FUEL VERSUS ELECTRICITY
                                          (Exajoules/Yr)
REGION
United States
OECD Europe/Canada .
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                             1985
                             60.4
                                        FUEL CONSUMPTION
                                         2000
                                         57.7
                                                     2025
                                                                2050
                                                     71.3
                                                                65.2
                                                                            2075
                                                                            67.7
                                                                                        2100
21.
15.,
4.
7.
1,

2.
4.
2,
.1
.6
.9
.7
,2
.7
.2
,2
.8
17
12
4.
9.
1.

2
5
3.
.1
.9
.3
.7
.7
.9
.9
.0
.2
14
12
4
11
4
2
6
9
5
.6
.8
.4
.7
.2
.1
.7
.4
.4
10.
8.
3,
11.
5.
2.
6
9
7
.2
.9
.4
.1
.7
.5
.6
.5
.3
8.
7.
3.
11,
7,
3,
6.
9.
10
.5
.5
, 1.
.6
,8
.1
.5
.6
.0
8.
7,
3.
14,
11,
4,
7,
11
15
.9
.9
,4
.5
.7
,4
.3
.2
.0
                                                                                        84.3
                                    ELECTRICITY CONSUMPTION
REGION
                             1985
                                         2000
                                                     2025
                                                                2050
                                                                            2075
                                                                                        2100
United States                  .0
OECD Europe/Canada             .0
OECD Pacific                   .0
Centrally Planned Europe       .0
Centrally Planned Asia         .0
Middle East                    .0
Africa                         .0
Latin America                  .0
South.and East Asia            .0

TOTAL
.0
.0
.0
.0
.2
.0
.0
.0
.2

.4
 .0
 .0
 .0
 .0
 .6
 .0
 .0
 .0
 .5

1.1
REGION                       1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL  :                      60.4
                                    TOTAL ENERGY CONSUMPTION
                                         2000
                                         57.7
                                                     2025
                                                                2050
                                                     71.6
                                                                 65.6
                                                                            2075
                                                                            68.4
                                                                                        2100
21
15
4
7
1

2
4
2
.1
.6
.9
.7
.2
.7
.2
.2
.8 •
17.
12.
4.
9.
1.

2.
5.
3.
,1
,9
,3
,7
,7
,9
.9
,0
.2
14.
12,
4,
11,
4,
2.
6.
9,
5,
.6
,8
.4
.7
.4
.1
.7
.4
.5
10.
8.
3.
11,
5.
2.
6.
9,
7.
,2
.9
.4
,1
,9
,5
.6
,5
,5
8.
7.
3,
11.
8.
3,
6.
9,
10.
.5
,5
.1
.6
.2
,1
,5
.6
,3
8,
7,
3,
14,
12.
4.
7.
11,
15,
,9,
.9
,4
.5'
.3
.4
,3
.2
.5
                                                                                        85.4
                                               B-95

-------
Policy Options for Stabilizing Global Climate
RCWP
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                          TABLE B-132

                              ELECTRIC UTILITY ENERGY CONSUMPTION
                                         (Exajoules/Yr)
                             1985
                            105.3
                                         2000
                                        134.9
                                                     2025
                                                                 2050
                                                    206.4
                                                                297 .4
                                                                             2075
                                                                            380.1
                                                                                         2100
26
24
7
26
6
1
2
4
4
.6
.6
.4
.4
.8
.9
.7
.3
.6
==-—
29
24.
7
34
13
3
4
7
9
.6
.0
.9
.5
.7
.2
.8
.7
.5
29.
25.
7.
38.
37.
9.
11.
19.
28.
5
4
6
0
4
6
0
9
0
:as:s
31.
27.
8.
49.
60.
15.
19.
31.
53.
6
9
9
3
1
7
0
2
7
33.
30.
9.
59.
78.
20.
26.
40.
81.
.1
1
9
.4 . '
.8
,7
.1
.4
6
35,
32.
11.
67.
92,
24,
31.
46,
108,
.8
.7
.0
.8
.4
.5
.0
.8
,8
                                                                                        450.8
                                          TABLE B-133

                 ENERGY CONVERSION EFFICIENCY AT ELECTRIC UTILITY POWERPLANTS*
                                           (percent)
REGION
                             1985
                                         2000
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
* Includes transmission and distribution losses
                                                     2025
                                                                 2050
                                                                             2075
                                                                                         2100
31.2
32.5
32.4
31.4
26.5
26.3
22.2
30.2
26.1
33.4
33.3
32.9
33.0
29.2
25.0
29.2
3-3.8
29.5
35.6
34.3
35.5
35.3
34.0
35.4
34.5
34.2
34.3
35.8
34.8
37.1
36.3
35.4
35.7
34.7
34.6
35.4
36.6
34.9
37.4
36.5
36.2
36.2
36.0
35.1
36.4
36.0
34.6
36.4
36.3
36.3
35.9
35.8
35.0
36.0
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-134

                              SYNTHETIC PRODUCTION OF OIL AND GAS
                                         (Exajoules/Yr)
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  ==:=
  .0
                                       OIL FROM SYNFUELS

                                         2000        2025.
                                                                 2050
                                                                             2075
                                                                                         2100
0
0
0
0
0
0
0
0
0
1
1

3
'I

4
6
2
.8
.3
.6
.3
.6
.0
.3
,4
.8
4.
3.
1,
- .7.
3.

10,
15";
6,
,2
.0
,5
,8
.8 .
.1
.2
.3
.7
7.
5,
2,
13,
'6,

17.
25.
11
,1
.0
.'5
.2
.5 '
.2
.1
.6
.2
8,
6.
3.
16.
8,

20
• - 30
13
.9
.1
.1
.5
.7
.2
.6
.8
.6
                                           .0
                                                     22,1
                                                                 52.6
                                                                             88.4
                                                                                        108.5
REGION
                             1985
                                       GAS FROM SYNFUELS
                                         2000
                                                     2025
                                                                 2050
TOTAL
                                           .0
                                                     79.6
                                                                109.3
                                                                             2075
                                                                            117.3
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
6.3
4.5
2.3
11.8
5.6
.2
15.5
• 23.2
10.2
8.7
6.2
3.1
16.2
7.7
.2
21.3
31.9
14.0
9.3
6.7
3.4
17.4
8.2
.3
22.8
34.2
15.0
7.9
5.6
2.8
14.8
7.0
.2
19.3
29.0
12.7
                                                                                         99.3
                                                B-96

-------
                                                     Appendix B:  Implementation of the Scenarios
-RCWP
                                          TABLE B-135

                       ENERGY USED FOR SYNTHETIC FUEL PRODUCTION  BY  TYPE
                                         (Exajoules/Yr)
 REGION
                             1985
                                              COAL
                                         2000
                                                     2025
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL

REGION
United .States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0

1985
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
BIOMASS
2000
.0
.0
.0
.0
.0
.0
.0
.0
.0











20
10
7
3
20
9

26
39
17
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0

25
.8
.7
.9
.1
.5
.3
.3
.4
.3
                                                                 2050

                                                                   .0
                                                                   .0
                                                                   .0
                                                                   .0
                                                                   .1
                                                                   .0
                                                                   .0
                                                                   .0
                                                                   .0

                                                                   .1
                                                                 2050
                                                                            2075
                                     .1
                                     .0
                                     .0
                                     .2
                                     .5
                                     .0
                                     .0
                                     .0
                                     .0
                                                                            2075
2100

  .7
  ,2
  .1
 1.2
 2.0
  .0
  .4
  .0
  .0

 4. 6
                                                                                        2100
 TOTAL
                                .0
                                                    135.3
                                                                215.4
                                                                           272.6
                                                                                       272.6
                                              TOTAL
 REGION                       1985

 United States                   .0
 OECD Europe/Canada              .0
 OECD Pacific                    .0
 Centrally Planned Europe        .0
 Centrally Planned Asia          .0
 Middle East                    .0
 Africa                         .0
 Latin America                   .0
 South and East Asia             .0

 TOTAL                          .0
2000

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
                                                     2025
                                                                 2050
                                                                            2075
                                                                                        2100
10.
7
3.
20.
9

26.
39.
17.
.8
.7
.9
.1
.5
.3
,3
.4
.3
17.
12.
6,
32.
15.

41,
62,
27.
.1
.2
.2
,0
,2
,5
,9
,8
.6
21.
15,
7.
40.
19,

53,
79.
34.
,8
,5
.8
.7
.6
,6
,0
,5
.9
22.
15,
7.
41.
21.

53.
79,
34.
.4
,7
,9
.7
,1
.6
,4
,5
9
                                                    135.3
                                                                215.5
                                                                           273.4
                                                                                       277.2
                                                B-97

-------
1'olicy Options for Stabilizing Global Climate
RCWP
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                                          TABLE B-136

                                 C02 EMISSIONS FROM FOSSIL  FUEL
                                       (Petagrams  C/Yr)
                             1985
TOTAL
                              5.1
                                         2000
                                          5.9
                                                     2025
                                                                 2050
                                                                             2075
                                                      5.7
                                                                  5.3
                                                                              5.0
                                                                                         2100
1.3
.9
.3
1.3
.6
.1
.1
.2
.3
1.2
.9
.3
1.5
.9
.2
.2
.3
.5
.8
.7
.2
1.1
1.5
.3
.1
.2
.7
.6
.5
.2
.9
1.8
.4
.0
.0
1.0
.4
,4
.1
.8
1.8
.it
-.0
-.2
1.2
.4
.4
.1
	 .8-
1.9
.4
-.0
-.2
1.4
                                                                                          5.2
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-137

                                  CO EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams C/Yr)
                            1985
                            185.8
                                        2000
                                        133.A
                                                    2025
                                                                2050
                                                    109.6
                                                                 58.A
                                                                            2075
                                                                                        2100
51,
44
14
31,
6
2
8
16
11
.0
.7
.1
.1
.0
.9
.5
.3
.2
22,
29,
9.
29,
6,
2,
8.,
14'
9,
,7
,6
.8
,1
.9
.6
.6
;'5
.7 ;
11,
10,
3.
23,
11,
4,
13
19,
11,
.6
.3
.6
.6
.7
.3
.7
.1
.8
7.
6.
2.
9.
8.
2.
5.
8.
7.
.6
,8
,6
,2
,8
.1
,8
,1
,3
6.
5,
2,
9,
10,
: 2,
6
8,
9
.4
.8
.4
.7
.9
.6
.0
.3
.7
6.
6,
2,
11
13
3.
6
9
13
.6
.1
.6
.6
.5
.4
.4
.2
.2
                                                                                         72.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                           TABLE B-138

                                  NOx EMISSIONS FROM FOSSIL FUEL
                                        (Teragrams N/Yr)
                             1985
                             24.2
                                         2000
                                         25.8
                                                     2025
                                                                 2050
                                                                             2075
                                                     30.6
                                                                 22.7
                                                                             22.7
                                                                                         2100
:==
6,
4,
1,
5,
2,


1,
1
,1
.6
.7
.8
.6
.4
.8
.0
.3
4.
3.
1.
6.
4.

1.
1.
2.
9
8
5
4
2
5
2
3
0
3
2

6
7
1
2
3
3
.1
.4
.9
.3
.2
.1
.6
.2
.8
2.
1.

3,
4.
1.
2.
3.
3.
0
8
7
4
5
0
3
3
5
1
1

3
4

2
3
3
.8
.7
.7
.8
.4
.9
.3
.3
.9
==s;s=
1.
1.

4,
4.

2,
3.
5,
.7
.6
,7
,6
.7
,9
.2
,2
,1
                                                                                         24.7
                                               B-98

-------
                                                     Appendix B:  Implementation of the Scenarios
.RCHR
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                          TABLE B-139

                                   PRIMARY ENERGY SUPPLY
                                       (Exajoules/Yr)
                             1985
                            301.6
                                         2000
                                        334.3
                                                     2025
                                                                 2050
                                                                            2075
                                                    519.6
                                                                            744.2
                                                                                        2100
63.
47,
8,
81.
25,
23,
16.
20,
14.
.7
.6
.9
,2
,6
,7
.3
,5
,1
49.
44.
10,
80,
38.
49.
21,
22.
18,
.1
.8
.4
,8
.1
.2
,0
,7
,2
48
44
14,
91
60,
33,
68,
102,
55,
.4
.2
.3
.5
,2
.9
.6
.9
.6
52.
45,
17,
105.
78,
24,
92.
142,
85,
,8
.3
.6
.8
.0
.5
.2
.5
.7
54.
47.
19.
118,
108.
23.
107.
159.
105.
5
8
2
,1
5
,4
,4
,5
.8
55,
50
20
120,
121,
23,
117,
168.
121
,8
.0
.5
.6
.6
.2
.5
.0
.7
                                                                                       798.9
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                              1985
                             117.9
                                         TABLE B-140

                                     PRIMARY OIL SUPPLY
                                       (Exajoules/Yr)
                                          2000
                                                      2025
                                                                  2050
                                                                             2075
                                         121.4
                                                      62.7
                                                                  18.0
                                                                              18.9
                                                                                         2100
20
11
1
26
5
22
10
14
5
.8
.9
.1
.0
.2
.4
.8
.1
.6
11.
8.

20.
6.
45.
14.
10 .
4.
.5
,6
,6
.4
.2
,8
,0
Pl
.2 ;
4,
4.

10,
4.
23,
9.
5.
2,
.2
.0
.2
.1
.4
.4
.2
.2
.0
1,
1,

2
3
6
2
1,

.1
.0
.0
.6
.0
.1
.4
.3
.5
1,
1,

4,
2.
1,
4,
1,
1.
.2
.6
.0
.6
.6
.6
.9
.3
.1
1
2

5
2

8
2,
1,
.1
.0
.0
.3
.5
.4
.4
.3
.6
                                                                                         23.6
REGION                        1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                         58.6
                                         TABLE B-141

                                      PRIMARY GAS SUPPLY
                                        (Exajoules/Yr)
                                          2000
                                                      2025
                                                                  2050
                                                                             2075
                                          70.6
                                                      44.0
                                                                  28.1
                                                                             28.6
                                                                                         2100
16,
9.

24.

1.
1,
2.
2.
.3
.7
,7
.0
.5
.2
.3
.5
.4
15.
11.
1.
27.
1.
3.
2.
4.
3.
,1
.1
.6
,7
,9
,2
.5
.4
,1
5.
4.

17.
2.
7.
1,
2.
1,
,9
.5
.8
.7
,1
.7
.3
.2
.8
1,


13,
1,
9,



.2
.9
.2
.7
.7
.2
.3
.5
.4



15
2
10



.2
.2
.0
.2
.6
.1
.0
.0
.3



9,
1.
10.



,3
.3
,0
,9
,8
,2
,0
,0
6
                                                                                         23.1
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-142

                                     PRIMARY COAL SUPPLY
                                       (Exajoules/Yr)
1985
19,
9
3
26,
18,

4,

4
.4
.4
.9
.7
.9
.0
.0
.6
.4
2000
12.
8,
4.
24.
26.

3,

7
.9
,4
.1
,9
.9
,0
,8
.9
.3
2025
5
3
2
11
19

2

5
.9
.9
.1
.7
.6
.0
.6
.6
.4
2050
2
1

5
8

1

2
.6
.7
.9
.2
.7
.0
.2
.3
.4
2075
1,


2,
23.



2,
.2
.8
.7
,3
.3
.0
.5
.1
.5
S 	
2100

1.

3.
29.



5.
6
0
9
6
5
0
6
0
6
                              87.3
                                          89.2
                                                      51.8
                                                                  23.0
                                                                             31.'4
                                                                                         41.8
                                               B-99

-------
Policy Options  for Stabilizing Global Climate
RCWR
                                         TABLE B-143

                                   PRIMARY BIOMASS SUPPLY
                                       (Exajoules/Yr)
REGION                        1985

United States                   .0
OECD Europe/Canada              .0
OECD Pacific                    .0
Centrally Planned Europe        .0
Centrally Planned Asia          .0
Middle East                     .0
Africa                          .0
Latin America                   .0
South and East Asia             .0

TOTAL                           .0
                                          2000
                                            .0
                                                      2025
                                                                  2050
                                                                              2075
                                                     265.8
                                                                 396.1
                                                                                          2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
21
15
7
39
18

51
77
34
.2
.1
.6
.5
.6
.6
.7
.5
.0
31.
22.
11.
58.
27.

77.
115.
50.
.5
.5
.3
.9
.8
.9
,0
.5
.7
35
25
12
66
31
1
86
129
56
.4
.3
.7
.0
.1
.0
.4
.6
.9
37
26
13
69
32
1
90
136
59
.2
.6
.4
.4
.7
.0
.8
.2
.8
                                                                                         467.1
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
                                         TABLE B-144

                                PRIMARY HYDROELECTRIC SUPPLY
                                        (Exajoules/Yr)
                              1985
TOTAL
                              21.2
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                          31.5
                                                      53.4
                                                                  66.9
                                                                              71.8
                                                                                          2100
3
8
1
2,
1


3
1
.3
.2
.2
.5
.0
.1
.2
.3
.4
3.
9.
1.
3.
2.


7'.
2.
9
7
3
2
6
2
5
3
8
4
10
1
3
7

1
16
6
.4
.8
.3
.7
.6
.5
7
.5
.9
4
11.
1.
3.
10.

4
20
10
.7
.0
.4
.7
.8
.6
,2
.0
.5
4.
11.
1,
3,
11,

6.
20.
11.
.7
.1
.4
.7
.5
.7
7,
.6
.9
4.
11.
1.
3.
11.

7.
20.
12.
.8
.1
.5
.7
,6
.7
n
.7
.4
                                                                                          73.5
REGION                        1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                         16.5
                                         TABLE B-145

                                    PRIMARY NUCLEAR SUPPLY
                                        (Exajoules/Yr)
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                          19.0
                                                      25.8
                                                                  58.2
                                                                              81.0
                                                                                          2100
3,
8,
2.
2,





.8
,4
.0
.0
.0 •
.0
.0
.0
.3
5,
6.
2.
3.





.0
.7
.6
.8
.2
,0
,1
,0
.6
4
4
1
5
4

1

3
.2
.6
.6
.2
.6
.9
.1
.5
.1
5.
5.
2.
10.
13.
3.
3.
2.
10.
9
.5
1
9
1
.9
.6
.5
,7
6
6
2
14
19
5
5
4
17
.3
.1
.6
.0
.9
.3
.0
.2
.6
6,
6.
2.
16,
24.
6,
6.
4,
23,
,6
5
,9
.1
.4
.1
.0
.9
4
                                                                                          96.9
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
1985

  .1
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .1
                                         TABLE B-146

                                     PRIMARY SOLAR SUPPLY
                                       (Exajoules/Yr)
                                          2000
                                           2.6
                                                      2025
                                                                  2050
                                                                              2075
                                                      16.1
                                                                  54.1
                                                                              68.1
                                                                                          2100
.7
.3
.2
.8
.3
.0
.1
.0
.2
2,
1.

3,
3.

1,

2,
.6
.3
.7
,6
.3
.8
.0
.4
.4
. 5.
2.
1.
10.
12.
3.
3,
2.
10,
,8
,7
.7
.8
,9
.8
.5
.4
.5
5.
2.
1.
12.
17.
4,
4.
3,
15,
.5
.7
',&
,3
.5
.7
.4
.7
.5
5
2
1
12
19
4
4
3
18
.2
.5
.8
.6
.1
.8
.7
.9
.3
                                                            72.9
                                               B-100

-------
                                                     Appendix B: Implementation of the Scenarios
RCHR
REGION
                                         TABLE  B-147

                                  PRIMARY ENERGY CONSUMPTION
                                       (Exajoules/Yr)
                              1985
                                          2000
                                                     2025
                                                                 2050
TOTAL
                             300..2
                                         334.3
                                                    520.1
                                                                643.3
                                                                             2075
                                                                            742.6
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
74.
67.
19
71
23.
5.
7.
15.
15.
.9
.0
.3
.1
.8
.8
.6
.6
.1
68
60
19
80
37
9
11
23
24
.2
.8
.4
.0
.1
.0
.7
.7
.4
66
58
19
88
85
24
36
72
68
.6
.4
.3
.6
.7
.4
.9
.1
.1
62
55
19
101
112.
34
52
93.
110
.8
.4
.8
.5
.9
.5
.8
.4
.2
61.
55.
21.
113.
132.
40,
64.
109.
144.
.7
.5
.0
.7
.6
.1
.3
.2
.5
62.5
56.5
22.4
121.4
141.3
41.7
70.2
114.7
168.7
                                                                                        799.4
                                          TABLE B-148

                     SECONDARY ENERGY  CONSUMPTION: FUEL VERSUS ELECTRICITY
                                        (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                             194.4
                                       FUEL  CONSUMPTION
                                          2000
                                                     2025
                                                                 2050
                                         207.9
                                                    267.2
                                                                292.5
                                                                             2075
                                                                            326.6
                                                                                         2100
48,
42.
11
44
17
3,
4
11
10
.2
.4
.9
.6
.0
.9
.7
,3
.4
40.
38.
11.
47.
24.
5.
7.
16.
15.
.9
.2
.7
,6
.6
.8-
.1 .
,4
.6
35.
31.
10,
44,
46,
14,
15,
34,
33,
.4
.8
.3
.4
.8
.8
.1
.8
.8
30
26
9
47
49
20
19
39
50
.0
.8
.4
.0
.8
.2
.2
.3
.8
29
26
9
51
52
23
23
45
65
.4
.1
.9
.7
.3
.1
.0
.9
.2
30,
26
10,
.55,
52.
23.
24.
47.
75.
.0
.7
.6
,5
.3
.7
.5
.5
.3
                                                                                        346.1
REGION
                                    ELECTRICITY CONSUMPTION
                              1985
                                          2000
                                                     2025
                                                                 2050
                                                                             2075
TOTAL
                              32.9
                                          41.1
                                                      68.2
                                                                 94.2
                                                                            114.9
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
8
8
2
8
1


1
1
.4
.0
.4
.4
.8
.5
.8
.3
.3
9
7
2
10
3
1
1
2
2
.1
.5
.5
.8
.7
.0
.4
.4
.7
9.
8.
2
12,
12,
3,
3
' 6
9
.6
.1.
.5
.8
.1
.5
.5
.8
.3
9.
8.
2.
15.
20.
5.
5.
9,
17.
.2
.2
,8
.3
.5
.1
.9
.8 .
.4
8
8
3
17
27
6
7
11
24
.9
.2
.0
.5
.0
.2
.8
.7
.6
8.7
8.2
3.1
18.4
30.0
6.6
8.7
12.2
29.1
                                                                                        125. 0
REGION
                              1985
                                    TOTAL ENERGY  CONSUMPTION
                                          2000
                                                      2025
                                                                 2050
                                                                             2075
TOTAL
                             227.3
                                         249.0
                                                    •335.4
                                                                 386.7
                                                                            441.5
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
56
50
14
53
18
4
5
12
11
.6
.4
.3
.0
.8
.4
.5
.6
.7
50
45
14
58
28
6
8
18
18
.0
.7
.2
.4
.3
.8
.5
.8
.3
45.
39.
12.
57,
58,
18.
18,
41,
43,
,0
.9
.8
.2
.9
.3
.6
.6
.1
39
35
12
62
70
25
25
49
68
.2
.0
.2
.3
.3
.3
.1
.1
.2
38.
34.
12,
69,
79,
29,
30,
57,
89,
.3
.3
.9
.2
.3
.3
.8
.6
.8
38.7
34.9
13.7
73.9
82.3
30.3
33.2
59.7
104.4
                                                                                        471.1
                                              B-101

-------
Policy Options for Stabilizing Global'Climate
RCWR
                                          TABLE B-149

                                   SECONDARY OIL CONSUMPTION
                                        (Exajoules/Yr)
REGION
                              1985
                                          2000
                                                      2025
                                                                  2050
TOTAL
                             100.6
                                         106.9
                                                     122.8
                                                                 134.1
                                                                             158,2
                                                                                          2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South- and East Asia
28
25
8
14
2
3
3
8
6
.8
.8
.0
.6
,2
.4
.1
.6
.1
24
23
7
17
3
5
4
12
9
.2
.3
.7
.4
.4
.2
.4
.3
.0
16
17
6
14
a
11
8
21
18
.8
.1
.4
.8
.3
.4
.5
.4
.1
12
13.
5.
14
11.
14
10
23
27
.7
.5
.8
.7
.5
,9
.6
.2
.2
12.
13
6.
17.
15
17.
12
26
36
.8
.4
.2
.8
.6
.0
.9
.4
.1
13.
14.
6.
21.
20,
17.
14.
27.
43.
7
2
8
7
6
5
2
8
7
                                                                                         180.2
                                         TABLE B-150

                                  SECONDARY GAS CONSUMPTION
                                       (Exajoules/Yr)

REGION                        1985        2000        2025        2050        2075        2100

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Afric-a
Latin America
South and East Asia

TOTAL                         48.8        47.8        87.7       103.8       117.3       121.5
15.
10.
1.
17.



2,
1.
,6
,3
,3
,1
.3
.5
.4
.1
2
13,
9.
1,
17,



s'
1.
.0
.1
.3
.5
.4
.6
,8
.''2
.9'
17.
12.
2.
24.
2,
3.
3,
12,
9.
,1
,1
.1
.6
,7
.4
,8
.4
.5
16,
11,
2,
28,
4
5,
5,
15,
16.
,2
.2
,2
.2
.0
.3
.2
.1
.4
15.
10.
2,
30,
4,
6,
6,
18,
21,
.7
.9
,4
.2
.9
.1
.6
.6
.9
15.
10.
2.
30.
5.
6.
7,
19,
25,
.4
.7
5
.3
.3
.2
.1
,0
.0
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-151

                                 SECONDARY SOLIDS CONSUMPTION
                                        (Exajoules/Yr)
                              1985
                              45.0
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                          53.2
                                                      56.7
                                                                  54.6
                                                                              51.1
                                                                                          2100
3.
6,
2,
12,
14,

1.

3,
,8
.3
.6
.9
.5
.0
.2
.6
.1
3,
5.
2.
12.
20.

1,

4,
,7
.8
.7
.7
.8
,0
.9
.9
.7
1.
2,
1.
5.
35.

2,
1.
6,
,5
.6
,8
,0
.8
.0
,8
.0
,2
1.
2,
1,
4,
34

3.
1
7,
.1
.1
.4
.1
.3
.0
,4
.0
,2

1.
1.
' 3,
31,

3,

7,
.9
.8
.3
.7
.8
.0
.5
.9
.2

1,
1,
3,
26,

3.

6.
.9
.8
.3
.5
.4
.0
,2
.7
,6
                                                                                          44.4
                                               B-102

-------
                                                    Appendix B:  Implementation of the Scenarios
RCWR
                                        TABLE B-152

               RESIDENTIAL/COMMERCIAL ENERGY CONSUMPTION: FUEL VERSUS ELECTRICITY
                                      (Exajoules/Yr)
REGION
United States
OECD 'Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                              1985
                              47.9
                                      FUEL CONSUMPTION
                                         2000
                                         42.1
                                                     2025
                                                                 2050
                                                                             2075
                                                                             48.0
                                                                                         2100
11
12
1
13
4


1
2
.5
.9
.6
.2
.3
.2
.4
.6
.2
7.
11.
1.
11.
4.


2.
2.
0
1
.6
.5
.8
.4
.8
.0
,9
6
7
1
12
5
1
1
3
4
.7
.8
.1
.8
.9
.0
.7
.3
.4
5.
6.

12
7
1
2
4
6
.6
.1
.9
.3
.1
.5
.3
.5
.5
4.
5.

11.
8.
1.
2.
5.
7,
8
.1
8
.8
,0
.8
.7
.1
.9
4.
4.

10.
8,
1,
2
5
8
.1
.5
.8
.6
.1
,8
.6
.2
.3
                                                                                         46.0
REGION
                              1985
                                    ELECTRICITY CONSUMPTION

                                         2000        2025
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
5
4
1
1





.2
.5
.1
.3
.2
.1
.3
.5
.5
5
3
1
2





.3
.6
.0
.0
.4
.2
.5
.8
.>9
5.
4,
1.
4.
1,

1.
1.
2.
.4
.3
.1
.4
.1
.7
.0
.5
.5
TOTAL
                              13.7
                                         14.7
                                                     22.0
                                                                 2050
                                                                  4.6
                                                                 25.6
                                                                             2075
                                                                              6.6
                                                                             29.4
                                                                                         2100
4.8
3.8
1.1
4.5
1.9
1.0
1.6
2.3
4.4
3.4
1.1
4.6
2.8
1.4
2.1
3.0
3.9
3.1
1.0
4.3
3.4
1.6
2.3
3.3
                                                                                          7.7
                                                                                         30.6
REGION
                              1985
                                    TOTAL ENERGY CONSUMPTION

                                         2000        2025
                                                                 2050
                                                                             2075
TOTAL
                              61.6
                                          56.8
                                                     66.7
                                                                 72.4
                                                                             77.4
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
16.
17.
2.
14.
4.


2.
2.
.7
.4
.7
.5
,5
,3
.7
.1
.7
12.
14.
2.
13.
5,

1.
2,
3,
,3
.7
,6
.5
.2
.6
.3
.8
.8
==5S
12.
12.
2.
17.
7,
1.
2,
4,
6.
.1
.1
.2
.2
,0
,7
,7
.8
.9
zxsss
10.
9.
2.
16.
9.
2.
3,
6.
11.
.4
.9
0
8
.0
5
.9
.8
,1
9.
8.
1.
16.
10,
3.
4,
8.
14.
.2
.5
.9
.4
.8
.2
.8
.1
.5
8.0
7.6
1.8
14.9
11.5
3.4
4.9
8.5
16.0
                                                                                         76.6
                                              B-103

-------
Policy Options for Stabilizing Global Climate
RCWR
                                          TABLE  B-153

                     INDUSTRIAL ENERGY CONSUMPTION:  FUEL  VERSUS ELECTRICITY
                                        (Exajoules/Yr)
                                       FUEL  CONSUMPTION
REGION
                              1985
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
TOTAL
                              86.1
                                         103.5
                                                     165.2
                                                                 190.2
                                                                             205.6
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
15.
13.
5.
23.
11.
3.
2.
5.
5.
6
9
4
7
5
0
1
5
4
16
14
5
26
13
4
3
9
9
.9
.3
.9
.4
.1
.5
.4
.4
.6
16
13
5
22
37
12
3
23
25
.9
.7
.7
.2
.6
.1
.0
.9
.1
15
13
5
25
37
16
11
26
38
.7
.1
.6
.3
.9
.6
.3
.7
.0
15
13
5
27
35
17
13
30
46
.5
.0
.3
.4
.9
.9
.2
.4
.5
15.7
13.2
5.9
23.2
30.6
16.9
13.5
29.4
49.6
                                                                                         203.0
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    ELECTRICITY CONSUMPTION

                              1935        2000         2025
                              19.2
                                          26.4
                                                                  2050
                                                      45.9
                                                                  63.2
                                                                              2075
                                                                              84.9
                                                                                          2100
3
3
1
7
1




.2
.5
.3
.1
.6
.4
.5
.3
.8
3.
3.
1.
8.
3.


1.
i:
8
9
5
8
,3
8
,9
.6
"8
4.
3.
1,
8,
10,
2,
2
5
6
.2
.3
.4
.4
.3
.8
.5
.3
.7
4
4
1
10
18
4
4
7
12
.4
.4
.7
.8
.4
.1
.3
.5
.6
4.
4.
1.
12.
23.
4,
5.
3,
17,
5
,8
,9
,9
,9
,8
,7
,7
.7
4.
5.
2.
14,
26,
5
6,
8.
21,
,8
.1
.1
.1
.0
.0
.4
,9
.0
                                                                                          93.4
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                    TOTAL ENERGY CONSUMPTION

                              1935        2000        2025
                             105.3
                                         134.9
                                                                  2050
                                                                              2075
                                                     211.1
                                                                 253.4
                                                                             290.5
                                                                                          2100
18
17
6
30
13
3
2
6
6
.8
.4
.7
.8
.1
.4
.6
.3
.2
20.
13.
7.
35
21
5
4
11
11
.7
.2
.4
.2
.4
.3
.3
.0
.4
21.
17.
7,
30.
48.
14,
10,
29,
31,
.1
,5
.1
.6
.4
.9
.5
.2
.3
20.
17.
7.
36.
56.
20.
15.
34.
50.
1
5
3
1
3
7
6
2
6
20
17
7
40
59
22
18
39
64
.0
.8
.7
.3
.8
.7
.9
.1
.2
20,
13,
8,
42,
56
21
19
38
70
.5
.3
.0
.3
.6
.9
.9
.3
.6
                                                                                        '296.4
                                               B-104

-------
                                                     Appendix B:  Implementation of the Scenarios
RCWR
                                         TABLE B-154

                    TRANSPORTATION ENERGY CONSUMPTION:  FUEL  VERSUS  ELECTRICITY
                                        (Exajoules/Yr)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                              60.4
                                       FUEL CONSUMPTION
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                          57.3
                                                      57.3
                                                                  55.5
                                                                              73.0
                                                                                         2100
21
15.
4.
7
1

2
4.
2
.1
.6
.9
.7
.2
.7
.2
.2
.8
17
12.
4,
9
1

2
5
3
.0
.8
.2
.7
.7
.9
.9
.0
.1
11
10
3
9
3
1
5
7
4
.8
.3
.5
.4
.3
.7
.4
.6
.3
8
7
2
9
4
2
5
8
6
.7
.6
.9
.4
.8
.1
.6
.1
.3
9.
8.
3.
12.
8,
3.
7
10
10
.1
.0
.3
.5
.4
.4
.1
.4
.8
10.
9.
3.
16.
13,
5.
8.
12
17,
2
0
9
,7
,6
,0
.4
.9
.4
                                                                                          97.1
                                    ELECTRICITY CONSUMPTION
REGION   '                     1985

United States                   .0
OECD Europe/Canada              .0
OECD Pacific                    .0
Centrally Planned Europe        .0
Centrally Planned Asia          .0
Middle East                     .0
Africa                          .0
Latin America                   .0
South and East Asia             .0
2000

  .0
  .0
  .0
  .0
  .0
  .0-,
  .0
  .0
  .0
2025

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .1
2050

  .0
  .0
  .0
  .0
  .2
  .0
  .0
  .0
  .2
 TOTAL
2075

  .0
  .0
  .0
  .0
  .3
  .0
  .0
  .0
  .3

  .6
2100

  .0
  .0
  .0
  .0
  .6
  .0
  .0
  .0
  .4

 1.0
REGION

.United States
OECD  Europe/Canada
OECD  Pacific
Centrally  Planned Europe
Centrally  Planned Asia
Middle East
Africa
Latin America
South and  East Asia

TOTAL
                                    TOTAL ENERGY CONSUMPTION

                              1985        2000        2025
                              60.4
                                                                  2050
                                                                              2075
                                          5 7.. 3
                                                      57.6
                                                                  55.9
                                                                              73.6
                                                                                          2100
21.
15.
4,
7,
1.

2,
4,
2,
,1
,6
,9
.7
,2
.7
.2
.2
.8 •
— — .:
17
12
4
9
1

2
'5
3
.0
.8
.2
.7
.7
.9
.9
.0
.1
11,
10,
3,
9,
3.
1,
5,
7
4.
.8
.3
.5
.4
.5
.7
.4
.6
.4
8
7
2
9
5
2
5
8
6
.7
.6
.9
.4
.0
.1
.6
.1
.5
9,
8
3,
12,
8,
3,
7
10,
11,
.1
.0
.3
.5
.7
.4
.1
.4
.1
10
9
3.
16,
14.
5.
8,
12.
17.
.2
.0
,9
.7
.2
,0
.4
.9
.8
                                                                                          98.1
                                               B-105

-------
Policy Options  for Stabilizing Global Climate
RCHR
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                         TABLE B-155

                              ELECTRIC UTILITY ENERGY CONSUMPTION
                                        (Exajoules/Yr)
                              1985
                             105.3
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                         126.0
                                                     193.0
                                                                 264.6
                                                                             314.9
                                                                                          2100
26.
24.
7.
26.
6.
1.
2.
4.
4.
6
6
.4
.4
.8
9
7
,3
,6
27
22
7
32
12
3
4
7
8
.3
.5
.6
.6
.5
.0
.5
.3
.7
26
23
7
35
• 34
9
10
19
26
.4
.2
.1
.3
.6
.6
.3
.9
.6
25.
23.
8.
41.
57.
14.
16.
29.
48.
8
7
0
6
2
1
9
0
3
24
23
8
46
73
16
21
33
66
.2
.7
.3
.9
.1
.8
.8
.7
.4
23.
23.
8.
49.
81.
17.
24,
34,
79,
,6
,6
,7
,5
,3
.7
. 1'
.8
.2.
                                                                                         342.5
                                         TABLE B-156

               ELECTRICITY CONVERSION EFFICIENCY AT ELECTRIC UTILITY POWERPLANTS*
                                          (percent)
REGION
                              1985
                                          2000
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
* Includes transmission and distribution losses
                                                      2025
                                                                  2050
                                                                              2075
                                                                                          2100
31,
32,
32,
31,
26,
26,
22,
30
26,
.2
.5
.4
.4
.5 ,
.3
.2
.2
.1
33
32
31
33
29
26
28
32
29
.3
.9
.6
.7
.6
.7
.9
.9
;9
36,
34.
33
36
34
37
35
33
35
.4
.9
.8
.0
.7
.5
.0
.7
.0
35,
34,
36
36,
36,
36.
36,
34,
36,
.7
.6
.3
.8
.0
.2
.1
.5
.0
36,
35,
37,
37,
36,
37,
37,
35,
37,
.8
.0
.3
.5
.8
.5
.2
.0
.0
36.
35,
36,
37.
37.
36,
36.
34.
36.
.9
.2
.8
.4
.0
,7
,5
,8
.7
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-157

                              SYNTHETIC PRODUCTION OF OIL AND GAS
                                        (Exajoules/Yr)
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  ===
  .0
                                       OIL FROM SYNFUELS

                                          2000        2025.
                                                                  2050
                                                                              2075
                                                                                         :2100
0
0
.0
.0
,0
,0
,0
,0
,0
5.9
4.2
2.1
11.1
' 5.2
.2
14.5
21.7
9.5
10.3
7.4
3.7
19.2
9.1 .
.3
25.2
37.8
16.6
12.3
8.8
4.4
23.0 -
10.9
.3
30.1
45.2
19.9
13.7
•9.8
4.9
25v5
12.1
-.4
33.4
50.2
22.0
                                            .0
                                                      74.4
                                                                 129.6
                                                                             154.9
                                                                                         172.0
REGION                        1985

United States                   .0
OECD Europe/Canada              .0
OECD Pacific                    .0
Centrally Planned Europe        . 0
Centrally Planned Asia          .0
Middle East                     .0
Africa                          . 0
Latin America                   .0
South and East Asia             .0

TOTAL
                                       GAS FROM SYNFUELS
                                          2000
                                            .0
                                                      2025
                                                     105.5
                                                                  2050
                                                                 133.7
                                                                              2075
                                                                             152.9
                                                                                          2100
.0
.0
.0
.0
.0
.0
.0
.0
.0
8.
6.
3.
15.
7.

20.
• 30.
13.
4
0
0
7
4
2
5
8
5
10
7
3
19
9

26
39
17
.6
.6
.8
.9
.4
.3
.0
.0
.1
12
8
4
22
10

29
44
19
sstss
.2
.7
.4
.7
.7
.3
.7
.6
.6
=:===i
13.
9.
4.
24.
11.

32.
48.
21.
1
4
7
5
5
4
0
1
1
                                                           164.8
                                               B-L06

-------
                                                      Appendix B: Implementation of the Scenarios
 RCWR
                                         TABLE B-158

                        ENERGY  USED FOR SYNTHETIC FUEL PRODUCTION BY TYPE
                                         (Exajoules/Xr)

                                             COAL

 REGION                        1985        2000        2025        2050        2075        2100
 United States                    .0           .0           .0           .0           .0          .0
 OECD Europe/Canada              .0           .0           .0           .0           .0          .0
 OECD Pacific                     .0           .0           .0           .0           .0          .0
 Centrally Planned  Europe         .0           .0           .0           .0           .0          .0
 Centrally Planned  Asia           .0           .0           .0           .0           .0          .0
 Middle East                     .0           .0           .0           .0           .0          .0
.Africa                          .0           .0           .0           .0           .0          .0
 Latin America                    .0           .0           .0           .0           .0          .0
 South and East  Asia             .0           .0           .0           .0           .0          .0
 TOTAL
                                                                     .0
 REGION
 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia
 TOTAL
 REGION

 United States
 OECD Europe/Canada
 OECD Pacific
 Centrally Planned Europe
 Centrally Planned Asia
 Middle East
 Africa
 Latin America
 South and East Asia

 TOTAL
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
1985

  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0
  .0

  .0
BIOMASS
2000
.0
.0
.0
.0
.0
.0
.0
.0
.0 »•
.0
TOTAL
2000
,0
.0
.0
.0
.0
.0
.0
.0
.0

2025
19.1
13.6
6.9
35.6
16.8
.5
46.6
69.8
30.7
239.6

2025
19.1
13.6
6.9
35.6
16.8
.5
46.6
69.8
30.7
                                                                  2050
                                                                              2075
                                                                 350.1
                                                                  2050
 27.9
 19.9
 10.0
 52.0
 24.5
 68,
102.
                                             .0
                                                     239.6
 44.8
                                                                 350.1
                                                                             409.6
 2075

 32.6
 23.3
 11.7
 60.9
 28.7
   .9
 79.6
119.5
 52.4

409.6
                                                                                          2100
19
13
6
35
16

46
69
30
.1
.6
.9
.6
.8
.5
.6
.8
.7
27.
19.
10.
52.
24.

68.
102.
44.
,9
.9
.0
.0
,5
.8
.1
,1
.8
32.
23.
11.
60.
28.

79.
119.
52.
,6
.3
.7
.9
.7
,9
,6
,5
.4
35
25
12
66
31
1
87
130
57
.7
.5
.8
.5
.4
.0
.1
.6
.3
                                                                                         447.9
                                                                                          2100
                                                                                         447.9
                                               B-107

-------
Policy Options for Stabilizing Global Climate
RCWR
                                         TABLE B-159

                                C02 EMISSIONS FROM FOSSIL FUEL
                                       (Petagrams  C/Yr)
REGION
                             1985
                                         2000
                                                     2025
                                                                 2050
TOTAL
                               5.1
                                           5.5
                                                       2.9
                                                                   1.0
                                                                             2075
                                                                               1.2
                                                                                        2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
1.3
.9
.3
1.3
.6
.1
.1
.2
.3
1.1
.8
.3
1.4
.8
.1
.2
.3
.A
.6
.5
.2
.6
1.2
.3
-.3
-.5
.A
.2
.2
.0
.2
1.1
.A
-.6
-.9
.A
.1
.2
.0
.2
1.2
.A
-.7
-1.0
.7
.1
.2
.0
.3
1.1
.5
-. 7
-1.0
.9
                                                                                           1.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE E-160

                                 CO EMISSIONS FROM FOSSIL FUEL
                                       (Teragrams C/Yr)
                              1985
                             185.8
                                          2000
                                                      2025
                                                                  2050
                                         132.1
                                                      88.0
                                                                  A5.9
                                                                              2075
                                                                              61.6
                                                                                         2100
51.
AA.
1A.
31.
6.
2.
8.
16.
11.
0
7
1
1
0
,9
.5
.3
.2
22,
29,
9,
28,
6,
2,
8,
1A,
9,
.5
.A
,7
.8
.6
.6
.5
.A
.5
8.
7,
2,
19.
9.
3,
11,
15,
9,
.8
,7
.7
.0
.6
,5
.2
.8
.6
6.
5.
2.
7.
6.
1.
A.
6.
5.
1 '
,3
.1
,2
,5
,8
,7
,7
7
6,
6
2
9
9
2,
6
8,
9
.8
.0
.5
.9
.0
.8
.1
.9
.A
7.
6.
2.
12,
12.
3,
7,
10,
1A,
6
.7
.9
,8
,A
,9
,1
,8
,0
                                                                                          78.3
                                         TABLE B-161

                                  NOx EMISSIONS FROM FOSSIL FUEL
                                       (Teragrams N/Yr)
REGION                        1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                         24.2
                                          2000
                                          24.2
                                                      2025
                                                                  2050
                                                      27.8
                                                                  20.A
                                                                              2075
                                                                              21.3
                                                                                          2100
6
A
1,
5,
2,


1
1,
.1
.6
.7
.8
.6
.A
.8
.0
.3
A.
3.
1,
6.
3.

1.
lc
1,
,6
,6
A
,0
.8
, 5
.1
,3
.8
2.
2.

A.
6.
1.
2.
3.
3.
.7
.1
.9
.1
,7
,1
8
.9
,5
1.
1.

2.
3.
1,
2.
3.
3.
,9
,6
,7
.7
.7
.0
.3
.3
.1
1.
1.

3.
3.
1,
2,
3,
3,
.9
.6
,7
,1
,5
.0
.A
.7
,A .
2.
1,

3
3,
1
2
A
A
.0
.7
.8
.6
.8
.1
.7
.1
.3
                                                                                          2A.O .
                                               B-108

-------
                                                     Appendix B:  Implementation of the Scenarios
SLOW
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                         TABLE B-163

                                     PRODUCTION OF WHEAT
                                    (Million Metric Tons)
                              1985
                             481.1
                                          2000
                                                      2025
                                                                  2050
                                                                             2075
                                         627 .it
                                                     855.3
                                                                1060.2
                                                                            1064.0
                                                                                         2100
72.
108.
16.
142.
40.
12.
11.
17.
59.
6
1
3
6
7
3
0
7
9
97
131
24
164
46
14
15
23
109
.5
.9
.1
.6
.8
.6
.0
.9
.0
128.
187.
37
190
54.
18.
22.
37.
178.
.5
.3
.8
.6
.4
.0
.1
.9
.5
146
219
49
212
60
21
30
85
233
.8
.1
.8
.2
.6
.5
.6
.8
.9
134.
196.
43.
200.
59.
30.
42.
95.
261.
0
6
5
7
2
9
3
6
2
127.
190,
41.
197.
61.
36.
53.
106.
294.
.0
.1
.9
.5
,7
.1
,8
.9
.7
                                                                                       1109.5
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                             277.9
                                         TABLE B-164

                                      PRODUCTION OF RICE
                                     (Million Metric  Tons)
                                          2000
                                         375.7
                                                      2025
                                                                  2050
                                                     538.5
                                                                 671.8
                                                                             2075
                                                                             786.2
                                                                                         2100
3.
2,
10.
4.
100.
1.
7
10.
137.
.9
.0
.1
.0
.8
.4
,3
,7
.7
3
2
10
5
115
2
13
13
208
.8
.7
.5
.7
.5
.0
.3
.9
-:.3
6
3
9
6
123
2
24
19
341
.2
.8
.5
.4
.8
.8
.9
.5
.7
8,
4.
7,
6.
123.
2,
35,
20.
462,
.8
.1
.5
,8
.9
.8
,4
.5
.0
8.
4.
7
6.
129
4
53
24
547
.5
.3
.0
.9
.6
.4
.9
.3
.2
7.
4.
6.
6.
126.
4.
65.
25.
576,
.5
.2
3
.4
.9
.9
.2
.4
.0
                                                                                        822.8
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-165

                                 PRODUCTION OF COARSE GRAINS
                                    (Million Metric Tons)
                              1985
                             809.9
                                          2000
                                                      2025
                                                                  2050
                                        1073.1
                                                    1453.3
                                                                1750.2
                                                                             2075
                                                                            1928.1
                                                                                         2100
233.
139.
10.
162.
82.
6.
56,
69,
50,
.3
,5
,3
,3
.3
.6
.0
.0
.5
277 .
205.
25.
203.
100.
9.
85,
102.
62,
.9
.7
.9
.6
,6
.7
.6
.1
.1
304,
286,
55.
267,
112,
14,
131.
203,
77
,6
.0
.1
.8
.0
.7
.9
.3
.8
319.
233,
81,
311.
119.
17.
161
409
96
.8
.5
.4
.4
.6
.9
.0
.2
.4
310.
234.
75.
315.
124.
26.
240,
485,
114,
,9
,1
,7
.7
,9
,9
.0
.5
.5
286,
229.
71.
304,
127.
30.
299,
528.
125,
.9
.6
.0
.6
.1
.6
.6
.4
.8
                                                                                       2003.6
REGION
                                         TABLE B-166

                                     PRODUCTION OF MEATS
                           (Million Metric Tons of Carcass Weight)
                              1985
TOTAL
                              68.0
                                          2000
                                          87.1
                                                      2025
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
11.
14.
4,
12.
4.

5.
11,
3,
.0
,6
,8
.2
.4
,9
.1
.6
.4
13
16
5
14
5
1
8
16
5
.8
.5
.7
.0
.4
.6
.5
.4
.2
13.
19,
7.
15.
6.
2,
15,
24,
9
.9
.2
.5
.3
.6
.8
.6
.5
.1
                                                     114.5
                                                                  2050
                                                                 130.3
                                                                              2075
                                                                             151.-1
                                                                                         2100
7.0
22.0
9.0
14.7
7.4
4.0
23.4
29.9
12.9
6.8
22.0
8.3
15.0
7.7
6.1
34.8
35.1
15.2
6.0
20.9
7.5
14.2
7.6
6.8
42.0
36.8
16.1
                                                                                         157.9
                                               B-109

-------
Policy Options  for Stabilizing Global Climate
SLOW
                                         TABLE B-167

                                 PRODUCTION OF DAIRY PRODUCTS
                          (Million Metric Tons of Milk Equivalent)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                             508.6
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                         634.1
                                                     851.1
                                                                1067.5
                                                                            1200.0
                                                                                          2100
61.
140,
23,
154
8,
6,
20
38
54
.5
.3
.0
.7
,9
,7
.0
,8
.7
71.
151.
28.
178.
14.
10.
32.
61.
85.
6
,5
2
.9
0
8
.0
8
.1
104,
165.
33.
188
19,
17,
54
101.
166
,5
.9
.1
.2
.8
.3
.5
.6
.1
127
167
31
177
24
22
75
133
307
.5
.0
.7
.9
.0
.3
.7
.9
.6
124.
168.
29.
181.
25.
34,
111.
159.
366,
2
3
5
,5
,1
,8
,4
,2
,2
113.
163.
27.
173.
25.
39,
136.
171.
397,
4
7
4
,8
,3
.2
,5
,3
.9
                                                                                        1248.5
                                         TABLE B-168

                                 PRODUCTION OF OTHER ANIMALS
                          (Million Metric Tons of Protein Equivalent)
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                              19.5
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                          27.3
                                                      42.8
                                                                  64.3
                                                                              72.1
                                                                                          2100
2
3
2
3
4


1,
1
.2
.8
.0
.0
.4
.2
.9
.3
.8
2.
4.
2.
3,
6.

1,
2,
3
.3
.6
.8
.5
.9
.4
.6
.3
.0
2.
5.
4.
3.
13.

2,
4,
5,
,4
,2
,8
,8
,5
,7
,6
,6
,2
2.
4.
9.
3.
26.

3.
7.
7.
1
5
2
4
1
8
2
5
6
2,
4,
8,
3,
28.
1.
5,
9
9,
.1
.7
.8
.6
.1
.3
.0
.2
.2
2
4
8
3
28
1
6
10
10
.0
.6
.3
.5
.'6
.5
.2
.0
.1
                                                                                          74.9
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                         TABLE B-1&9

                                 NITROGENOUS FERTILIZER USE
                                   (Million Metric Tons N)
                              1985
                              63.7
                                          2000
                                         100.4
                                                      2025
                                                                  2050
                                                     141.1
                                                                 166.3
                                                                              2075
                                                                             180.5
                                                                                          2100
10,
11,
1,
13.
12,
1,
2,
2,
8,
,4
.9
,0
.5
.1 .
.0
.1
.9
.7
11.
18.
1.
22,
17.
1.
4.
4,
18,
9
,6
,1
4
.0
,5
,4
.7
,8
12,
24.
1,
25,
20,
2,
9,
8
37.
.8
.2
.8
.4
.1
.4
.1
.0
.2
10,
22
2,
27
21,
3
14.
10
53
.6
.6
.2
.6
.2
.1
.7
.5
.8
9.
21.
1.
27.
21.
3.
18.
13.
62.
,8
,8
7
,3
,7
.9
9
,4
,1
8,
21.
1.
26.
21.
4,
22.
15,
65,
.8
,4
,5
,8
,7
,2
,0
.1
,9
                                                                                         187.3
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-170

                                 LAND UNDER RICE CULTIVATION
                                     (Million Hectares)
                              1985
                             146.7
                                          2000
                                         167.9
                                                      2025
                                                                  2050
                                                                              2075
                                                     200.2
                                                                 221.2
                                                                             235.9
                                                                                          2100
1.1
.9
2.4
2.1
43.1
.7
3.5
8.0
84 ..9
1.0
.9
2.3
2.5
43.8
.9
5.1
8.6
102.7
1.4
1.0
1.8
2.4
43.8
1.0
7.5
9.6
131.7
1.8
.9
1.3
2.2
42.7
.9
8.5
8.5
154.4
1.6
.9
1.0
2.3
44.5
1.5
11.5
9.4
163.2
1.3
.9
.8
2.1
43.3
, 1.6
12'. 7
9.2
154.2
226.1
                                               B-110

-------
                                                     Appendix B:  Implementation of the Scenarios
RAPID
REGION
                                         TABLE B-171

                                     PRODUCTION OF WHEAT
                                    (Million Metric Tons)
                              1985
                                          2000
                                                      2025
                                                                  2050
                                                                             2075
TOTAL
                             481.1
                                         628.2
                                                     843.1
                                                                 966.3
                                                                             975.1
                                                                                         2100
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
72.
108.
16.
142.
40,
12.
11.
17.
59,
.6
.1
.3
,6
,7
,3
,0
.7
;9
97.
132,
24,
164,
47.
14,
15
23
109
.6
.0
.3
.6
.0
.6
.1
.9
.1
127.
180.
34.
190.
54.
17.
22.
36.
180.
4
5
0
6
6
3
0
1
8
141
166
34
211
60
19
26
60
246
.7
.1
.3
.9
.6
.0
.4
.0
.2
129
155
31
206
61
22
32
64
271
.7
.6
.8
.2
.0
.5
.2
.7
.4
126
154
' 31
209
61
24
36
66
284
.8
.0
.1
.3
.8
.5
.2
.8
.9
                                                                                        995.3
REGION             '"          1985
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL                        277.9
                                         TABLE B-172

                                      PRODUCTION OF RICE
                                     (Million Metric Tons)
                                          2000
                                         376.5
                                                      2025
                                                                  2050
                                                                             2075
                                                     536.9
                                                                 655.7
                                                                             708.9
                                                                                         2100
3.
2,
10,
4,
100
1
7
10
137
.9
.0
.1
.0
.8
.4
.3
.7
.7
3.
2.
. 10.
5,
115.
2.
13,
14.
208-
.8
.7
.6
,7
,5
.0
.3
.0
.9
6.
3,
9,
6,
123,
2,
24,
19.
341,
.2
.7
.3
.4
.8
.8
.4
.2
.0
8.
4,
9.
6.
125,
3.
35,
22.
439,
.9
.7
.5
.9
.7
.3
.6
.4
.0
8.
4.
8.
6,
126.
3.
44.
24.
481,
,1
,6
.7
.7
.7
,9
.5
,0
.7
7
4
8
6
125
4
49,
24,
494
.7
.5
.4
.7
.9
,1
.4
.3
.3
                                                                                        725.3
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia
TOTAL
                                         TABLE B-173

                                 PRODUCTION OF COARSE GRAINS
                                    (Million Metric Tons)
                              1985
                             809.9
                                          2000
                                                      2025
                                                                  2050
                                        1074.6
                                                    1433.3
                                                                1728.4
                                                                              2075
                                                                            1851.6
                                                                                         2100
233
139
10
162
82
6
56
69
50
.3
.5
.3
.3
.3
.6
.0
.0
.5
278
206
26
203
99
9
85
102
62
.2
.6
.2
.6
.9
.7
.8
.3
.4
308
279
50
267
111
14
127
194
79
.2.
.7
.7
.7
.1
.5
.8
.6
.0
314.
292.
86.
311.
119.
18.
155.
352.
78.
2
6
1
6
3
,2
.0 .
,7
,8
304,
294.
84.
321,
127,
22,
202,
402,
91,
.0
.9
,3
.9
.3
.6
.7
.4
.5
295
293
82
325
128
24
227
413-
95,
.8
.1
.1
.6
.5
.4
.4
.3
.6
                                                                                        1885.7
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle' East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-174

                                     PRODUCTION OF MEATS
                           (Million Metric Tons of Carcass Weight)
                              1985
                              68.0
                                          2000
                                          87.2
                                                      2025
                                                                  2050
                                                                              2075
                                                     113.4
                                                                 134.9
                                                                             143.0
                                                                                         2100
11.
14,
4.
12,
4,

5,
11,
3,
.0
,6
,8
.2
,4
.9
.1
,6
.4
13
16
5
14
5
1
8
16
5
.8
.5
.7
.0
.4
.6
.5
.5
.2
ISiSSK
13
18
7
15
6
2
• 15
24
9
K=SS
.5
.9
.3
.3
.6
.8
.2
.5
.2
8,
22,
9,
14.
7,
4,
22,
31.
13,
.8
.6
.5
,8
.5
.1
.8
.7
.2
8,
21,
8,
14,
7,
4
28
34
14
.0
.8
.8
.6
.6
.9
.4
.3
.5
7c
21.
8.
14.
7.
5,
31,
34,
' 14,
,7
.5
,5
,6
.5
.3
,4
.7
.9
146.2
                                               B-lll

-------
Policy Options for Stabilizing Global Climate
RAPID
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-175

                                 PRODUCTION OF DAIRY PRODUCTS
                             (Million Metric Tons  MiLk  Equivalent)
                              1985
                             508.6
                                          2000
                                         634.5
                                                      2025
                                                                  2050
                                                                              2075
                                                     856.2
                                                                1110.6
                                                                            1161.9
                                                                                         2100
61.
140.
23.
ISA.
8.
6.
20.
38,
54.
5
3
0
,7
,9
.7
0
,8
,7
71.
151.
28.
178.
14.
10,
32,
62.
85,
,6
.7
,3
.9
.0
,8
,0
.0
,1
10A.
168.
32.
188,
19,
17,
5A,
IDA,
167
.6
,0
,8
.3
.8
,7
.1
.1
.1
139,
177,
33,
178,
24
23
76,
143
314
,6
,8
.2
.0
.0
.3
,2
.7
.8
129
172
31
176
24
28
94
156
350
.0
.4
.0
.0
.5
.1
.2
.5
.2
124,
171,
30,
177,
24,
30
104
159
363
,8
,1
.1
.2
.6
.3
.7
.8
.7
                                                                                        1186.1
                                         TABLE B-176

                                 PRODUCTION OF OTHER ANIMALS
                          (Million Metric Tons of Protein Equivalent)
REGION

United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                              1985
                              19.5
                                          2000
                                                      2025
                                                                  2050
                                          27.4
                                                      43.2
                                                                  65.7
                                                                              2075
                                                                              68.0
                                                                                          2100
:=:
2
3
2
3
4


1
1
.2
.8
.0
.0
.4
.2
.9
.3
.8
2,
4
2
3
6

1
2
3
==SS
.3
.6
.8
.5
.9
.4
.6
.4
>0
2.
5,
4.
3.
13,

2,
4,
5,
,4
,4
.9
.8
,5
.7
.6
,6
.2
2,
5,
9,
3.
26,

3,
7,
7
,2
.2
.4
,4
.1
.9
.4
.2
.9
2,
5
8,
3
26,
1
4
7
8
.1
.1
.8
.4
.7
.1
.2
.9
.7
2
5
8
3
27
1
4
8
9
.0
.1
.6
.5
.0
.2
.7
.1
.1
                                                                                          69.3
REGION
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-177

                                  NITROGENOUS FERTILIZER USE
                                    (Million Metric Tons N)
                              1985
                              63.7
                                          2000
                                         100.5
                                                      2025
                                                                  2050
                                                                              2075
                                                     139.8
                                                                 147.7
                                                                             155.8
                                                                                          2100
10.4
11.9
1.0
13.5
12.1
1.0
2.1
2.9
8.7
:=KSRS=
11.9
18.7
1.1
22.4
17.0
1.5
4.4
4.7
18.8
12.7
23.3
1.6
25.4
20.1
2.4
8.1
8.3
37.9
10.9
21.8
2.0
27.6
21.2
3.1
10.8
11.0
39.3
10.0
21.5
1.8
27.7
21.5
3.4
13.1
12.8
44.0
9.7
21.4
1.7
27.9
21.5
3.6
14.4
13.2
45.6
                                                                                         158.9
REGION
========
United States
OECD Europe/Canada
OECD Pacific
Centrally Planned Europe
Centrally Planned Asia
Middle East
Africa
Latin America
South and East Asia

TOTAL
                                         TABLE B-178

                                 LAND UNDER RICE CULTIVATION
                                      (Million Hectares)
                              1985
                                          2000
                                                      2025
                                                                  2050
                                                                              2075
                                                                                          2100
1.

2,
2.
43,

3
8,
84.
.46
,1
,9
,4
.1
.1
.7
.5
.0
.9
.7
1.

2,
2,
43.

5,
8
103,
168,
,0
.9
.3
.5
.9
.9
.2
.7
.1
.4
1.
1,
1,
2,
43,
1,
7
9
131
199
,4
,0
.7
.4
.8
.0
.3
.4
.2
.2
1.
1.
1.
2.
43.
1.
8.
9.
155.
225.
8
0
6
4
6
1
8
1
7
1
1.
1.
1.
2.
43,
- 1,
10,
9
156
227
5
0
,3
.3
.8
.3
.1
.1
.8
.1
1.

1.
2.
43.
1.
10.
8.
148,
217,
3
9
1
,3
2
.4
4
,7
.1
.5
                                               B-112

-------
                                                     Appendix B:  Implementation of the Scenarios
sew
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
CEMENT PRODUCTION
                                            TABLE B-179

                                       C02 EMISSIONS BY TYPE
                                         (Petagrams C/Yr)
TOTAL
1985

 5.1
  .7
  .1

 6.0
2000

 6.2
 1.2
  .2

 7.6
2025

 7.6
 1.8
  .2

 9.6
2050

 7.9
 1.7
  .2

 9.9
2075

 9.0
  .4
  .3

 9.6
                                                                                             2100
                                                                                             10.7
ACTIVITY
                                            TABLE B-180

                                       N20 EMISSIONS BY TYPE
                                         (Teragrams N/Yr)
                                  1985
                                              2000
                                                          2025
                                                                      2050
TOTAL
                                  12.5
                                              14.3
                                                          16.5
                                                                      17.0
                                                                                 2075
                                                                                  15.9
                                                                                             2100
COMMERCIAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BIOMASS BURNING
NATURAL LAND EMISSIONS
OCEANS/FRESHWATER
1.0
1.6
.4
1.4
6.0
2.0
1.4
2.5
.6
1.8
• 6.0
2.0
1.6
3.5
1.0
2.3
6.0
2.0
1.6
4.1
.9
2.4
6.0
2.0
1.8
4.5
.2
1.4
6.0
2.0
1.9
4.6
.0
1.1
6.0
2.0
                                                                                             15.6
                                            TABLE B-181

                                       CH4 EMISSIONS BY TYPE
                                         (Teragrams CH4/YD
ACTIVITY                          1985

COMMERCIAL ENERGY COMBUSTION
FUEL PRODUCTION & TR,
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS /FRESHWATER
WILD RUMINANTS AND TERMITES
TOTAL                            510.7
                                              2000
                                                          2025
                                                                      2050
                                             581.0
                                                         687.9
                                                                     748.4
                                                                                  2075
                                                                                 783.9
                                                                                             2100
BUSTION 2.
NSMISSION 60.
75.
109.
55.
30.
115.
15,
RMITES 44.
BILIZATION 5,
.0
.0
.2
,4
,1
,0
.0
.0
.0
.0
2.
76.
94,
125,
68.
35,
115,
15,
44.
5,
.2
.7
.4 '
.3
.1
.5
.0
.0
.0
.0
2
97
125,
149
87,
46
115,
15
44
5
.8
.9
.0
.4
.4
.4
.0
.0
.0
.0
3
105
151
165
86,
58,
115.
15
44
5
.0
.0
.4
.1
.9
.1
.0
.0
.0
.0
3
127
171
176
50
76
115
15
44
5
.6
.0
.7
.0
.5
.2
.0
.0
.0
.0
4
154
178
168
40,
104,
115,
15
44
5,
.4
.2
.7
.7
.2
.5
.0
.0
.0
.0
                                                                                            829.7
                                            TABLE B-182

                                       NOx EMISSIONS BY TYPE
                                         (Teragrams N/Yr)
ACTIVITY                           1985
COMMERCIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING
TOTAL                             54.2
                                               2000
                                              61.2
                         2025

                        32.9
                        22.1
                        12.5
                         3.5

                        71.1
                         2050

                        34.1
                        22.0
                        12.5
                         3.5
                                                                                   2075
                                                                                              2100
                                    42.8
                                    10.2
                                    12.
                                     3,
                                                                      72.2
                                                                                  66.7
                                                                                             69.0
                                               B-113

-------
Policy Options for Stabilizing Global Climate
sew
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
AGRICULTURAL BURNING
HOOD USE
WILDFIRES
OCEANS

TOTAL
                                  1985
160.0
110.0
 20.0
 10.0
 20.0
                                            TABLE B-183

                                        cc EMISSIONS  BY'TYPE
                                          (Teragrams  C/Yr)
                                              2000
            188,
            254.
117.8
 20.5
 10.0
 20.0
 2025

249.5
394.5
130.0
 21. tf
 10.0
 20.0

82S.4
                                                                      2050
273.6
379.2
137.1
 22.3
 10.0
                                     20.0
                                                                     842.2
                                                                                  2075
                                                                                 614.1
 2100

437.2
  S-.6-
126.9'
 24.3
 10.0
 20.0

623.0
                                               B-114

-------
RCW
                                                     Appendix B: Implementation of the Scenarios
ACTIVITY
COMMERICIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
CEMENT PRODUCTION
TOTAL
                                            TABLE B-18A

                                       C02 EMISSIONS BY TYPE
                                         (Petagrams C/Yr)
.985
5.1
.7
.1
2000
7.0
.9
.2
2025
11.2
1.0
.3
2050
15.6
1.0
.3
2075
20.5
1.1
.A
2100
25.0
.8
.A
                                   6.0
                                               8.1
                                                          12. A
                                                                     16.9
                                                                                 22.0
                                                                                             26.1
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BIOMASS BURNING
NATURAL LAND EMISSIONS
OCEANS/FRESHWATER
TOTAL
                                            TABLE B-185

                                       N20 EMISSIONS BY TYPE
                                         (Teragrams N/Yr)
                                  1985
                                  12.5
                                             2000
                                              1A.2
                                                         2025
                                                                     2050
                                                          16.1
                                                                     17.2
                                                                                 2075
                                                                                 18.1
                                                                                             2100
1.0
1.6
.A
l.A
6.0
2.0
1.5
2.5
.5
1.7
6.0
2.0
2. A
3.5
.5
1.7
6.0
2.0
3.2
3.7
.6
1.8
6.0
2.0
3.8
3.9
.6
1.8
6.0
2.0
A. 2
3.9
.A
1.6
6.0
2.0
                                                                                             18.1
ACTIVITY
                                           TABLE B-186

                                     CHA EMISSIONS BY TYPE
                                       (Teragrams CHA/Yr)
                                  1985
                                             2000
                                                         2025
                                                                     2050
                                                                                 2075
TOTAL
                                 510.7
                                             590.1
                                                        731.9
                                                                    901.1
                                                                               10AA.5
                                                                                              2100
COMMERICAL ENERGY COMBUSTION
FUEL PRODUCTION & TRANSMISSION
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS/FRESHWATER
WILD RUMINANTS AND TERMITES
METHANE HYDRATE DESTABILIZATION
2
60,
75.
109
55,
30,
115,
15,
AA
5,
.0
.0
.2
.A
.1
.0
.0
.0
.0
.0
2.
88.
9A.
125.
60.
39.
115.
15.
AA.
5.
3
5
5 •
7
A
6
0
0
0
0
3,
152.
12A,
1A8.
63,
60.
115,
15.
AA.
5,
.7
.1
.6
.7
.6
.3
,0
.0
.0
.0
5.
230,
156,
167.
65.
97.
115,
15,
AA,
5,
. 1
.2
.0
.9
.7
.2
.0
.0
.0
.0
6,
311.
163.
169.
66.
1A7.
115,
15,
AA,
5,
.A
.9
.6
.5
.A
.6
.0
.0
.0
.0
8. A
389. A
166.8
162.3
55.3
16A.9
115.0
15.0
AA.O
5.0
                                                                                            1126.1
                                            TABLE B-187

                                       NOx EMISSIONS BY TYPE
                                         (Teragrams N/Yr)
ACTIVITY                          1985
COMMERICIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING
TOTAL                             5A.2
                                             2000
                                              62.A
                                                         2025
                                                                     2050
                                                         79.2
                                                                     95.A
                                                                                 2075
                                                                                110.A
                                                                                             2100
2A.2
13.9
12.5
3.5
31.0
15.3
12.5
3.5
A7.0
16.2
12.5
3.5
62.7
16.7
12.5
3.5
77.5
16.9
12.5
3.5
91.5
1A.O
12.5
3.5
                                                                                            121.6
                                              B-115

-------
Policy Options  for Stabilizing Global Climate


RCW

                                            TABLE B-188

                                       CO EMISSIONS BY TYPE
                                         (Teragrams C/Yr)

ACTIVITY   .                       1985        2000        2025        2050        2075         2100
COmERCIAL ENERGY COMBUSTION     185.8       197.6       334.9       477.5       636.0        862.7
TROPICAL DEFORESTATION           160.0       195.1       210.4       225.8       241.1        164.4
AGRICULTURAL BURNING             110.0       119.5       130.6       134.0       128.0        118.6
WOOD USE                          20.0        19.5        18.7        18.0        17.2         16.5
OCEANS                            20.0        20.0  •      20.0        20.0        20.0         20.0
WILDFIRES                         10.0        10.0        10.0        10.0        10.0         10.0

TOTAL                            505.8       561.7       724.6       885.3      1052.3       1192.2
                                               B-116

-------
RCHA
                                                     Appendix B:  Implementation of the Scenarios
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
CEMENT PRODUCTION
                                          TABLE B-189

                                     C02 EMISSIONS BY TYPE
                                        (Petagrams C/Yr)
 1985

  5.1
   .7
   .1
TOTAL
                                   6.0
2000

 7.8
 1.2
  .2

 9.1
2025

19.8
 1.8
  .3

21.9
                                                                      2050
                                                                      36.6
2075

49.6
  .4
  .4

50.3
2100

5it.it
  .0
  .4

54.8
                                          TABLE B-190
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BIOMASS BURNING
NATURAL. LAND EMISSIONS
OCEANS/FRESHWATER
                                     N20 EMISSIONS BY TYPE
                                        (Teragrams N/Yr)
                                  1985
TOTAL
                                  12.5
             2000

              1.7
              2.5
               .6
              1.9
              6.0
              2.0

             14.7
                                                          2025
                                                          18.5
                        2050

                         5.7
                         3.7
                          .9
                         2.4
                         6.0
                         2.0
                       ;==:=::==:—
                        20.7
                        2075

                         7.9
                         3.9
                          .2
                         1.4
                         6.0
                         2.0

                        21.3
            2100

             9.0
             3.9
              .0
             1.1
             6.0
             2.0

            22.0
                                          TABLE B-191
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
FUEL PRODUCTION & TRANSMISSION
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS/FRESHWATER
WILD RUMINANTS AND TERMITES
METHANE HYDRATE DESTABILIZATION

TOTAL
                                      CH4 EMISSIONS BY TYPE
                                        (Teragrams CH4/Yr)
                                  1985
  2
 60
 75.2
109.4
 55.1
 30.0
115.0
 15.0
 44.0
  5.0

510.7
                                              2000
                                                          2025
                                             614.4
             5.0
                                                         911.9
                                                                      2050
                         7,
                       544,
                       156,
                       167.9
                        86.5
                        97.2
                       115.
                        15,
                        44,
                         5.0
                                                                    1237.6
                        2075

                         8.9
                       786.5
                       163.6.
                       169.5
                        48.9
                       147.6
                       115.0
                        15.0
                        44.0
                         5.0

                      1504.0
                                                                                              2100
            10.4
           854.6
           166.8
           162.3
            39.0
           164.9
           115,
            15.
            44.
                                                 5.0
                                                                                            1576.9
                                          TABLE B-192
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING

TOTAL
                                     NOx EMISSIONS BY TYPE
                                        (Teragrams N/Yr)
                                  1985
                                  54.2
                                              2000
                                              67.1
                                                          2025
                                                         104.9
                                                                      2050
                                                                     145.3
                                                                                  2075
                                                                                 174.2
                                                                                              2100
                                                                                             186.8
                                               B-117

-------
Policy Options for Stabilizing Global Climate
RCWA
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
AGRICULTURAL BURNING
HOOD USE
WILDFIRES
OCEANS

TOTAL
                                          TABLE  B-193

                                      CO  EMISSIONS  BY  TYPE
                                        (Teragrams  C/Yr)

                                  1985        2000        2025
185.8       195.4
160,
110,
 20.
 10,
 20.0
                                                                      2050
                                                                                  2075
399.7
394.5
130.6
21.4
10.0
20.0
631.6
379.2
134.0
22.3
10.0
20.0
789.8
78.9
128.0
23.3
10.0
20.0
                                                                                             2100
                                                            942.9
                                             619.6
                                                         976.2
                                                                    1197.1
                                                                                1050.1
                                                                                            1122.3
                                               B-118

-------
                                                     Appendix B:  Implementation of the Scenarios
SCWP
ACTIVITY
                                          TABLE B-194

                                     C02  EMISSIONS BY TYPE
                                        (Petagrams C/Yr)
                                 1985
COMMERCIAL ENERGY COMBUSTION      5.1
TROPICAL DEFORESTATION             .7
CEMENT PRODUCTION                  .1
TOTAL                             6.0
2000

 5.6
 -.2
  .1

 5.6
2025

 5.5
 -.5
  .2

 5.2
2050

 4.2
 -.3
  .2

 4.0
2075

 3.3
 -.2
  .1

 3.3
2100

 2.6
 -.2
  .1

 2.6
ACTIVITY
COMMERICAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BIOMASS BURNING
NATURAL LAND EMISSIONS
OCEANS/FRESHWATER

TOTAL
                                           TABLE B-195

                                      N20  EMISSIONS BY TYPE
                                        (Teragrams N/Yr)
                                 1985
                                 12.5
                                            2000
                                             12.9
                                                        2025
                                                                    2050
                                                         13.1
                                                                    13.1
                                                                                2075
                                                                                13.0
                                                                                            2100
1.0
1.6
.4
1.4
6.0
2.0
1.2
2.3
.2
1.1
6.0
2.0
1.2
2.9
.0
1.0
6.0
2.0
1.1
3.0
.0
1.0
6.0
2.0
1.1
2.8
.0
1.0
6.0
2.0
1.2
2.6
.0
1.0
6.0
2.0
                                                                                            12.8
ACTIVITY
                                           TABLE B-196

                                     CH4  EMISSIONS BY TYPE
                                       (Teragrams CH4/Yr)
                                 1985
                                             2000
                                                        2025
                                                                    2050
TOTAL
                                510.7
                                            528.1
                                                        544.8
                                                                   527.9
                                                                                2075
                                                                               518.0
                                                                                            2100
COMMERCIAL ENERGY COMBUSTION
FUEL PRODUCTION & TRANSMISSION
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS/FRESHWATER
WILD RUMINANTS AND TERMITES
METHANE HYDRATE DESTABILIZATION
2.
60.
75.
109.
55.
30.
115.
15.
44.
5.
=K=±SSS
0
0
2
4
1
0
0
0
0
0
1
68
88
116
44
30
115
15
44
5
.9
.6
.2
.2
.0
.2
.0
.0
.0
.0
ZSSSSSS
1.
64.
104.
122.
38.
34.
115.
15.
44.
5.
=55=
.8
.6
0
,3
.5
.6
0
.0
,0
.0
1.
47.
112.
119.
38.
30.
115.
15.
44.
5.
=====
,8
.0
,0
2
.4
.6
.0
.0
.0
.0
5SS3S
1.
45.
112.
112'.
38.
28.
115.
15.
44.
5.
=5=
9
4
9
1
3
4
0
0
0
0
2.2
39.2
104.7
94.8
36.0
27.3
115.0
15.0
44.0
5.0
                                                                                           483.0
                                           TABLE  B-197

                                     NOx EMISSIONS  BY TYPE
                                        (Teragrams  N/Yr)
ACTIVITY                         1985
COMMERCIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING
TOTAL                            54.2
                                             2000
                                             51.8
                                                         2025
                                                                    2050
                                                         47.8
                                                                    44.0
                                                                                2075
                                                                                43.9
                                                                                            2100
24.2
13.9
12.5
3.5
24.6
11. 1
12.5
3.5
22.0
9.7
12.5
3.5
18.3
9.6
12.5
3.5
18.2
9.7
12.5
3.5
19.6
9.1
12.5
3.5
                                                                                            44.7
                                               B-119

-------
Policy Options  for Stabilizing Global Climate
SCOT
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
AGRICULTURAL BURNING
WOOD USE
WILDFIRES
OCEANS

TOTAL
                                 1985
185.8
160.0
110.D
 20.0
 10.0
 20.0

5Q5.8
                                           TABLE B-198

                                       CO EMISSIONS BY TYPE
                                         (Teragrams C/Yr)
 2000

135,5
 63,6
117.8
 19.4
 10.0
 20.0

366.3
 2025

102.1
  8.8
130.0
 18.5
 10.0
 20.0

289.4
 2050

 64.6
  2.2
137.1
 17.6
 10.0
 20.0

251.5
 2075

 69.7
  2.2
139.2
 16,8
 10.0
 20.0

257.9
 2100

'81.6
   .0
126.9
 15.0
 10.0
 20.0

254.5
                                               B-120

-------
                                                     Appendix 1$:  Implementation of the Scenarios
RCWP
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
CEMENT PRODUCTION
                                            TABLE B-199

                                       C02 EMISSIONS BY  TYPE
                                         (Petagrams C/Yr)
1985

 5.1
  .7
  .1
TOTAL
                                   6.0
2000

 5.9

  .2

 5.9
2025

 5.7
 -.5
  .2

 5.4
2050

 5.3
 -.3
  .3

 5.3
2075

 5.0
 -.2
  .3
                                                                                  5.2
2100

 5.2

  .3

 5.3
ACTIVITY
COMMERICIAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BIOMASS BURNING
NATURAL LAND EMISSIONS
OCEANS/FRESHWATER

TOTAL
                                           TABLE B-200

                                      N20 EMISSIONS BY TYPE
                                         (Teragrams N/Yr)
                                  1985
                                  12.5
                                              2000
                                              12.9
                                                          2025
                                                                      2050
                                                          13.3
                                                                      12.9
                                                                                 2075
                                                                                  12.7
                                                                                             2100
1.0
1.6
.it
1.4
6.0
2.0
1.3
2.3
.2
1.2
6.0
2.0
1.4
2.8
.0
1.0
6.0
2.0
1.3
2.6
.0
.9
6.0
2.0
1.3
2.4
.0
.9
6.0
2.0
1.5
2.2
.0
.9
6.0
2.0
                                                                                              12.6
ACTIVITY
                                           TABLE B-201

                                     CH4 EMISSIONS BY TYPE
                                       (Teragrams CH4/Yr)
                                  1985
                                              2000
                                                          2025
                                                                      2050
TOTAL
                                 510.7
                                             536.7
                                                         561.2
                                                                     567.3
                                                                                  2075
                                                                                 548.9
                                                                                             2100
COMMERCIAL ENERGY COMBUSTION
FUEL PRODUCTION & TRANSMISSION
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS/FRESHWATER
WILD RUMINANTS AND TERMITES
METHANE HYDRATE DESTABILIZATION
2,
60,
75,
109,
55,
30,
115,
15
44
5
.0
,0
.2
.4
.1
.0
.0
.0
.0
.0
1.
73.
88,
116,
43.
34,
115,
15,
44.
5,
,9
,0
,3
.6
,7
,3
.0
.0
.0
.0
2
69
103
121
37
48
115
15
44
5
.0
.2
.7
.6
.3
.4
.0
.0
.0
.0
1.
69.
115,
121,
36.
44.
115.
15.
44,
5,
.8
,6
,3
,2
.0
,5
.0
.0
,0
,0
1
75,
107
'107
34
42
115
15
44
5
.9
.9
.7
.9
.3
.3
.0
.0
.0
.0
2.1
81.2
98.0
91.2
32.0
41.2
115.0
15.0
44.0
5.0
                                                                                             524.6
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING

TOTAL
                                           TABLE B-202

                                     NOx EMISSIONS BY TYPE
                                        (Teragrams N/Yr)
                                  1985
                                  54.2
                                              2000
                                              52.9
                                                          2025
                                                                      2050
                                                          56.1
                                                                      47.8
                                                                                  2075
                                                                                  47.4
                                                                                             210*
24.2
13.9
12.5
3.5
25.8
11.1
12.5
3.5
30.6
9.5
12.5
3.5
=====3S
22.7
9.1
12.5
3.5
22.7
8.6
12.5
3.5
24.7
8.1
12.5
3.5
                                                                                             48.8
                                               B-121

-------
Policy Options for Stabilizing Global Climate


HCWP

                                           TABLE B-203

                                      CO EMISSIONS BY TYPE
                                        CTeragraras C/Yr)

ACTIVITY                          1985        2000        2025        2050        2073        2100
COMMERCIAL ENERGY COMBUSTION     185.8       133.4       109.6        58.4        61.8,       72,5'
TROPICAL DEFORESTATION           160.0        63.6         8.8         2.2         2.2        .  ,.0
AGRICULTURAL BURNING             110.0       119,5       130.6       134,0       128.0       118.6
WOOD USE                          20,0        18.1        15.3        12.9        10.9         9.2
WILDFIRES                         10.0        10.0        10.0        10.0        10.0        10.0
OCEANS                            20.0        20.0        20.0        20.0        20.0        20.0

TOTAL                            505.8       364.5       294.2       237.5       232.9       230.3
                                               B-122

-------
                                                     Appendix B:  Implementation of the Scenarios
RCWR
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
TROPICAL DEFORESTATION
CEMENT PRODUCTION
TOTAL
                                            TABLE  B-204

                                        C02  EMISSIONS  BY  TYPE
                                          (Petagrams C/Yr)
                                   1985
                                               2000
                                    6.0
                                                5.2
                                                           2025
                                                            2.1
                                                                       2050
                                               2075

                                                1.2
                                               -1.0
                                                 ,3

                                                 .5
                                                                                              2100
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
FERTILIZER USE
GAIN OF CULTIVATED LAND
BICMASS BURNING
NATURAL LAND EMISSIONS
OCEANS/FRESHWATER

TOTAL
                                             TABLE  B-205

                                        N20  EMISSIONS  BY  TYPE
                                          (Teragrams N/Yr)
                                   1985
                                   12.5
                                               2000
                                               12.8
                                                           2025
                                                                       2050
                                                           13.1
                                                                       12.7
                                                                                   2075
                                                                                   12.6
                                                                                              2100
1.0
1.6
.4
1.4
6.0
2.0
1.2
2.3
.2
1.2
' 6.0
2.0
1.2
2.8
.0
1.0
6.0
2.0
1.1
2.6
.0
.9
6.0
2.0
1.2
2.4
.0
.9
6.0
2.0
1.4
2.2
.0
.9
6.0
2.0
                                                                                              12.5
ACTIVITY
COMMERCIAL ENERGY COMBUSTION
FUEL PRODUCTION & TRj
ENTERIC FERMENTATION
RICE PRODUCTION
BIOMASS BURNING
LANDFILLS
WETLANDS
OCEANS/FRESHWATER
WILD RUMINANTS AND TERMITES
METHANE HYDRATE DESTABILIZATION

TOTAL
                                            TABLE B-206

                                       CH4  EMISSIONS  BY  TYPE
                                         (Teragrams CH4/Yr)
                                    1985
                                  510.7
                                               2000
                                                           2025
                                                                       2050
                                              529.6
                                                          520.8
                                                                      500.2
                                                                                   2075
                                                                                  484.1
                                                                                               2100
ON 2
SION 60
75,
109.
55.
30.
115.
15.
S 44
AT ION 5
.0
.0
,2
4
1
0
0
0
.0
.0
1.
66.
88.
116.
43.
34.
115.
15.
44.
5.
,8
.0
3
6
7
3
0
0
0
.0
1
29
103
121,
37.
48,
115.
15,
44
5
.7
.1
.7
.6
.3
.4
0
.0
.0
.0
1
2
115
121
36
44.
115,
15,
44
5
.6
.7
.3
.2
.0
.5
.0
.0
.0
.0
2.
10,
107.
' 107,
34,
42.
115.
15.
44,
5.
.0
.9
,7
9
,3
,3
0
,0
,0
,0
2.
19
98
91.
32
41,
115.
15.
44.
5.
.4
.0
.0
.2
.0
.2
.0
.0
.0
,0
                                                                                             462.7
ACTIVITY

COMMERCIAL ENERGY COMBUSTION
BIOMASS BURNING
NATURAL LAND EMISSIONS
LIGHTNING

TOTAL
                                            TABLE B-207

                                       NOx EMISSIONS BY  TYPE
                                          (Teragrams N/Yr)
1985

24.2
13.9
12.5
 3.5

54.2
                                               2000
                                                           2025
                                               51.3
                                                           53.2
                                                                       2050
45.5
                                                                                   2075
            46.0
                                                                                              2100
                       48.1
                                               B-123

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Policy Options for Stabilizing Global Climate

RCWR

                                            TABLE B-206

                                        CO EMISSIONS BY TYPE
                                          CTeragrams C/Yr)

ACTIVITY                            1985        2000        2025        2050        2075        2100
COMMERCIAL ENERGY COMBUSTION       185.8       132.1        88.0        45,9        61.6        78.3
TROPICAL DEFORESTATION             160.0        63.6         8.8         2.2         2.2           .0
AGRICULTURAL BURNING               110.0       119.5       130.6       134.0       128.0       118.6
WOOD USE     -     .                  20.0        18.1        15.3        12.9        10.9         9.2
WILDFIRES                           10.0        10.0        10.0        10.0        10.0        10.0
OCEANS                              20.0        20.0        20.0        20.0        20.0        20.0

TOTAL                              505.8       363,2       272.6       225.0       232.7       236.1
                                               B-124

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                                    APPENDIX C
                            SENSITIVITY ANALYSES
FINDINGS

*     The   degree   of  participation   by
developing  countries  in  policies  to  limit
warming is one of the most important factors
affecting equilibrium temperatures in the year
2100.  If only industrialized countries  adopt
policy  measures, equilibrium  temperatures
could increase  by 40% or more relative  to
scenarios with  global  cooperation.    This
suggests  that,  despite  uncertainties  about
future  economic growth  rates,  developing
countries will be a significant determinant in
the ultimate level of global warming.

•     Delaying  any   response  to  global
warming by OECD,  U.S.S.R., and  Eastern
Europe until the year 2010 and by developing
countries until 2025   might  increase  the
equilibrium warming commitment in 2050 by
40-50%.

•     The sensitivity of the climate system to
a given increase in greenhouse gases is one of
the  most important  causes  for uncertainty
about  the  ultimate  magnitude of global
warming.  For most  of the  analysis in this
report,  we  have assumed that the climate
sensitivity to doubling CO2 is 2.0  to 4.0°C;
broadening the range of climate sensitivity to
between  1.5 and 5.5°C for a CO2  doubling
causes the estimated range  for equilibrium
warming in 2050 to become 2.2-7.9°C in the
Rapidly  Changing  World  (RCW)  scenario.
The impact on realized warming is  less:  the
estimated range for 2050 increases from 2.0-
3.0°C to 1.6-3.5°C.    This  uncertainty  has
important  implications  for  the timing and
stringency of policy responses. Even  the lower
values, when considered with information on
the impacts of global warming, suggest a need
for caution about future emissions.

•     Uncertainties   in   biogeochemical
feedbacks appear to be potentially  the most
important  reason   to  suspect  that  global
warming  may  ultimately   be  greater   than
predicted  by   current  general  circulation
models.  Changes  in the  ocean circulation,
methane releases from hydrates, bogs, and rice
cultivation and other positive  feedbacks  could
amplify realized warming in 2100 by 20-40%
for a climate sensitivity of 2.0-4.0°C.  These
estimates are speculative,  they are based on
the fragmentary evidence currently available,
and these positive feedbacks may not occur or
may be delayed until the latter part of the next
century, but the potentially large impact on
the magnitude of warming suggests that even
more drastic  policy  measures  than those
considered  in  the  Rapidly Changing  World
with  Stabilizing Policies  (RCWP)  scenario
might be needed.

•     Sensitivity analyses   with  four  ocean
models for  CO2 uptake suggest that the path
of atmospheric concentrations could  follow
somewhat different trajectories, but very little
difference is observed in equilibrium warming
for  the  year  2100.    These  equilibrium
temperatures differ by at most 13% depending
on the type of ocean model.  More complex
ocean  circulation  models  currently in  the
research stage could broaden or decrease this
range in the future.

•     Assumptions about the total supply of
oil  and gas are among the least significant
factors affecting global warming  in  the year
2100.   While  gas  may  be  desirable  as a
transition  fuel, sensitivity  tests that assume
very  optimistic  estimates  of oil  and   gas
availability  at  each price  level suggest only
small changes  in  global warming.   A larger
impact could occur if policy measures were
adopted to  take advantage of the  assumed
increases in gas resources.

•     The sources of methane are subject to
considerable uncertainty.  Estimates of some
individual emission sources vary by a factor of
two to three.  Sensitivity tests that consider
extreme  assumptions  about anthropogenic
methane  emission  sources  suggest   that
uncertainties in  this  budget could  cause
equilibrium warming commitments in 2100 to
vary by about 5%. These results should not be
interpreted to  mean that methane is not an
important  greenhouse  gas, but  simply  that
uncertainties in the current  budget do not
greatly  affect  the  ultimate temperatures
derived in this report.
                                            C-l

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Policy Options for Stabilizing Global Climate
•     A  . comparison   between   current
atmospheric concentrations and growth rates
for the greenhouse gases and those calculated
with  the  atmospheric  composition model,
based   on   estimates   of   pre-industrial
concentrations and past emissions,  indicates
agreement.  The largest  discrepancies are for
relatively short-lived gases where emissions
have been increasing rapidly in recent years,
such as HCFC-22 and carbon tetrachloride.

•     Non-greenhouse gases such as NOX, CO,
and  non-methane  hydrocarbons  (NMHC)
affect the  lifetimes and  concentrations of
tropospheric  ozone  and   methane.     A
comparison  of  different  chemistry models
suggests    that    increases   in   methane
concentrations may vary by approximately  a
factor of three to four for similar assumptions
about NOX/CO/NMHC.   This  range may be
attributed to differences in initial budgets and
modeling  approaches  and  may ultimately
increase or decrease as other models become
available.

•     The  most important determinant of
future atmospheric concentrations of methane
appears to  be the growth rate  of  methane
sources.   While NOX  and  CO affect  the
lifetime of methane, model studies suggest that
assumptions about the emissions of these gases
are less important than assumptions about the
direct  emissions of  methane.    However,
considerable research is needed to further our
understanding  of  the  chemistry   of  the
atmosphere.

•     There is considerable uncertainty about
future  concentrations of tropospheric ozone
and about changes in composition at different
altitudes.    While  model  comparisons  all
suggest that increases in ozone are likely, the
effect of these changes in global temperatures
is difficult to predict.

•     For  the  major   sensitivity  analyses
presented  in  this  appendix,  Table   C-l
summarizes  the  impact  on  realized  warming
and equilibrium warming by  2050 and 2100
(assuming   a  3.0°C   climate  sensitivity).
Throughout  this  appendix,   results   are
discussed for 2.0-4.0°C climate sensitivities for
the Rapidly Changing World Scenario, with
any figures using the midpoint of this range,
i.e., a 3.0°C climate sensitivity, unless stated
otherwise.
                                            C-2

-------
                                                               \p[K'iidi\ {':  Sen.sitivitv Analyses
                                         TABLE €-1

                      Impact of Sensitivity Analyses on Ri-aliztd Warming
                                  and Equilibrium Warming

                           (degrees Celsius — 3,0°C climate sensitivity)
2050

Rapidly Changing World - No Response (RCW)
Rapidly Changing World - Stabilizing Policies (RCWP)
Sensitivity Case Assumptions
No Participation by Developing Countries3
Global Delay in Adopting Policies*
Non-Fossil Technolo^1
Fossil Resources
High Coal Prices'1
High Oil Supply*
High Gas Supp!yf
Methane Budget8
N2O From Fertilizer
Anhydrous Ammonia15
NjO Leaching1
NjO From Combustion*
CO2 From Biomass*
CO2 Models1
Oeschger et al.°
Bolin et ai,n
Bjorkstrom0
Siegenthalerp
Unknown Sink**
1.5-5.5"C Sensitivityr
Heat Diffusion4
Prather Model
CFC-11 Lifetime1
Chlorine/Col O,u
Trop Oj/CH/ "
OH/NOX*
Feedbacks
Ocean Circulation*
Methane*
COj/CHyUptake1
Realised
2.6a
1.6
2.1
2.2
2.4-2.5
2.4
2.6
2.6
2.5-2.7
2.6
2.6
2.6
2.5
-
-
2.4-2.6
1,6-3.5
2.0-2.9

2.6
2.5
2,6
2.5-2.6

3.5
2.8
3.0
Equilibrium
4.3°
23
3.2-3.4
3.4
3.9-4.1
3.8
4.3
4.4
4.2-4.5
4.3
4.3
4.3
4.3
4.2
4,3
4.3
3.9
4.0-4.5
2.2-7,9
4.3

4.3
4.1
4.4
4.3-4.4

4.5
4.7
5.0
2100
Realized
5.0°
2.1
3.3-3.7
2.9
4.2-4.5
4.1
4.8
5.0
4.9-5.3
5.0
5.0
5.0
5.0
-
-
4.4-5.2
3.1-7.0
4.1-5.7

5.0
4.6
5.1
4.9-5.1

7.4
5.6
6.4
Equilibrium
7.6°*
2.8
4.7-5.4
3.8
6.3-6.7
6.0
7.3*
7.6*
7.3-8.0*
7,6*
7.6*
7,6*
7.5*
7.3
7.5
7.5
6.6
6.5-7.8*
3,8-13.9*
7.6*

7.6*
7.0
7.7*
7.5-7.7*

8.1*
8.6*
9.1*
* Estimates of equilibrium warming commitments greater than 6° C represent extrapolations beyond the range
tested in most climate models, and this warming may not be fully realized because the strength of some positive
feedback mechanisms may decline as the Earth warms.
                                             C-3

-------
Policy Options for Stabilizing Global Climate
                                        TABLE C-l -- NOTES


    Developing countries were assumed to not participate in climate stabilization policies. The range represents
    uncertainty in the rate of technological diffusion; that is, even if developing countries do not participate, they
    will indirectly benefit from technological improvements as a result of stabilization policies among the developed
    countries.

    Impact if developed countries do not respond to global warming until 2010; developing countries delay to 2025.

    These ranges represent modest to optimistic assumptions about future commercial availability of non-fossil
    technologies, e.g., solar photovoltaics,  advanced  nuclear power designs, and  synthetic fuel production from
    biomass. Solar photovoltaic costs decline to 6 cents/kwh (1988$) by 2030 in the optimistic scenario and by 2050
    in the modest assumptions. Nuclear costs decline 0.5% annually with the optimistic assumptions and remain
    relatively flat in the modest assumptions.  The cost of producing and converting biomass to modern fuels
    reaches  $4.35/gigajoule for gas and $6.00 (gigajoule) for liquids by  2030 in the optimistic assumptions and by
    2050 in  the modest assumptions. The total amount of fuel available from biomass is 205 EJ.

    The impact of an escalation in coal prices above the RCW case by about 3% annually from 1985 to 2025 and
    about 1% annually from  2025  to 2100.

    The impact of an increase in global  oil resources to 25,000 EJ, more than  double the estimate in  the RCW
    case, assuming proportionate increases in resource availability at each cost level.

    The impact of an increase in global  natural gas resources to 27,000 EJ, more than 2.5 times the estimate in
    the RCW case, assuming proportionate increases in resource availability at each cost level.

    These ranges represent assumptions about the'felative sizes of anthropogenic versus non-anthropogenic sources
    of methane emissions, thereby affecting growth in emissions over time, i.e., high emission levels (373 Tg CH4)
    from anthropogenic activities such as fuel production and landfilling with low emission levels (137 Tg CH4)
    from natural processes such as oceans and wetlands, versus low anthropogenic emissions  (245 Tg CH4) with
    high natural emissions (265 Tg CH4).

    The impact of elevating the emission coefficient for the anhydrous ammonia fertilizer type (the percent of N
    evolved as N2O) from 2.5% to 4.0%.

    The impact of assuming reduced N2O emissions from fertilizer leaching into surface water and ground water,
    modeled by  decreasing all the fertilizer emission coefficients  by 2 percentage points.

    The impact of higher emission coefficients for N2O from combustion; assumes that N2O emissions are about
    20-25% of NOj emissions and the N2O emissions from combustion sources in 1985 equaled 2.2 Tg N, over
    2 times  the level assumed in the RCW case.

    The impact of assuming a higher estimate for the amount of carbon initially  contained in forest vegetation and
    soils (roughly a 50-100% increase) and a more rapid rate of change in land use, resulting in emissions of carbon
    of 281 Pg from 1980 and 2100 compared to 118 Pg C in the RCW scenario.
                                                                                                    \
    Realized warming was not calculated in these tests.

    This box-diffusion model represents carbon turnover below 75 meters as a purely diffusive process.

    A  12-compartment regional  model that  divides the Atlantic and  Pacific-Indian Oceans into  surface-,
    intermediate-,  deep-,  and bottom-water compartments and divides  the Arctic  and Antarctic Oceans into
    surface- and deep-water compartments.

    An advective-diffusive model that divides the ocean into cold and warm compartments; water downwells directly
    from the cold surface compartment into intermediate and deep layers.

    An outcrop-diffusion model that allows direct ventilation of the intermediate and deep oceans in high latitudes
    by incorporating an outcrop connecting all sublayers to the atmosphere.

    These ranges represent the impact of alternative assumptions about the "unknown carbon sink" that absorbs
    the unaccounted-for carbon in the carbon cycle. Two sensitivities  were analyzed: 1) a high case, where the
    size of the unknown sink increases  at the same rate as atmospheric CO2 levels compared with pre-industrial
    levels; and 2) a low case, where the size  decreases to zero exponentially at  2% per year.

    Atmospheric response to a doubling QfCO2 was varied from 1.5 to 5.5° C.


                                                  C-4

-------
                                                               Appendix C:  Sensitivity Analyses
                             TABLE C-l -- NOTES (continued)


Heal diffusion in the oceans is modeled as a purely diffusive process.  To capture some of the uncertainty
regarding actual heat uptake, ihe base case eddy-diffusion coefficient of 0.55x 10  m2/sec was increased to 2xlO'4
and decreased to 2x10° nr/sec.

The atmospheric lifetime of CFG-11, 65 years in the RCW case, was varied from 55 to 75 years. Increases
or decreases  in the atmospheric concentration of CFC-11, however, tend to be offset by corresponding
decreases or increases in atmospheric concentrations of other trace gases, such as other CFCs and CH4.

The amount of stratospheric ozone depletion due to chlorine contained in CFCs was increased from a 0.03%
to 0.20% decline in total column  ozone/(ppb)2 of stratospheric chlorine.

The rate at which tropospneric ozone forms as a result of CH4 abundance was increased.  In the RCW case,
this variable for the Northern Hemisphere is a 0.2% change in tropospheric ozone for each percentage change
in CH4 concentration; it was changed to 0.4% in the sensitivity analysis.

Tropospheric OH formation is affected by the level of NO, emissions.  A 0.1% OH change for every  1%
change in  NO, emissions for  the Northern Hemisphere  was assumed in the RCW case; in the sensitivity
analysis, a range of 0.05% to 0.2% was evaluated.

For this analysis we assumed that a 2°C increase in realized  warming would alter ocean circulation patterns
sufficiently  to shut  off net uptake of CO2 and heat by the oceans.

We assumed that with each 1°C increase in temperature, an additional 110 Tg CH4 from methane hydrates,
12 Tg CH4 from bogs, and 7 Tg CH4 from rice cultivation would be released.

This case illustrates the combined impact of several types of biogeochemical feedbacks:  1) methane emissions
from hydrates, bogs, and rice cultivation (see footnote above); 2) increased stability of the thermocline, thereby
slowing the rate of  heat and CO2  uptake of the deep ocean by 30% due to less mixing; 3) vegetation albedo,
which is a decrease  in global albedo as a result of changes in the distribution of terrestrial ecosystems by 0.06%
per 1°C warming;  4) disruption of existing ecosystems, resulting in transient reductions in biomass and  soil
carbon at the rate of 0.5 Pg C per year per  1°C warming;  and 5) CO2 fertilization, which is an increase in the
amount of carbon stored in the biosphere  in response to  higher CO2 concentrations by 0.3 Pg C per ppm.
                                             C-5

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Policy Options for Stabilizing Global Climate
INTRODUCTION

      The Rapidly Changing World (RCW)
and Slowly Changing World (SCW) scenarios
presented in Chapter VI describe two signifi-
cantly  different  futures  for  the  global
community.   Although these two potential
paths capture a wide range of uncertainty, they
do not represent all possible outcomes. Alter-
native  assumptions  are clearly  possible for
many of the parameters  specified  in  these
scenarios; these alternative specifications could
alter  the timing  and  magnitude  of global
climate  change described in the RCW and
SCW  scenarios.     To  understand   the
importance of these alternative assumptions,
this  appendix examines how  changes in key
parameters affect our portrayal of the rate and
magnitude of global climate  change.  These
sensitivity   analyses   include   alternative
assumptions about the  magnitude and timing
of global policies to combat  climate change,
rates of technological change,  trace-gas source
strengths and emission coefficients, the carbon
cycle,  sensitivity  of   the   climate  system,
atmospheric chemistry, and feedbacks.

      The sensitivity analyses  discussed in this
appendix are generally run  relative to the
Rapidly Changing World scenario (specifically
the RCW and RCWP cases),  unless specified
otherwise.

ASSUMPTIONS ABOUT THE
MAGNITUDE AND TIMING OF GLOBAL
CLIMATE STABILIZATION  STRATEGIES

      The analyses  of the  Stabilizing Policy
scenarios presented  in  this Report are  based
on the assumption that the global community
takes immediate, concerted action to contend
with  the consequences  of climate  change.
Potential actions, which  are  discussed  in
Chapters V,  VII, arid VIII, include reducing
the  amount of energy required  to meet the
world's   increasing   needs,   developing
alternative technologies that do not require
the  consumption  of  fossil  fuels,  halting
deforestation,  and   making   changes  in
agricultural  practices,  among others.   For
many reasons,  however,  the  world may not
respond  to the threat of climate change in a
timely fashion.   This section explores the
consequences of other possibilities, particularly
the   unwillingness  or  inability  of  some
countries to participate in climate stabilization
programs  and  the  implications of delaying
global action until a later date.

No Participation by the Developing Countries

      Most of the greenhouse gas emissions
currently  committing the world to climate
change  can be  traced  to activities by  the
industrialized   countries.     Although   the
quantity of emissions generated by developing
countries has been increasing, the argument is
sometimes made that since the greenhouse
problem  has  been  largely caused  by  the
industrialized countries, these countries should
be responsible for solving the problem.  Also,
despite   the   potential  environmental
consequences of global climate change, other
problems facing the developing countries, such
as poverty, inadequate health care, and other
apparently  more  pressing  environmental
problems may make it difficult for developing
countries to commit any resources  to climate
stabilization policies.

      Regardless of  the  merits  of  these
arguments, for this sensitivity analysis we have
assumed that developing countries  do  not
participate  in   any  climate   stabilization
activities;  that  is, only  developed countries
adopt policies to limit global climate change.
For  this  analysis the  developing countries
include  China  and centrally-planned Asian
economies, the  Middle  East, Africa,  Latin
America, and South/Southeast Asia. We have
assumed that industrialized countries (i.e., the
U.S., the rest of the OECD countries, and the
USSR and Eastern Europe) follow the path
assumed in the  Rapidly Changing World with
Stabilizing Policies  (RCWP)  scenario,  while
developing countries follow the path assumed
in the Rapidly Changing World No Response
(RCW)  case,  in  which  the  entire  global
community  does  not   respond to  climate
change.

      Even if developing countries do  not
participate in  global stabilization policies,
however, policies adopted by the industrialized
countries  are likely to lead  to  technological
advancements, altered market conditions, etc.,
that  indirectly   reduce  emissions  in  the
developing countries as well.  For example,
advancements by the developed  countries in
automobile fuel efficiency  or  fuel supply
                                            C-6

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                                                             Appendix C:  Sensitivity Analyses
technologies may be partly  adopted by  the
developing countries, tangentially allowing for
some climate stabilization benefits.   If  the
developing  countries   do  not  participate,
however, they may tend to adopt technological
advances more slowly and at a higher cost than
if they had participated  from the  start.  This
slower rate of technological diffusion could
occur for  many reasons -- for example, if the
industrialized countries  take  actions   that
prevent easy access to improved technologies
or they are unwilling or unable to make  the
necessary capital available for investment, or if
developing  countries decide to invest  their
limited resources in other areas.

      Since  we  cannot be  certain  of  the
direction   that   non-participation   by   the
developing countries might take, we analyzed
two  cases to capture the potential range of
likely possibilities.  In the  first case,  little
technological diffusion was assumed, resulting
in a future  path  of energy consumption and
investment  trends  for  developing countries
similar to those assumed in the RCW scenario.
In the second case, developing countries were
assumed  to have  greater  access   to  the
efficiency  improvements  and  technological
advances assumed for  the RCWP case as a
result  of   policies  by  the  industrialized
countries   to  make  these  improvements
available and extend the credit necessary  for
investment  by  the developing countries in
these improvements.

      In this analysis key assumptions for the
developing countries included the following:
(1) rates of energy efficiency improvements for
all sectors are the same as in the RCW case or
midway between  the RCW and RCWP  case;
for  example,  automobile  efficiency levels,
which by 2050 in developing countries were 6.7
liters/100 km (35 mpg) in the RCW case and
3.1 liters/100 km (75 mpg) in the RCWP case,
were varied from 5.9-4.1 liters/100 km (40-58
mpg); (2) CFCs are not phased  out (although
compliance with the Montreal Protocol would
still  occur); (3)  agricultural practices that
cause methane emissions from rice and enteric
fermentation  and  nitrous   oxides   from
fertilizers  do not change  or  would show
modest   improvements;  (4)  deforestation
continues  as  in  the  RCW  case  with  an
exponential decline in forest area;  (5)  non-
fossil energy supply technologies developed by
the industrialized countries arc available  to
developing countries at a later  date and a
higher cost than assumed in the RCWP case;
for example, technological di(fusion of biomass
gasification technology would  occur 10 years
later  than it would  in  the RCWP case, but
feedstock costs would remain high due to a
lack of investment by the developing countries
in highly productive energy plantations; and
(6) no additional incentives are provided for
increased use of natural gas.


      Without   the  participation  of  the
developing   countries   to   stabilize   the
atmosphere, the  amount of greenhouse gas
emissions will increase  substantially:  In the
analysis considered here, CO2 emissions are
3.9-5.3 Pg C higher than in the" RCWP case by
2050  and  4.6-8.5  Pg   C higher  by  2100
(emissions by 2100 are 12.3 to 16.2 Pg C lower
than  in  the RCW case since industrialized
countries adopt climate stabilization policies);1
other  greenhouse  gas   emissions  are also
higher. These emission increases are sufficient
to increase realized warming by 0.4-0.6°C  in
2050 compared with the RCWP case and 1.2-
1.6°C  by  2100   (see   Figure  C-l),  with
equilibrium warming by 2100 up to 1.9-2.6°C
higher.  Figure C-l also shows the results for
the SCW scenario.  In this scenario, emission
increases are sufficient  to increase realized
warming by 0.4-0.5°C in  2050 compared with
the SCWP case  and 0.8-1.0°C  by 2100, with
equilibrium warming by 2100 up to 1.2-1.6°C
higher.


      The implications of these results are
clear:   even  if  the  industrialized  countries
adopt very stringent policies to counteract the
effects of climate change,  the atmosphere
continues to warm at a rapid rate.  As a result,
unilateral action by the industrialized countries
can significantly slow the rate and magnitude
of climate  change, but   because   of   the
growing impact that developing countries have
on   the   global  climate,   without   the
participation  of  the developing  countries,
substantial  global warming is unavoidable.
Because most of the world's population resides
in these  countries,  their role  in  climate
stabilization becomes increasingly important as
the demand  for resources to feed and clothe
their  growing population and improve  their
standard of living expands.
                                            C-7

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  Policy Options for Stabilizing Global Climate
                                FIGURE C-l

                  INCREASE IN REALIZED WARMING
       WHEN DEVELOPING COUNTRIES DO NOT PARTICIPATE
                      (Based on 3.0 Degree Sensitivity)
         Slowly Changing World
   4 -
I  3
m
                          SCW
 SCWP with
No Participation
 by Developing
  Countries
                          SCWP
  1986  2000   2026  2060   2076   2100
                 Year
                                  Rapidly Changing World
                                       5 -
                                       4 -
3 -
 RCWP with
No Participation
 by Developing
  Countries
                            1986  2000  2025   2050   2076
                                                        2100
                                   C-8

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                                                            Appendix C:  Sensitivity Analyses
Delay in Adoption of Policies

      The Stabilizing Policy cases (including
the RCWR case) presented in Chapter VI
assume  that  the global  community  takes
immediate action to respond to the dangers
posed by climate  change.  For this sensitivity
analysis we have assumed  that  the global
community delays any response to the threat
of climate change, with developed countries
(i.e, the United States, the rest of the OECD
countries, the USSR and  Eastern European
economies) delaying action until 2010, and the
developing  countries delaying action until
2025.   Additionally, once  regions do initiate
action to combat global warming, they do so at
a slower rate than assumed in the RCWP case.
This slower approach assumes a minimum 25-
year delay in attaining the policy goals of the
RCWP  case; that is,  levels  of technological
improvement, availability of alternative energy
supply technologies, etc., will be achieved at
least 25 years  later.   For  example, in  the
RCWP case, automobile efficiency reaches 3,1
liters/100 km (75  mpg) by 2050; in the Delay
case  industrialized   countries   reach   3.9
liters/100  km  (60  mpg)   by  2050,  while
developing countries reach 4.7 liters/100 km
(50  mpg);  the  rate  of  energy  efficiency
improvement for  the residential, commercial,
and industrial sectors is unchanged from the
rates assumed in the RCW case, through 2010
for industrialized  countries and through 2025
for developing  countries.  After these years,
energy efficiency  improvements occur at the
same  rate assumed in the RCWP case.   In
addition, the implementation  of  production
and consumption  taxes on fossil fuels from the
RCWP  case   is   delayed   until   2010  for
developed  countries  and  until  2025  for
developing countries.

      Delaying the adoption  of  policies  to
stabilize the atmosphere significantly increases
the Earth's  commitment to  global warming.
With delay by the industrialized countries until
2010 and  by the developing countries until
2025,   the  increase  in  realized  warming
compared to that  assumed in the RCWP case
is 0.5-0.7°C  by 2050 and  0.6-0.9°C by 2100;
equilibrium  warming  is 0.7-1.4'C  higher by
2050 and 0.7-1.4°C higher  by 2100 (based on
climate sensitivities of 2.0-4.0°C; see Figure C-
2),  Figure C-2 also shows the results for the
Slowly Changing  World scenarios.  If global
delays do  occur, the  increase  in  realized
warming compared  to  that assumed in the
SCWP case is 0.4-0.6°C by 2050 and 0.4-0.6°C
by  2100;  equilibrium  warming is  0.5-1.1°C
higher by 2050 and 0.4-0.8°C higher by 2100
(based on climate sensitivities of 2.0-4.0°C).

ASSUMPTIONS AFFECTING RATES OF
TECHNOLOGICAL  CHANGE

      The  extent of  global  warming will
depend on the  availability of energy supplies
and technologies that minimize dependence on
carbon-based fuels, nitrogen-based fertilizers,
and other sources of greenhouse gas emissions.
The availability of non-fossil fuel technologies
and  the  development  of  new  production
methods  that significantly increase the supply
of natural  gas could have  an impact on the
rate of change  in greenhouse gas emissions.
Alternative  assumptions   regarding  these
factors are presented below.

Availability of Non-Fossil Technologies

      Most technologies in use currently rely
on fossil fuels to supply their energy needs. In
the   RCW,  fossil-fuel-based   technologies
continue to  dominate  throughout the next
century:  by 2100 fossil fuels still supply over
70% of primary  energy  needs.  However,  if
non-fossil technologies can be commercialized
earlier, the magnitude of global climate change
can be reduced  because these technologies do
not emit the greenhouse  gases that cause
global warming. To evaluate the implications
of the availability of non-fossil technologies,
two different scenarios were analyzed: (1) an
Early  Non-Fossil  case, in which non-fossil
technologies, specifically solar photovoltaics,
advanced   nuclear   power  designs,  and
production of synthetic fuels from btomass, are
commercially available by 2000 at a rate faster
than that assumed in the RCWP case; and (2)
an  Intermediate  Non-Fossil case, in which
non-fossil technologies are widely available by
the middle  of the next century (i.e., greater use
of non-fossil technologies than in the RCW
case, but less than in the RCWP case).  The
intent of these two cases is to capture a range
of possible roles for non-fossil technologies,
with the first case reflecting very optimistic
assumptions on non-fossil availability and the
second  case   reflecting  more   modest
assumptions.
                                            C-9

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Policy Options for Stabilizing Global Climate
                             FIGURE C-2

                INCREASE IN REALIZED WARMING
           DUE TO GLOBAL DELAY IN POLICY OPTIONS
                     (Based on 3.0 Degree Sensitivity)
        Slowly Changing World
  6 -
 1985  2000  20ZS   2050  2075   2100
Rapidly Changing World
                                   1986  2000  2025   2060   207S  2100
                                C40

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                                                             Appendix C: Sensitivity Analyses
      In the Early Non-Fossil case, non-fossil
energy sources increase their  share of total
primary energy supply from 12% in 1985 to
about 40% by 2025 and 55% by 2100, while in
the Intermediate Non-Fossil case the share for
non-fossil  technologies increases to about 20%
by 2025 and about 50% by 2100 (see Figure
C-3a).  As shown in Figure C-3a,  the non-
fossil share of total energy is lower in the long
run compared with the share in the RCWP
case;  this  is because other policies that were
included in the RCWP case to discourage the
use of fossil fuels were not included in this
case.  In both cases, however, an increased role
for non-fossil  technologies  can affect  the
amount of global warming.  As shown in
Figure C-3b, for the two cases  presented here
the amount of realized  warming compared
with the RCW case could be  reduced about
0.1-0.2°C  by 2050  and  0.4-0.9°C  by 2100;
equilibrium warming could be reduced about
0.2-0.6°C by 2050 and 0.6-1.7°C by 2100 (based
on 2.0-4.0°C climate sensitivities).

Cost and Availability of Fossil Fuels

      As  discussed in Chapters  IV and  V,
there  is  significant  uncertainty  over  the
amount  of  fossil-fuel  resources  available
globally and the cost at which these  resources
could be produced. The development of the
fossil  energy   resource  estimates  and  the
associated extraction costs used in this analysis
are documented in ICF (1988).  Given the
uncertainties about the cost and availability of
fossil energy supplies, several sensitivity cases
were analyzed.  These are discussed  below.

High Coal Prices

      In the RCW case from 1985 to 2050
there was no  real escalation  in coal prices.
Given the vast quantity  of  coal  resources
available   worldwide,   and   the  rate  of
productivity improvements in  coal extraction
that have helped to contain cost increases, coal
prices may not escalate in real  terms (e.g.,
from 1949 to  1987, U.S. coal  prices declined
an average  of 0.2%  annually  [EIA, 1988]).
Since the longer-term price path for coal is
highly uncertain, however, we analyzed  the
impacts of a high price coal case where coal
prices escalated about 1% annually from 1985
to 2100.
      As illustrated in Figure C-4a, increasing
coal prices have a significant impact on the
amount  of primary energy consumed; for
example, by 2100 total primary energy demand
is  more than 15% lower compared with this
demand  in the RCW  case.   Most  of this
reduction in energy demand is due to the
decline in coal use as consumers respond to
the escalating prices. Because coal is a major
energy resource for electricity production and
synthetic fuel production, the impact on the
level  of  greenhouse gas  emissions  is  fairly
substantial.  For example, CO2 emissions are
reduced nearly  40% by 2100. The reductions
in greenhouse gas emissions have a significant
impact on global warming, as shown in Figure
C-4b, which  indicates  a decline  in realized
warming from the RCW case of 0.2-0.3°C by
2050  and 0.7-1.0°C  by  2100 (assuming 2.0-
4.0°C climate sensitivities). The corresponding
decrease in equilibrium warming by  2100  is
Alternative  Oil and  Natural  Gas  Supply
Assumptions

      There are many uncertainties concerning
the amount of oil and natural gas  supplies
available worldwide. As discussed in Chapter
V, for example, the viability of increased use
of natural gas as a  near-term option for
reducing greenhouse gas  emissions critically
depends  on  the   amount  of  natural  gas
available, its price, the length of time over
which adequate supplies can be secured, etc.
To  explore   how sensitive  the  level  of
greenhouse gas emissions  may be  to  the
amount of oil  and natural gas supplies,  two
sensitivity  cases  assuming   higher  global
supplies have been analyzed:  (1) a high oil
resource  case  and  (2) a high  natural  gas
resource  case.    The  higher  oil  resource
estimates were derived from Grossling  and
Nielsen (1985), who indicated that resources
may be more than double the estimates used
in the base case analyses  (which were about
12,000 EJ of conventional oil resources).2  For
this  analysis  we  assumed  conventional oil
resources of about 25,000 EJ.  Natural gas
estimates were derived from Hay et al. (1988),
which assumed in-place resources  of about
150,000 EJ.  For  purposes of this sensitivity
case,    we   assumed  that   technological
improvements in gas extraction would permit
                                            C-ll

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Policy Options for Stabilizing Global Climate
                            FIGURE C-3
         AVAILABILITY OF NON-FOSSIL ENERGY OPTIONS
  (a)     Non-Fossil Share Of Total Primary Energy Supply

     100
    u
    o
    0.
      80
      60
      40
      20
                                    RCWP


                                    Non-Fossil
                                     Energy Options


                                    RCW
  (b)
    w
    1  4
    4)
    o
    W  o
    4)
    Q
Increase In Realized Warming

  (Based on 3.0 Degree Sensitivity)
        1985  2000
     2025
  2050
Year
2075
                                    RCW

                                    Non-Fossil
                                      Energy Options
                                    RCWP
2100
                              C-12

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                                        Appendix C: Sensitivity Analyses
                          FIGURE C-4
 IMPACT OF 1% PER YEAR REAL ESCALATION IN COAL PRICES
(a)
Total Primary Energy Demand
   1500
   1250
 » 1000
 o
 s  75°
 UJ
    500
    250

      0
                                                    RCW
                                   High Coal Prices
                                   RCWP
(b)
 Increase In Realized Warming
  (Based on 3.0 Degree Sensitivity)
       1985 2000
     2025     2050
           Year
2075
                                                   RCW

                                                   High Coal Prices
                                                 ^ RCWP
2100
                            C-13

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Policy Options for Stabilizing Global Climate
an additional 10% of in-place resources to be
economically recovered.   This amount  was
added  to  the baseline  estimates of pioved
reserves   and    economically   recoverable
resources, for a total resource base of about
27,000 EJ.  We  must  emphasize that  these
sensitivity cases do not examine policy options
that encourage greater  use of oil and natural
gas; rather, they only attempt to examine how
current uncertainties concerning the size of the
resource base for these energy supplies  can
directly affect the rate and magnitude of global
climate change.   Policy options encouraging
greater use of these fuels in  conjunction with
higher  resource  estimates  would  have  a
substantially different impact.

    '  High Oil Resources.  An increase in
global oil resources  to 25,000 EJ is more than
double the resource estimates assumed in the
RCW case.  These additional resources were
assumed to be available at the same economic
costs, such that the amount of oil available at
any given price was twice the amount assumed
in  the  RCW case.   This  increase  in oil
resources  had two  major impacts:   (1)  the
amount of synthetic production of liquid fuels
from   coal   declined   substantially   since
conventional oil  supplies were available at a
competitive price to  meet this demand; and (2)
total demand for energy, mainly oil, increased
as.  consumers responded to  the  increased
availability of oil supplies at the same price
(since twice the amount of oil was available at
a price equal to that in the RCW case).  The
net effect of these impacts is a small increase
in total primary energy demand in the first
half of the  next  century (a  2% increase by
2050) followed by a small decrease, a major
shift from coal (primarily for synthetic fuel
production)  to oil, and a  decrease in  the
portion of total  primary energy supplied by
non-fossil resources  since oil is more plentiful
and competitive; for example, non-fossil fuels
supply about 22% of  all  energy  by  2050
compared with 23% in the  RCW case  (see
Figure C-5).  The net effect of these factors is
a decrease in CO2 emissions of 0.2 Pg C by
2050 and  1.2 Pg C  by 2100.  The decline in
coal production also lowered methane (CH4)
emissions  since the amount of CH4 emitted
during coal  mining decreased substantially
(e.g.,  by  2100  CH4  emissions  from  fuel
production declined from about 390 Tg in the
RCW case to 260 Tg), resulting in a modest
decline of about 0.2°C in realized warming by
2100 compared with the RCW case warming
(assuming 2.0-4.0°C climate sensitivities).3

      High Natural Gas Resources.  For the
high natural gas resource case, natural gas
resources were increased from about 10,000 EJ
to 27,000 EJ. As in the high oil resource case,
higher natural gas resource estimates result in
two major impacts: (1) an increase  in demand
for energy, particularly for gas, since natural
gas is more  plentiful  compared  with  the
amount available in the RCW case; and (2) a
decline in the conversion of coal to synthetic
gas, since natural gas supplies are available to
meet the demand.
      Overall, by the end of the 21st century
the  amount of  primary energy  consumed
changes very little from the RCW case. In the
near term, energy demand increases slightly
compared with the RCW case since natural gas
is more plentiful (e.g., by 2025 energy demand
is about 3% higher compared with the RCW
case;  see  Figure C-6).   However,  the  total
amount of energy required in the long run is
less  because a  greater  portion of end-use
energy demand  is met   with  natural   gas
rather than with synthetic gas from coal.  This
increase  in   conventional    natural   gas
consumption reduces the total primary energy
required to satisfy demand because the decline
in synthetic fuel demand from the RCW case
reduces the amount of  energy required for
synthetic fuel conversion, although this impact
is small: by 2100 primary energy demand is
lower by about 1%.


      The amount  of natural gas consumed
does  increase  significantly; for example,  in
2050 natural gas consumption increases, to 210
EJ compared with 100 EJ in the RCW case.
However, the increased availability of natural
gas also reduces the portion of energy supplied
by non-fossil fuels; for example, by 2050 non-
fossil energy sources supply about 20% of total
demand compared with 23% in the RCW case.
The net impact on CO2 emissions due to these
factors is quite small:  a decline of 0.2 Pg by
2050 and  1.1 Pg by 2100. The impact on
realized and equilibrium wanning is negligible
(less than 0.1°C).
                                           C-14

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                                       Appendix C: Sensitivity Analyses
                         FIGURE C-5


           IMPACT OF HIGHER OIL RESOURCES ON

              TOTAL PRIMARY ENERGY SUPPLY


                  Rapidly Changing World
1500
1250
                                                     Biomass

                                                     Solar

                                                     Nuclear
                                                     Hydro
                                                     Gas
                                                     Oil
                                                     Coal
                     High Oil Resources
                                 Biomass
                                 Solar

                                 Nuclear

                                 Hydro
                                 Gas
                                                     Coal
    1985  2000
2025      2050

      Year
2075
2100
                           C-15

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Policy Options for Stabilizing Global Climate
  1500
                           FIGURE C-6



      IMPACT OF HIGHER NATURAL GAS RESOURCES ON


                TOTAL PRIMARY ENERGY SUPPLY



                    Rapidly Changing World
  1500  <—
  1250
0 1000
>
\
M

•2  750
uj  500




   250
                   High Natural Gas Resources
                                                       Biomass

                                                       Solar
      1985   2000
2025      2050

      Year
2075
                                                       Coal
                                                       Biomass

                                                       Solar
2100
                             C-16

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                                                           Appendix C:  Sensitivity Analyses
Availability of Methanol-Fueled Vehicles

      The  transportation sector throughout
the world is heavily dependent on petroleum-
based fuels.  This dependence, particularly on
gasoline and diesel fuel, produces substantial
quantities of greenhouse gases (see CHAPTER
IV).   A  variety  of  non-petroleum-based
alternatives are under development, including
the  use  of  methanol.   There  are  many
potential advantages to using methanol as a
transportation fuel  rather  than  gasoline;
according  to  recent   research,   advanced
methanol-fueled  vehicles could be 20-40%
more energy efficient, emit much lower levels
of CO, and reduce non-methane hydrocarbon
(NMHC) reactivity up  to 95% (Gray, 1987).
Methanol's  potential  to  reduce  NMHC
reactivity could reduce levels of urban ozone,
which would improve  ambient air quality in
urban areas. These reductions could be on the
order of about 5-20%  of peak ozone levels
(DeLuchi et al., 1988). However, it  is not
clear  how reductions in urban ozone levels
may  translate  to  reductions in  average
tropospheric ozone and, therefore, changes in
radiative forcing.  Current understanding of
these atmospheric processes attributes urban
ozone changes primarily to NMHC and NOX
flux, while tropospheric ozone changes depend
primarily  on  (in   descending  order  of
importance) CH4, CO, NOX flux, and NMHC
flux (Prather, 1989).   Interactions between
urban  air   quality  and  the  rest  of the
troposphere cannot be evaluated  with the
aggregate model used here.

      Since  the ability  of methanol to affect
tropospheric ozone levels cannot be reliably
estimated,  we  cannot  reflect all   of the
potential advantages of using methanol as a
transportation fuel.   It is useful  to  note,
however,  that  in  addition  to  reducing
emissions of CO and  other gases, methanol
can  be  produced  from  different  types  of
feedstocks,  such  as  natural  gas,  coal,  or
biomass.  When biomass is the feedstock, the
carbon emitted during the combustion process
is  recycled  from the  environment  as the
biomass is grown.  As  a result, the net CO2
emissions are zero when  biomass is  used.
Greenhouse gas emissions from  methanol,
however, can  be greater  than those  from
gasoline  if  coal is used  as the feedstock
because additional emissions will be generated
during  the  methanol  production  process.
According   to   one   analysis,   methanol
production from coal would generate about
twice the amount of CO2-equivalent emissions
(based on their radiative effect) compared to
gasoline from crude oil,  while methanol from
natural gas  would only  be  slightly  better
(about  3%)  than  petroleum-based  fuels
(DeLuchi et  al.,  1988).   From  a  global
warming perspective,  DeLuchi et al.  (1988)
concluded that only biomass-derived methanol
would  substantially reduce  the amount of
radiative forcing  from  transportation fuels,
although as  mentioned above,  this argument
does not incorporate any potential benefits
from reductions in urban ozone levels.

ATMOSPHERIC COMPOSITION:
COMPARISON OF MODEL RESULTS TO
ESTIMATES OF HISTORICAL
CONCENTRATIONS


      The atmospheric composition model was
applied to estimates Of historical emissions of
trace  gases  and  the results  compared to
historical data on atmospheric composition.
This exercise  provides  insight  on how the
model  performed under  conditions  much
different from  the reference year, 1985,  and
provided  one  mechanism to  validate  the
model. The exercise included the development
of a single scenario of historical emissions of
trace gases and application of the model using
different assumptions on  climate sensitivity
and chemistry parameters in the model.


      The scenario of historical emissions of
trace gases is based on  estimates of natural
sources from the  Atmospheric Stabilization
Framework described in Chapter VI, estimates
from a study by Darmstadter et al. (1987) on
historical  emissions   from   various
anthropogenic   sources,  and  estimates  of
historical CO2 emissions from Rotty (1987)
and Houghton (1988).  For natural emission
sources, historical emissions were assumed to
be constant  from 1870 to  1985 at the levels
assumed in the scenarios described in Chapter
VI. The exception is emissions of CH4 from
wetlands, which were assumed to be larger in
1870 by 50% and to decline to current levels
due to  destruction of wetlands.  The estimates
of historical emissions of CFCs and halons
were  taken  from U.S.  EPA's  Regulatory
                                           C-17

-------
 Policy Options for Stabilizing Global Climate
 Impact  Analysis  on  Stratospheric  Ozone
 Protection (U.S. EPA, 1988).

       The alternative  scenarios of historical
 atmospheric composition and global warming
 reflect a range of assumptions concerning the
 climate sensitivity and the first- and second-
 order relationships  assumed in  the  model.
 Figure C-7 illustrates the increase in realized
 warming projected from 1840 to  1985, which
 ranges from 0.4°C to 0.8°C based on a range of
 climate sensitivities  (from 1.5  to 5.5°C for
 doubled CO2).  These results  compare well
 with results  from  Wigley et  al. (1986), who
 estimated a global temperature increase of 0.3-
 0.7°C in the last century, and  Hansen et al.
 (1988), who estimated a global temperature
 increase of 0.4-0.8°C during the same  period.
 The model produced estimates of atmospheric
 concentrations of  CO2, CH4, N2O, CO, and
 CFC-12   within   1.5%  and   estimates  of
 concentrations of CFC-11  within 3.5%  of
 observed  values in  1985.  In  addition,  the
 pattern   of   estimated   atmospheric
 concentrations over time conformed well with
 historical measurements for CO2, N2O, and
 CH4.  Estimates of concentrations of some
. gases  such  as  HCFC-22  varied from  the
 historical measurements to a greater  extent,
 which reflects their more recent introduction
 and   rapid   growth   in    atmospheric
 concentrations.  Table C-2 summarizes  the
 results for the long-lived gases.

       For CO2, the atmospheric concentration
 over time matched  the Mauna Loa and Ice
 Core measurements by design through  the use
 of the unknown  sink in the model  (see
 Unknown  Sink  in  Carbon Cycle).    The
 unknown sink is zero through 1940 and then
 slowly rises  to 1.9  Pg C  per year by 1985,
 which represents  about  one-third  of  the
 estimated anthropogenic emissions.

       The estimates of CH4 concentrations
 match atmospheric and ice core measurements
 well, especially given the uncertainties in the
 emissions   estimates  and  the   historical
 measurements.  The model shows somewhat
 higher than expected growth in the late 19th
 century,  which may  reflect the uncertainties
 surrounding  the    scenario    of   historical
 emissions.  Using  the  reference assumptions,
 the   model   achieves   an   atmospheric
 concentration of 1671  ppb in 1985 compared
to the observed value of 1675 ppb.  The CH4
concentrations  vary  considerably  in  the
sensitivity analyses and range from 1650 ppb
to  1750   ppb  for  alternative   chemistry
parameters.

      Of  the  three  dominant  greenhouse
gases, the  estimates of N2O concentrations
vary the most from historical measurements.
The model predicts concentrations of 314 ppb
in 1985 compared to 308-310 ppb cited in the
literature.  From  1979 to  1986,  the  model
estimates  growth  in N2O concentrations  of
310-314 ppb compared to measurement data
that suggests growth of 303  to 310 ppb. One
of the possible explanations  of these results is
that the relative share of emissions of N2O
from anthropogenic sources  is  larger than
estimated   in  the   model.     A   larger
anthropogenic source  combined with lower
natural emissions or a shorter atmospheric life
would  be  needed  to  reduce   the  overall
concentrations  and  obtain the growth  in.
concentrations seen from 1979 to 1986. These
results   suggest   that   the  model'  may
underestimate    future   atmospheric
concentrations of N2O.

     The model "predicts" very little deviation
from current  levels  for the  short-lived gases,
including OH, O3, and CO. The results for
levels in 1870 include higher levels of OH by
14-26%, lower levels of tropospheric O3 by 19-
29%,   lower   concentrations  of  CO   by
approximately 50%, and  increased levels  of
upper stratospheric ozone by 4.5%.
ASSUMPTIONS ABOUT TRACE-GAS
SOURCES AND STRENGTHS

      Among the various greenhouse gases
there is some uncertainty over the quantity of
emissions  that can be attributed to specific
sources and the ability of these gases to modify
the atmosphere.  The most critical of these
uncertainties are examined below.

Methane Sources

      The available evidence on CH4 indicates
that annual production ranges from 400-640
Tg of methane (based on  known sources and
sinks, its  atmospheric lifetime, and current
atmospheric  concentrations).  Within  this
                                           C-18

-------
                                            Appendix C: Sensitivity Analyses
   0.9  h
   0.8  -
   0.7  -
   0.6  h
e
o
u>
o
   0.4
   0.3  -
   0.2
   0.1
                             FIGURE C-7




              REALIZED WARMING THROUGH 1985


                  (Based on 1.5-5.5 Degree Sensitivity)
      1840    1865
1890     1915    1940    1965   1985


         Year
                               e-19

-------
Policy Options for Stabilizing Global Climate
                                      TABLE C-2



                   Comparison of Model Results to Concentrations in 1986
Trace Gas (units)
CO2 (ppm)
N20(ppb)
CH4 (ppb)a
CFC-11 (ppt)
CFC-12 (ppt)
HCFC-22 (ppt)
CC14 (ppt)b
CH3CC13 (ppt)
Halon 1211 (ppt)
a 1987 value.
b 1982 value.
Model
Model Results Growth Rates
346
314
1650-1750
212-222
391
37
70
186
0.4


0.4%
0.27%
1%
4%
4%
14%
0.6%
12%
100%


Atmospheric Observed
Measurements Growth Rates
346
310
1675
226
392
100
121
125
2


0.4%
0.2-0.3%
1%
4%
4%
7%
1.3%
6%
>10%


                                         C-20

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                                                            Appendix C:  Sensitivity Analyses
budget, however, there is  much dispute over
the size of individual sources.  For example,
research indicates that current CH4 emissions
from   rice  paddies   could  be  60-170  Tg;
similarly,  estimated emissions from  biomass
burning range from 50-100 Tg (Cicerone and
Oremland, 1988).

      To account for these uncertainties, the
initial CH4 budget was varied to construct two
cases:  (1) a high anthropogenic impact case,
where the starting methane budget was biased
toward  anthropogenic sources  by assuming
that anthropogenic  activities such  as  fuel
production  and  landfilling  caused  higher
emission levels  than  assumed  in the  RCW
case,  while lower emission  estimates  were
assumed  from  natural  processes  such  as
oceans, wetlands, wildfires, and wild ruminants;
and (2) a low anthropogenic impact case, by
assuming lower emissions from anthropogenic
activities  such as fuel production, enteric
fermentation,  and  rice   cultivation,   with
corresponding emission increases from natural
processes  such as oceans and wetlands.   The
specific emission assumptions for the starting
budget are summarized in  Table C-3.

      The alternative starting budgets in Table
C-3 result in different growth paths for  CH4,
since  emissions  from anthropogenic sources
increase by  different amounts  over   time.
These   differences  alter   the   atmospheric
concentration  of  CH4:     by  2100  the
atmospheric concentration is about 3600-3800
ppb in  the Low  Impact case and 5450-5700
ppb in the High Impact case (compared with
4300-4500 ppb in the RCW case and assuming
2°-4°C climate sensitivities).   The  increase
(decrease)  in CH4 also  increases  (decreases)
the amount  of  tropospheric ozone.    The
impact on realized warming is summarized in
Figure C-8, which indicates a decline of 0.1-
0.2°C  by  2100   in  the  Low  Impact  case
compared with the RCW case and an increase
of 0.2-0.3°C by 2100 in the High Impact case.
The corresponding  effects  on equilibrium
warming by 2100 are a decline of 0.2-0.4°C in
the Low Impact case  and  an increase of 0.3-
0.6°C in the High Impact case  (based on 2°-
4°C climate sensitivities).
Nitrous Oxide Emissions From Fertilizer

      N2O is naturally produced in soils by
microbial processes during denitrification and
nitrification.  When nitrogen-based fertilizers
are applied, N2O emissions from the soil can
increase  as a result of the additional nitrogen
source.   The amount of fertilizer nitrogen
evolved  as  N2O  is  highly  variable   and
uncertain.    We  have  used  the  emission
estimates developed by Galbally (1985) in our
base cases:   0.5%  for  anhydrous  ammonia,
0.1%  for   ammonium  nitrate,  0.1%  for
ammonium salts, 0.5% for urea, and 0.05% for
nitrates.    An  N2O emission  pathway  not
included in Galbally's estimates is leaching
from the fields  into  the ground water  or
surface water because of fertilizer application.
Conrad et al. (1983) and Kaplan et al. (1978)
have  suggested  that the amount  of  N2O
evolved due  to leaching may be as large as
N2O   from  the   denitrification/nitrification
processes in the soil (i.e., 0.5-2.0%). Ronen et
al. (1988) have calculated that the N2O  flux
from these sources is  10-20% of the global
production  of N2O annually, which  is  an
estimate greater than 3% of nitrogen evolved
as N2O.  Alternative  assumptions on  N2O
emissions are explored below.

Anhydrous Ammonia

      One of the key uncertainties concerns
the  emission   coefficient  for  anhydrous
ammonia. A review of the scientific literature
on   measurements  of  N2O  emissions  by
fertilizer type indicates that the percentage of
anhydrous ammonia evolved  as N ranges from
0.05-6.84%, with most measurements ranging
from 0.5-2.0% (Eichner, 1988). The impact of
this uncertainty was evaluated by changing the
anhydrous ammonia coefficient by 1.5%.  This
change  increased the amount of N2O from
fertilizer applications by about 0.06-0.07 Tg of
N annually, which was too small to affect the
amount of global warming.

N2O Leaching From Fertilizer

      As discussed above, in the RCW case
N2O emissions from fertilizer were based on
                                            C-21

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Policy Options for Stabilizing Global Climate
                                      TABLE C-3



                 Low and High Anthropogenic Impact Budgets For Methane



                                (teragrams/year as of 1985)
Source of Methane
Fuel Production
Enteric Fermentation
Rice Cultivation
Landfills
Oceans
Wetlands
Biomass Burning - Anthropogenic
Biomass Burning — Natural
Wild Ruminants
Other Sources
TOTAL
Low Impact
50
70
60
30
45
' 150
53
2
44
7
511
RCW
60
75
109
30
15
115
53
2
44
7
511
High Impact
95
75
109
58
6
100
48
2
10
7
511
                                          C-22

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                                     Appendix C: Sensitivity Analyses
                       FIGURE C-8


            INCREASE IN REALIZED WARMING

        DUE TO CHANGES IN THE METHANE BUDGET
         (Degrees Celsius; Based on 3,0 Degree Sensitivity)
w
9
O
10
CD
4)
Q
    2  f
    1985  2000
                                                  High Methane
                                                  Low Methane
2025     2050

       Year
2075
2100
                          C-23

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Policy Options for Stabilizing Global Climate
estimates  by  Galbally  (1985)  with  a  2%
increase  in  these  estimates  to  allow  for
leaching.  The rate of emissions related to
leaching   is,  however,  highly  uncertain;
therefore, a no leaching case was analyzed by
decreasing the emission coefficients by two
percentage points (to remove  the impact of
the leaching assumed  in the base cases).  In
order to account for this change and  maintain
the N2O  budget at  its original level, N2O
emissions  from  wetlands   were  increased
correspondingly.  The consequent lower rate of
N2O from fertilizer resulted in a decrease in
emissions of about 1.0-2.0 Tg N annually.

      Atmospheric   N2O   concentrations
decrease about 25 ppb by 2100 compared with
the RCW case  (from 430  to  404  ppb; see
Figure  C-9).   While  N2O concentrations
decrease when  leaching is eliminated, the
impact on global wanning is not as certain. In
this case, global warming was slightly increased
(less than 0.001°C).  Specifically, lower N2O
levels in the stratosphere increase the amount
of stratospheric  ozone, which in turn allows
less ultraviolet (UV) radiation to penetrate to
lower elevations. The reduced UV  radiation
decreases the amount of  CFC  destruction,
which increases the contribution of  CFCs to
global warming.  None of these reactions are
very strong, since the change in N2O emissions
due to leaching does not have  a major effect
on atmospheric  concentrations, but  they are
sufficient  to  counteract the effect  of lower
N2O concentrations alone.

N2O Emissions From  Combustion

      During    the   combustion    process,
chemical  interactions downstream from the
combustion   chamber can lead   to  N2O
formation from nitrogen oxides.  The rate of
this  formation is highly uncertain,  although
recent evidence indicates that it is likely to be
fairly small.   In the RCW case these low
emission  coefficients  were  assumed  (see
CHAPTER II).  To ascertain  the impact of
higher emission  coefficients, N2O coefficients
from combustion were increased such  that
emissions from energy in 1985  were  2.2 Tg N
rather than 1.0 Tg N as obtained in the RCW
case.   The  higher  N2O  emission levels
increased atmospheric concentrations about 30
ppb  by 2100 (as shown in  Figure C-10);  the
resulting  impact  on  global  warming  was
negligible  (less  than  0.1°C)  for the same
reasons discussed above under leaching from
fertilizer.

UNCERTAINTIES IN THE GLOBAL
CARBON CYCLE

      The global carbon cycle, which regulates
the flow of carbon through the environment,
including  the atmosphere,  biosphere,  and
hydrosphere, was discussed in Chapters II and
III.  Uncertainties in the size of the various
sources  and  sinks  for  carbon  and  the
interactions  that govern the flow of carbon
increase the difficulty of estimating the impact
of anthropogenic activities on global climate.
In this section the major uncertainties in the
global carbon cycle are evaluated.  The first
part focuses on the impact of deforestation on
CO2 emissions. The second part discusses the
ability of the oceans to absorb CO2 and heat.
Currently, the oceans  are the dominant sink
for anthropogenic CO2 emissions, with the
mixed layer alone  containing  about  as much
carbon as the atmosphere.  The oceans' ability
to operate as  a net sink for carbon and heat is
an important  component of the global climate
system; any changes in  this absorption ability
could have profound effects on global climate
(see CHAPTER III).

Unknown Sink In Carbon Cycle

      Atmospheric CO2 concentrations have
changed historically because of an imbalance
between the sources and sinks for carbon.  If
the production of carbon exceeds the ability of
the various carbon sinks to absorb it, then the
atmospheric CO2 concentrations will increase
(and vice versa).  When analyzing the amount
of carbon produced from  various sources in
the past,  atmospheric scientists  have  been
unable to balance  the carbon cycle.   That is,
given current estimates of carbon sources, it
would   appear    that  atmospheric  CO2
concentrations would have to be higher than
currently measured, since all known  sinks do
not appear to be  able to absorb all of the
carbon  produced.   To  account for  this
imbalance, we have assumed the  existence of
an   "unknown  sink"   that   absorbs   the
unaccounted-for carbon.   The size  of  this
unknown  sink  depends  on  the assumed
magnitude of known sources and sinks - by
definition,  the  unknown  sink  is   simply:
                                           C-24

-------
                                       Appendix C: Sensitivity Analyses
                         FIGURE C-9



    CHANGE IN ATMOSPHERIC CONCENTRATION OF N2O


                     DUE TO LEACHING

              (Based on 3.0 Degree Celsius Sensitivity)
   450
   400 -
c  350
_o
EE
ffl
i_
o
Q.
CO
a
0.
   300
   250 -
   200
                                                    RCW
                                                    Leaching
      1985  2000
2025
  2050

Year
2075
2100
                            C-25

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Policy Options for Stabilizing Global Climate
                          FIGURE €-10

      CHANGE IN ATMOSPHERIC CONCENTRATION OF N20
                      DUE TO COMBUSTION
               (Based on 3,0 Degree Celsius Sensitivity)
    500
    450
    400
 jo
 ffl
  a
  Q.
    350
    300
    250
    200
                                                     Combustion
                                                     RCW
       1985  2000
2025     2050
       Year
2075     2100
                             C-26

-------
                                                            Appendix C:  Sensitivity Analyses
sources  minus  sinks  minus   atmospheric
accumulation.

      For our base cases,  the  size  of the
unknown sink was  kept constant  at  1.6  Pg
annually, based on as calculated value (from
the  model)   for   1975-1985.     However,
alternative  assumptions are  plausible.   To
capture these  uncertainties, two sensitivities
were analyzed: (1) a high case, where the size
of the unknown sink increases at the same rate
as atmospheric CO2 levels compared with pre-
industrial  levels  (this increase might occur,
e.g., because the size of the unknown sink is
related  to  the   fertilization  of  terrestrial
ecosystems by  increasing CO2); and (2) a low
case,  where   the  size  decreases  to  zero
exponentially at 2%  per year (e.g., because the
process responsible for the unknown sink has
a limited capacity).

      When the  unknown sink is assumed to
increase in proportion to CO., concentrations
in the RCW  case,  the amount  of  carbon
absorbed by the unknown  sink  increases  to
11.9 Pg annually  by 2100. This rate of carbon
absorption  results  in  a  decline  in  CO2
concentrations relative to the RCW scenario,
which reduces realized warming by 0.1-0.2°C in
2050  and  0.5-0.7°C  in 2100;" equilibrium
warming is reduced in 2050 by 0.2-0.5 C and in
2100 by 0.7-1.5CC (based on 2.0-4.0°C climate
sensitivities).

      In  the  low case, that  is,  when  the
unknown sink decreases to zero, the estimated
impact on warming is significantly lower, since
the unknown sink was only 1.6 Pg annually to
start.   As a  result,  CO2  concentrations do
increase, but the increase in realized warming
is less than 0.1°C in 2050 and 0.1-0.2°C in 2100
(based on 2.0-4.0°C climate sensitivities; see
Figure C-ll).

Amount of CO2 From Deforestation

      Estimates of the amount of CO2 emitted
from deforestation activities vary because of
different   assumptions   on   the   rate  of
deforestation, the fate of the deforested lands,
and the amount of carbon contained in the
forest vegetation and soils.  In the  base cases
we used the lower carbon estimates  (i.e., lower
biomass estimates) given by Houghton (1988);
for 1980 the resulting net flux of carbon to the
atmosphere  was  about  0.4  Pg of  carbon.
Higher estimates of initial biomass have also
been analyzed by Houghton (1988); with these
estimates  the   nei  flux  of  carbon  to  the
atmosphere in 1980 would have been about 2.2
Pg.   These  higher  biomass  estimates  are
evaluated  here for the  three  deforestation
scenarios discussed in Chapter  VI.  The net
flux of carbon for each  of these scenarios is
presented in Figure C~12.


      In the RCW  case the  rate of  CO2
emissions from deforestation was based on an
exponential  decline in forest area  using the
lower biomass  assumptions.   If the  higher
biomass estimates are used, the total carbon
flux from deforestation from  1980 to 2100 is
281 Pg compared  with  118 Pg using the low
estimates of carbon stocks (Houghton, 1988).
Similarly,   in  the   population-based
deforestation scenario the total carbon flux to
the atmosphere from  1980 to 2100 is about
138 Pg using the lower biomass estimates and
324 Pg using the higher biomass estimates.  In
the   reforestation   scenario,  the   total
accumulation of carbon from  the atmosphere
was 38 Pg using the lower biomass estimates
and 59 Pg using the higher biomass estimates.


      Despite the substantial increase in the
amount of carbon from deforestation when the
higher biomass estimates are used  (e.g., by
2050 CO2 emissions from deforestation are 2.3
Pg compared with 1.0 Pg in the RCW with the
lower estimates), the resulting  atmospheric
concentration of CO2 is slightly lower  (see
Figure C-13 for the differences in the RCW
case, i.e., forest area declines exponentially).
This result is due to the larger size  of the
"unknown carbon sink" in our model when
higher deforestation  emissions  are  assumed
(see Unknown Sink In Carbon Cycle above).
In our analysis the increase in the size of the
unknown sink was sufficient to absorb some of
the additional carbon when the higher biomass
estimates are used, assuming  that the size of
the unknown sink  remains  constant at its
average 1975-1985 value (i.e., 2.6 Pg C  with
high biomass vs. 1.6 Pg C with low biomass).
The decrease in  CO2 concentrations decreased
realized wanning and equilibrium warming less
than 0.10C by 2100 compared with the RCW
case warming  (assuming 2.0-4.0°C  climate
sensitivities).
                                           C-27

-------
Policy Options for Stabilizing Global Climate
                            FIGURE C-ll



            IMPACT ON REALIZED WARMING DUE TO


                     SIZE OF UNKNOWN SINK


                   (Based on 3.0 Degree Sensitivity)
   .2
   co
   "3
   o
   (0
   a>
   a>

   D)
   O
   a
                                                       2% Decline

                                                       RCW
                                                       Proportional

                                                        Increase
       1985  2000
2025
  2050

Year
2075
2100
                               C-28

-------
                                     Appendix C: Sensitivity Analyses
                      FIGURE C-12
CO 2 FROM DEFORESTATION ASSUMING HIGH BIOMASS


                (Petagrams of Carbon/Year)
 4  -
                              /   i
sew/

   /
   /
  /
  /
                       RCW
                    Stabilizing

                    Policy Scenarios
  1950     1980     2010     2040


                         Year
                2070
2100
                         C-29

-------
Policy Options for Stabilizing Global Climate
                          FIGURE C-13

          IMPACT OF HIGH BIOMASS ASSUMPTIONS ON
            ATMOSPHERIC CONCENTRATIONS OF C02
                (Based on 3.0 Degree Celsius Sensitivity)
    1000
     900 -
     800 -
 c
 o
 =   700
 GO
 
-------
                                                           Appendix C: Sensitivity Analyses
Alternative CO2 Models of Ocean Chemistry
and Circulation

      In  the RCW case ocean chemistry was
represented  using a  diffusion model of the
ocean (the Modified GISS model) based on
the model described by Hansen et al. (1988).
Several  other  approaches have  also  been
developed and  adopted  for  the  U.S.  EPA
framework by W. Emmanuel  and B. Moore.
These include:

•     Box-Diffusion  Model   introduced  by
Oeschger et al. (1975), which represents the
turnover  of carbon  below 75 meters  as  a
purely diffusive  process.

•     12-Compartment  Regional  Model by
Bolin et al. (1983), which divides the Atlantic
and  Pacific-Indian   Oceans  into  surface-,
intermediate-,   deep-,   and   bottom-water
compartments  and  divides the  Arctic  and
Antarctic Oceans into surface- and deep-water
compartments.

•    Advective-Diffusive   Model   by
Bjorkstrom (1979), which divides the surface
ocean into  cold  and  warm  compartments;
water downwells directly from the cold surface
compartment into  intermediate  and  deep
layers.

•     Outcrop-Diffusion   Model   by
Siegenthaler  (1983),  which   allows  direct
ventilation of  the  intermediate  and  deep
oceans at  high latitudes by incorporating
outcrops   connecting  all  sublayers  to  the
atmosphere.

      Because each of these  models uses a
different   approach    to  evaluate   ocean
chemistry, the resulting impact on atmospheric
CO2 concentrations  could vary  from  one
approach  to the  next.   To  determine how
comparable these models were, the RCW case
was evaluated using each model in turn.

     The   estimates   of    future   CO2
concentrations   from   each   model   are
summarized in  Figure  C-14a.  These results
indicate that the Modified GISS model tends
to   project   higher   atmospheric   CO2
concentrations  than  the other models; for
example,  by  2100. CO2 concentrations are
about  3%  higher   than   concentrations
estimated by Bolin et al. or Bjorkstrom, about
5% higher that those estimated by Oeschger et
al.,  and  about 23%  higher   than  those
estimated  by Siegenthaler.  There  are  two
basic reasons for these differences:  (1)  The
Modified  GISS model,   unlike the  other
models, incorporates  temperature  feedback
that alters ocean carbonate chemistry; that is,
as the mixed layer of the oceans warms due to
atmospheric warming,  the  amount of carbon
that can be absorbed by the oceans decreases;
and  (2) The Modified GISS model does not
incorporate any heat or CO2 transfer between
the thermocline and the deep  ocean (below
1,000 meters); to the  extent heat or CO2 is
transported to the  ocean depths in the long
run, the Modified GISS model understates the
oceans' absorption capacity.

      Siegenthaler's Outcrop-Diffusion Model
estimates lower CO2 concentrations than any
of the other models. This result is anticipated
because the  Outcrop-Diffusion Model allows
CO2 to be absorbed from  the atmosphere to
the deep layers rather than diffuse through the
intervening  layers,  so that,  in  this  model,
carbon is absorbed more quickly in the oceans
than in the other models. By 2100 equilibrium
warming using Siegenthaler's model  is  about
1°C lower than  the RCW case (see Figure C-
14b  for  warming  estimates  from  all  five
models).

ASSUMPTIONS ABOUT CLIMATE
SENSITIVITY AND TIMING

Sensitivity of the Climate System

      A general benchmark for comparing
atmospheric models is their response to a
doubling of  CO2 concentrations (2xCO2; see
CHAPTER HI).  Put simply, this benchmark
describes  how  much  warming would  be
expected once  the   atmosphere stabilizes
following   a  twofold  increase  in  CO2
concentrations.  In our analyses we have used
the range  from 2.0-4.0°C.  As  discussed in
Chapter III, there is a great deal of uncertainty
about  the  strength  of  internal  climate
feedbacks, and,  in  some  cases, whether a
feedback will be positive or negative.  If cloud
and  surface  albedo changes  produce large
positive feedbacks,  as  suggested by  some
analyses, the climate sensitivity could be 5.5°C
or greater.  On  the other hand, these feed-
                                           C-31

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Policy Options for Stabilizing Global Climate
                           FIGURE C-14
          COMPARISON OF DIFFERENT OCEAN MODELS
     1000
   o
900  -



800  -



700
   o

   •  600
   a
   o.
      500



      400



      300
    "5
    "5
    o
    M
    o>
    »
    Q
                          Concentrations
                                  Bjorkstrom

                                  Bolln
                Slegenthaler
                              ROW

                              Oeschger
                 Impact on Equilibrium Warming
                                                     RCW

                                                     Oeschger
         1985 2000
2025     2050

       Year
                                   2075
2100
                              C-32

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                                                            Appendix C:  Sensitivity Analyses
backs could  be weak and  cloud  feedbacks
could be negative,  resulting  in a  climate
sensitivity as low as 1.5°C. For the sensitivity
analysis,  therefore, we have evaluated  the
extent of global warming using 1.5 and 5.5°C
as lower and upper bounds, respectively. The
impact  of these  assumptions   on  realized
warming is summarized in Figure C-15 for the
RCW and SCW cases.  In the RCW case, the
range of  realized  warming for  a  1.5-5.5°C
climate sensitivity would be 1.6-3.5°C by 2050
and 3.1-7.0°C by 2100, compared  with a range
of 2.0-3.0°C by 2050 and 3.8-6.0°C by 2100
when the climate sensitivity is bounded by 2.0-
4.0°C.     The   corresponding   values  for
equilibrium warming for a 1.5-5.5°C climate
sensitivity are 2.2-7.9°C by 2050 and 3.8-13.9°C
by 2100, compared with 2.9-5.8°C by 2050 and
5.1-10.10C by 2100  for  a  2.0-4.0°C climate
sensitivity.  In  the SCW case, the range of
realized  warming  for  a 1.5-5.5°C  climate
sensitivity would be 1.4-3.1°C by 2050 and 2.1-
5.0°C by 2100, compared with a range of 1.7-
2.6°C by 2050 and 2.6-4.2°C by 2100 when the
range of climate sensitivity is 2.0-4.0°C.  The
corresponding values for equilibrium warming
for a 1.5-5.5°C climate sensitivity are 1.8-6.5°C
by 2050 and 2.5-9.0°C by 2100, compared with
2.3-4.7°C by 2050 and 3.3-6.6°C by 2100 for a
2.0-4.0°C climate sensitivity.

Rate of Heat Diffusion

      CO2 and heat  are currently transferred
from the atmosphere to the oceans and within
the ocean itself as a result of many complex
chemical and physical interactions.  One of
these interactions is the transfer of heat from
the mixed layer to the thermocline, thereby
delaying   global   warming.     Additionally,
changes  in   ocean  mixing  and circulation
patterns  as a result  of climate change could
alter the capacity of the oceans to absorb heat
(see BIOGEOCHEMICAL FEEDBACKS below
for further discussion). The rate at which heat
is absorbed only  affects  the rate of realized
warming, not the rate of equilibrium warming,
because  the  oceans  cannot  absorb  heat
indefinitely.

      In our model the rate at which mixing
occurs  between  the mixed layer  and  the
thermocline is  parameterized with an eddy-
diffusion coefficient (see CHAPTER HI). The
value of the  eddy-diffusion coefficient in the
base cases was  assumed  to  be 0.55 x 10"4
m2/sec.    For  purposes  of  this  sensitivity
analysis alternative values of 2 x 10"5 and 2 x
10"4 have been evaluated.
      As shown in Figure C-16 the rate at
which the oceans absorb heat can  noticeably
affect the amount of realized warming by 2100.
If the rate of heat absorption is greater than
that assumed  in the  base  cases (i.e., if the
eddy-diffusion coefficient is 2 x 10"4 m2/sec),
realized warming by 2100 would be 0.5-1.2°C
less than in the RCW case (assuming 2.0-4.0°C
climate sensitivities).  For  the smaller eddy-
diffusion coefficient of 2 x 10"5 m2/sec, realized
warming by 2100 would be 0.3-0.9°C higher.

ASSUMPTIONS ABOUT ATMOSPHERIC
CHEMISTRY: A COMPARISON OF
MODELS

      As discussed in Chapters II and III, the
chemistry  of the future troposphere is one of
the  uncertainties  in  the  prediction  of
atmospheric  composition.     The principal
factors  contributing  to  this uncertainty  are:
(1) the complexity and tremendous natural
variability of  chemistry in the troposphere,
especially regarding oxidant formation; (2) the
range  of  interactions between tropospheric
chemistry  and radiation perturbed  by climate
change  and  changes    in   stratospheric
composition; and (3) the range of uncertainties
in future  emissions of CH4, CO,  NOX,  and
non-methane  hydrocarbons (NMHC).   This
section focuses on the first two  aspects of
uncertainty in atmospheric  composition.

      Recognizing   the    uncertainty   in
tropospheric chemistry, U.S. EPA sponsored a
workshop on atmospheric composition  to
discuss recent  modelling  efforts  among
members   of  the   atmospheric  sciences
community and to construct a parameterized
atmospheric  chemistry model  that  would
incorporate the latest scientific findings. The
end result was  the  Assessment  Model for
Atmospheric  Composition  (AMAC),   the
model used to obtain the findings discussed in
this report. AMAC was developed  by Prather
of NASA/GISS as a result of the  workshop,
which  was held in January  1988 (see Prather,
1989). To obtain insight into the uncertainties
made by the AMAC and to  ensure results that
are comparable  to   current,  more detailed
                                            C-33

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Policy Options for Stabilizing Global Climate
                              FIGURE C-15
  7 -
                IMPACT OF CLIMATE SENSITIVITY ON


                        REALIZED WARMING


                   (Based on 1.5 - 5.5 Degree Sensitivity)
        Slowly Changing World
 1985  2000   2025   2050   2075   2100
Rapidly Changing World
                                    1985  2000   2025   2050   2075   2100
                                                                   5.5'
                                                                   4.0'
                                                                      c
                                                                      •
                                                                      ta
                                                                   2.0'
                                                                   1.5*
                                 C-34

-------
                                      Appendix C:  Sensitivity Analyses
                       FIGURE C-16




            INCREASE IN REALIZED WARMING


         DUE TO RATE OF OCEAN HEAT UPTAKE


               (Based on 3.0 Degree Sensitivity)
    6
w

"35
"5
O
«   o
O   3
O

O)
O
o
                                                2x10
                                              -, RCW
                                                2x10
                                                     -4

     1985 2000
2025     2050

       Year
2075
2100
                          C-35

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 Policy Options for Stabilizing Global Climate
 modeling efforts, a set of common scenarios of
 CH4> CO, and NOX emissions were analyzed in
 the AMAC, as well as in two current research
 models: a 2-D tropospheric chemistry model
 developed by Isaksen (Isaksen and Hov, 1987);
 and a multi-box photochemical model of the
 global  troposphere  developed by Thompson
 and co-workers at NASA/Goddard (Thompson
 et al., 1989).

 Model  Descriptions

 Assessment Model for Atmospheric Composition

      The  focus of  interest in tropospheric
 composition is on O3, CH4, and OH, because
  the two former gases  are key greenhouse
 absorbers  and OH  (together  with ozone)
 determines  the oxidizing  capacity  of  the
 atmosphere and the abundance of many gases
 such as methane,  carbon monoxide, methyl
 chloroform, and HCFC-22 (CHF2C1).

      For the simulation of the troposphere in
 this  model,  the  Northern  and  Southern
 Hemispheres   (NH  &  SH)  are  treated
 separately because significant asymmetries are
 observed in many of the important shorter-
 lived gases, such as CO  and NOX.  These
 species play a major role in the budgets for
- CH4, O3, and OH in each hemisphere.

       In the AMAC, tropospheric OH can be
 treated as a steady-state variable as it responds
 immediately to the annual average values of
 the trace gases. To derive perturbations to
 OH, a  non-linear system is solved equating a
 "production" term to a "loss" term. OH losses
 are partitioned  among  the predicted  gases
 (CH4, CO), the specified fluxes (NMHC), and
 self-reactions (OH).  The production side of
 the equation  includes a positive response to
 increases in UV radiation (i.e., loss in column
 ozone) and in tropospheric H2O, O3  and NOX
 fluxes.  Coefficients for variations in either the
 production or loss  terms with  respect  to
 column O3, tropospheric water vapor, trop-O3,
 CO, CH4, and fluxes of both NMHCs and NOX
 are based on results from 1-D and 2-D models
 (Liu et al., 1987; Thompson and Cicerone,
 1986; Isaksen  and Hov, 1987; Isaksen et al.,
 1988).    Major sources  of  uncertainty  in
 calculating  OH are the  spatial  averaging for
 this highly variable constituent   and  the
nonlinearity  in  perturbation  coefficients,
especially with respect to NOX distribution.

      Perturbations  to  tropospheric ozone
affect both tropospheric  temperatures and the
long-lived source gases controlled by OH.  A
significant  fraction  of  tropospheric ozone
originates in the stratosphere and is destroyed
by surface deposition; it is sufficiently short-
lived  (a  few   months)  that  the  AMAC
calculates ozone perturbations separately for
each  hemisphere.   Changes in tropospheric
ozone are associated with perturbations to the
total  ozone  column, and to tropospheric
chemical reactions,  which are  evaluated with
sensitivity   coefficients,  dln(O3)/dln(X),
ascribed to the precursor gases (Column -O3,
0.8; CH4, 0.2; CO, O.I; NOX flux, O.I; NMHC
flux,  O.I).   The coefficients  are based on
detailed  photochemical  models  for typical
tropospheric  air parcels  (Liu et al.,  1987;
Thompson et al., 1989), but their uncertainties
are large, by approximately a factor of 2.  Also,.
the efficiency of O3 production varies widely
with the NOX levels (Liu  et al., 1987), which in
turn  cannot  be  adequately  characterized
throughout the entire troposphere  due to their
large  dynamic  range.    A similar  concern
applies to the simplified  treatment  of non-
methane  hydrocarbons.

Isaksen Model

      The Isaksen model  is a 2-D transport
model that  calculates absolute  concentrations
for O3 and OH (and several dozen other trace
chemical constituents in the troposphere) as
functions of altitude and  latitude, as emissions
are varied over  time (Isaksen  and  Hov, 1987;
Isaksen et al., 1988). Unlike the AMAC, thisx
model  resolves  latitudinal   and   altitude
distributions,  and   emission  changes   are
introduced  with latitudinal  discrimination.
The transport of longer-lived constituents can
locate key areas of tropospheric  ozone and
OH change that the AMAC will miss; because
a 2-D model resolves altitude, the effects of
high-altitude aircraft emissions on NOX and
ozone or cloud perturbations to radiation
fields, for example,  can be explored.   The
Isaksen model differs from the AMAC in that
the  troposphere is  not  coupled  to   the
stratosphere, so  that the impact of changing
climate  or  perturbations  on  stratospheric
                                            C-3<6

-------
                                                            Appendix C: Sensitivity Analyses
ozone are.not included. Methane flux changes
are included in annual updates of the model.

Thompson et al. (1989) Model

      The Thompson model couples the result
of 1-D model calculations of the time  history
for eight chemically coherent global regions,
which are then averaged to estimate net global
changes.    A  steady-state  method is used:
emissions  are  specified  in  simulations  to
represent conditions at 5-year intervals.  This
is  somewhat inadequate for lifetime changes,
although test runs show  that this introduces
discrepancies in calculated mixing ratios of at
most 15%.

      The description of chemically coherent
regions offers insight into regional variability,
a feature lacking in the version of the Isaksen
model  used here, which does not have  the
longitudinal   variation   needed   to   treat
emissions that are restricted to the source area
but can have extensive effects on ozone and
OH. Like the Isaksen model, the Thompson
model  includes  a  more complete   set  of
chemical constituents than  does the AMAC
and can identify other effects and interactions
of climate perturbation.   For  example,  the
oxidants  that  contribute  to sulfuric  acid
formation in clouds and rain (HO2 and  H2O2)
are very  sensitive to changes in stratospheric
ozone and tropospheric water vapor.

Results from the Common Scenarios

      It  is not easy  to compare the models
because  the  structure,   input,  and derived
quantities  from  the three  models are not
treated comparably.   Nevertheless, insights
into  uncertainties   can  be  obtained   by
comparing selected results from each  model.
U.S.  EPA supplied  eight  scenarios   of
alternative estimates of CH4, CO, and NOX for
evaluation in each model. In this section one
of these scenarios  is discussed (U.S. EPA
Scenario #2),  which assumes low  CH4, low
CO, and  high NOX growth in sources, a rapid
growth  scenario  for  CO2  and N2O from
combustion, and a CFC  and halon scenario
consistent with the Montreal Protocol.  Table
C-4 summarizes the emission estimates  for the
U.S. EPA scenarios  and compares them  to
estimates from the RCW and SCW scenarios.
The RCW and SCW cases could not  be
explicitly included for this model comparison
because  the  development  of these  cases
occurred  simultaneously  with  the  model
comparison. Table C-5 summarizes the results
for all eight scenarios.

      The  U.S. EPA #2 emission estimates
are in the  same range as those of the other
two  cases except for CO emissions.  These
estimates are much lower than both the RCW
and  SCW  cases and  are  similar  to  the
Stabilizing   Policy  cases  due  to  stringent
control  assumptions on  transport  vehicle
emissions.  For the other emissions, the CO2
emission estimates   in  U.S. EPA #2  fall
between the RCW and SCW  cases  for most of
the  time   periods,  approaching  the RCW
estimates  by  2100.    The  CH4   and NOX
estimates are similar to those for the SCW
case, except that NOX estimates after 2050 fall
between the RCW and SCW estimates.

      The AMAC's troposphere is basically a
parameterized  2-box  model:  it reports mean
tropospheric values   (ppb)  for  CH4,  and
separate perturbations (% change)  to OH and
O3 in each hemisphere.   For  the  global
average perturbation  to OH and O3, Northern
and Southern Hemisphere results are averaged
with  equal weight.    In addition  to  the
perturbed  species  discussed  here with  the
tropospheric chemical models, the  AMAC
calculated other significant perturbations, such
as a 12% decrease in  column ozone, a 2K rise
in mean tropospheric temperature, along with
a 10% increase in tropospheric water vapor.
These  perturbations  have  an  impact  on
tropospheric  OH,   O3,  CO,  and   CH4.
Additionally, unlike  the other two models,
which provide  point estimates, the  AMAC
produces a range of trace-gas scenarios  in
response to specified uncertainties in  the
model coefficients.

      The  Thompson  model averages over
eight  "chemically coherent  regions."   This
approach is probably adequate for  short-lived
species  such   as  OH,  and  possibly   for
tropospheric O3.    However, it   makes  it
difficult to  interpret  CH4 calculations, which
predict different CH4 concentrations among
the boxes,  when in fact the  long  lifetime of
CH4 ensures that it is well mixed throughout
the troposphere.   The methane  results  in
Table C-5 have been  averaged over the eight
                                           C-37

-------
Policy Options lor Stabilizing (.'lobsil Climate
                                          TABLE C-4

                          Comparison of Emission Estimates For U.S. EPA,
                                      RCW, and SCW cases

                              (in teragrams, unless indicated otherwise)
     Trace Gas
1985
                                           Emissions Estimates by Year
2000
2025
2050
2075
2100
     C02 (Pg C)
U.S. EPA #1
U.S. EPA #2
U.S. EPA #3
U.S. EPA #4
U.S. EPA #5
U.S. EPA #6
U.S. EPA #7
U.S. EPA #8
RCW
SCW
6.3
6.3
7.9
7.9
6.3
6.3
7.9
7.9
6.0
6.0
7.1
73
8.7
9.0
7.1
7.3
8.7
9.0
8,1
7.6
7.4
10.4
9.3
113
7.4
10.4
9.3
123
12.4
9.6
6.9
13.7
9.0
15.9
6.9
13.7
9.0
15.9
16.9
9.9
6.3
17.9
8.8
20.9
6.3
17.9
8.8
20.9
22.0
9.6
6.3
25.2
8.9
28.5
6.3
25.2
8.9
28.5
26.1
10.7
     CO (as C)
U.S. EPA #1
U.S. EPA #2
U.S. EPA #3
U.S. EPA #4
U.S. EPA #5
U.S. EPA #6
U.S. EPA #1
U.S. EPA #8
RCW
SCW
315.5
315.5
750.5
750.5
315.5
315.5
750.5
750.5
505.8
505.8
225.3 :
225.6
696.3
696.5
225.3
225.6
696.3
696.5
561.7
610.8
183.6
194.5
701.4
734.9
183.6
194.5
701.4
734.9
724.6
825.4
168.6
191.8
699.3
778,0
168.6
191.8
699.3
778.0
885.3
842.2
148.1
177.5
684.4
807.0
148.1
177.5
684.4
807.0
1052.3
614.1
143.5
192.1
691.6
892.7
143.5
192.1
691.6
892.7
1192.2
625.0
     CH,
U.S. EPA #1
U.S, EPA #2
U.S. EPA #3
U.S. EPA #4
U.S. EPA #5
U.S. EPA #6
U.S.JEPA#7
U.S. EPA #8
RCW
SCW
389.2
389.2
389.2
389.2
419.0
419.0
419.0
419.0
510.7
510.7
434.5
437.5
443.8
446.8
517.1
52Z5
522.2
527.6
590.1
581.0
508.4
530.2
531.6
553.6
674.5
726.7
6875
740.4
731.9
687.9
566.5
610.9
601.6
647.0
795.2
9185
815.6
941.1
901.1
748.4
618.7
669.0
664.1
717.6
903.6
1096.0
930.1
1131.7
. 1044.5
783.9
628.6
698.8
683.4
757.4
945.1
1252.9
978.7
1126.1
1126.1
829.7
     NOX (as N)
U.S. EPA #1
U.S. EPA #2
U.S. EPA #3
U.S. EPA #4
U.S. EPA #5
U.S. EPA #6
U.S. EPA #7
U.S. EPA #8
RCW .
SCW
40.4
59.4
40.4
59.4
40.4
59.4
40.4
59.4
54.2
54.2
345
58.6
35.5
60.1
345
58.6
355
60.1
62.4
61.2
28.0 -
64.1
31.2
68,9
28.0
64.1
31.2
68.9
79.2
71.1
26.2
72.1
31.0
80.2
26.2
72.1
31,0
80.2
95.4
72.2
23.3
824
29.9
95.2
23.3
82.4
29.9
95.2
110.4
66.7
23.2
103.6
30.7
120.1
23.2
103.6
30.7
120.1
121.6
69.0
                                             C-38

-------
                                                     Appendix C: Sensitivity Analyses
                                  TABLE C-5

       Comparison of Results From Atmospheric Chemistry Models for the Year 2050
                                Compared to 1985

MODEL                                 TEST CASE RESULTS
                                LOW CH.
HIGH CH4

Increases in Methane (ppb)
Low NOX
Prather - average
(minimum/maximum)
Isaksen
Thompson et al.
High NOX
Prather - average
' (minimum/maximum)
Isaksen
Thompson et al.
Percent Change in CO
Low NOX
Prather
Isaksen
Thompson et al.
High NOX
Prather
Isaksen
Thompson et al.
Percent Change in OH
Low NOX
Prather -- average
(minimum/maximum)
Isaksen
Thompson et al.
High NOX
Prather - average
(minimum/maximum)
Isaksen
Thompson et al.
Percent Change in O3
Low NOX
Prather -- average
(minimum/maximum)
Isaksen
Thompson et al.
High NOX
Prather - average
(minimum/maximum)
Isaksen
Thompson et al.
Low CO
U.S. EPA#1
806
(669/943)
400
1112
U.S. EPA#2
801
(658/944)
350
1331
U.S. EPA#1
16
-13
-12
U.S. EPA#2
17
-9
-1.5
U.S. EPA#1
-9
(-15/-2)
5
-9.6
U.S. EPA#2
-2
(-8/4)
8
-8.9
U.S. EPA#1
1
(-7/8)
-1
4.3
U.S. EPA#2
5
(-2/13)
5
12
High CO
U.S. EPA#3
1031
(901/1160)
720
1498
U.S. EPA#4
1048
(898/1197)
550
1740
U.S. EPA#3
43
8
25
U.S. EPA#4
44
8
36
U.S. EPA#3
-14
(-20/-9)
- 1
-16
U.S. EPA#4
-9
(-15/-2)
4
-15
U.S. EPA#3
8
(-1/17)
2
11
U.S. EPA#4
13
(5/22)
8
19
Low CO
U.S. EPA#5
1750
(1586/1914)
950
2555
U.S. EPA#6
2082
(1901/2264)
1010
3305
U.S. EPA#5
55
0
14
U.S. EPA#6
70
8
32
U.S. EPA#5
-23
(-30/-17)
1
-21
U.S. EPA#6
-22
(-29/-16)
5
-22
U.S. EPA#5
21
(8/34)
3
15
U.S. EPA#6
33
(18/47)
10
27
High CO
U.S. EPA#7
2022
(1734/2052)
1220
4306
U.S. EPA#8
2242
(2056/2427)
1200
3989
U.S.EPA#7
82
17
77
U.S. EPA#8
99
19.
78
U.S. EPA#7
-26
(-32/-20)
-2
-31
U.S. EPA#8
-25
(-32/-19)
3
-27
U.S. EPA#7
27
(13/41)
5
28
U.S. EPA#8
39
(24/55)
13
34
                                     C-39

-------
 Policy Options for Stabilizing Global Climate
 regions and  scaled to account for the CH4
 lifetime  changes  occurring in the perturbed
 atmosphere.   Also summarized are percent
 changes in CO (surface mixing ratios) and OH
 and O3  (column-integrated from  0-15 km).
 The CH4 changes obtained by the Thompson
• model are much  higher than those obtained
 with the AMAC, while the CO changes are
 somewhat less than the AMAC. Although not
 shown in the global averages in Table C-5, the
 most useful results of the regional calculations
 are localized estimates of OH and O3 changes
 in  each chemically defined region where CO
 and NOX growth rates may differ considerably.
 The differences between areas with controlled
 emissions  (Urban 1)  and  without  controlled
 emissions  (Urban 2)  are very striking (see
 Figure C-17).

      The   Isaksen   model   calculates
 perturbations as a function of latitude, altitude,
 (0-16 km), and time  of year.  The increase in
 CH4 is distributed uniformly throughout the
 troposphere as expected. There is  a problem
 with the implementation of the U.S. EPA #2
 scenario  in   that the  CH4  concentrations
 decline  at  the  beginning  of the   model
 integration.   This may be  due to  the low
 estimate of global CO flux.  Initial fluxes were
- scaled in the AMAC and Thompson models to
 obtain a steady-state of current concentrations.
 CH4  does   not  recover   to  its   initial
 concentration for at  least 20 years into the
 scenario, and this is probably the  reason for
 the Isaksen  model predicting  such  a small
 increase in CH4.  The patterns for OH and O3
 perturbations are distinct (see  Figure  C-18).
 The greatest changes in O3 are below 2 km
 altitude:  there is a large increase between 0°
 and 35°N  and a  small decrease centered at
 50°N.  The spatial pattern of changes in OH
 are interesting:  in the upper troposphere
 between 12 and  16 km the  OH increases by
 10-30% in the Northern Hemisphere, whereas
 throughout most  of the Southern Hemisphere
 OH decreases. Both of these changes may be
 driven by increases in CH4.  In the dry upper
 troposphere  in the  presence of NOX, CH4
 increases the OH concentration  during  its
 atmospheric  oxidation,  but  in  the  lower
 troposphere  the  CH4 provides merely  a sink
 for OH.

       Overall, all three models predict similar
 increases in tropospheric O3. The Thompson
et al. and AMAC models predict decreases in
tropospheric  OH,  while the  Isaksen model
reports  a  globally  averaged increase.   This
discrepancy may be  explained by  the  large
increases in OH above 12 km as noted above,
something  that  is  also calculated by the
Thompson  model.    However, most of the
difference in OH levels seems attributable to
the  lower  CO and  CH4  concentrations
calculated by Isaksen compared with the other
two models.  As shown in  Table C-5 for all
eight scenarios, none of the increases in CO by
2050  are  more than   15-20% in  Isaksen,
whereas Thompson et  al.  and AMAC  show
CO increases of 80-100%  (see scenarios #7
and #8). Some of the CO and OH differences
between  Isaksen et  al. and  the other  two
models  are   due   to  the  difference  in
initialization described above, but most of the
OH difference may be due to how CO behaves
in each model.  This may be one of the more
prominent uncertainties in predicting future.
tropospheric composition. CO has a moderate
lifetime (typically about a  few months) with
considerable spatial variability that is not well
resolved in any of  the  models.  Perhaps the
Isaksen model gives a lower limit to CO and
OH  changes,  and  the other two models
estimate the largest expected changes.

EVALUATION OF  UNCERTAINTIES
USING AMAC

      Comparing the results of AMAC to
other models given identical scenarios provides
one  approach to   evaluating uncertainties
related to atmospheric chemistry.   Valuable
information can also be obtained by testing the
robustness of the AMAC results to changes inN
critical  model parameters.   This section
examines  these impacts   by varying  key
parameters within AMAC and then comparing
the results to the RCW scenario.

Atmospheric Lifetime of CFC-11

      The assumed atmospheric lifetime for
CFC-11 in the AMAC for the RCW case was
65 years.  Its atmospheric  lifetime, however,
may range from 55 to 75 years (Prather, 1989);
these estimates were evaluated to  determine
the impact on atmospheric chemistry.  The
changes  in  atmospheric concentration for
CFC-11 are summarized in Figure C-19, which
indicates that  concentration levels may vary
                                           C-40

-------
                                            Appendix C: Sensitivity Analyses
                             FIGURE C-17
         REGIONAL DIFFERENCES FOR URBAN AREAS
         WITH DIFFERENT EMISSIONS OF CO AND NO
          Fractional Change: 1985-2060
        urDan 1
Fractional Change: 1985-2050
Source: Thompson et al, 1989.
                                C-41

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Policy Options for Stabilizing Global Climate
                                   FIGURE C-18
               2.00-j
                      OH AND  OZONE PERTURBATIONS

                      IN THE ISAKSEN AND HOV MODEL
                                  (Percent Change)

                                     Ozone
                  33  80  10 SO SO  40  SO 20 <3   0 -to -20 -SO -40 -SO -SO -10 -80 -90
                                                               LATITUCt'
                                        OH
               2.00
                  SO 80  10  SO SO 40  SO  20  to  3
                                             -
-------
                                      Appendix C: Sensitivity Analyses
                        FIGURE C-19





     SENSITIVITY OF ATMOSPHERIC CONCENTRATION



               OF CFC-11 TO ITS LIFETIME


             (Based on 3.0 Degree Celsius Sensitivity)
   900
   800
   700
   600
c
o
I-  500
9
a.

ta
  400
   300
   200
   100
     1985 2000
2025     2050


       Year
                            ...4 75 Years





                              RCW (65 Years)






                              55 Years
2075     2100
                           C-43

-------
Policy Options for Stabilizing Global Climate
from about 690 to 860 ppt by 2100.  Increases
(decreases) in the atmospheric concentration
of CFC-11, however, tend  to  be  offset  by
corresponding   decreases   (increases)   in
atmospheric  concentrations of .other trace
gases, such as other CFCs and CH4.  That is,
the increase (decrease) in the lifetime of CFC-
11  increases  (decreases)  the  amount  of
stratospheric  ozone depletion, which increases
(decreases) the amount of UV radiation; these
higher (lower) UV levels increase (decrease)
the rate of destruction of these other gases.
As a result, the impacts on global warming are
negligible  (less than 0.1°C).

Interaction of Chlorine with Column Ozone

      Chlorine  in  the   stratosphere has a
negative, non-linear impact on total column
ozone. This chemical interaction is one of the
primary   causes  of   stratospheric  ozone
depletion  due to the chlorine  contained in
CFCs; this interaction has been included in the
AMAC, however, primarily for its ability to
affect  the   rate  of  tropospheric  ozone
formation.  In the RCW case this relationship
was defined as a 0.03% decline in total column
ozone/(ppb)2  of stratospheric chlorine.   A
higher value, 0.20%, was evaluated, which
would increase  the  rate of column ozone
destruction.

      With   the  0.20%   assumption, total
column ozone depletion was 47-48% by 2050
(assuming  2.0-4.0°C  climate   sensitivities)
compared with a total column ozone depletion
of 17.5% with the lower value (i.e., the -0.03%
value  used in  the RCW case).  The increase in
total column ozone depletion has a positive
feedback on the tropospheric OH levels due to
the increase in UV radiation.  The  resulting
OH   interactions  with  other  trace  gases
substantially   reduces    the   atmospheric
concentration of  CH4,   HCFC-22,  methyl
chloroform, and methyl chloride, and reduces
the rate  of tropospheric  ozone formation.
(The  role of O3 is problematic, Oj at 10-12
km probably would increase. At this altitude,
O3 probably has the largest greenhouse effect;
see CHAPTER II.) These impacts reduce the
amount of global warming; as shown  in Figure
C-20,  the decline in realized wanning is 0.1°C
by 2050  compared  with  the RCW case, and
0.3-0.5°C by 2100; the decline in equilibrium
warming by 2100 is 0.4-0.8°C (assuming 2.0-
4.0°C climate sensitivities).

Sensitivity  of Tropospheric Ozone to CH4
Abundance

      Tropospheric  ozone  formation   is
affected  by the  amount  of CH4 present,
although the rate at which tropospheric ozone
forms as a result of CH4 abundance is subject
to some uncertainty. In the RCW case, this
variable  for the Northern  Hemisphere was
assumed to be a 0.2% change in tropospheric
ozone for  each percentage  change in CH4
concentration; other evidence suggests that a
higher value, 0.4%, is possible (Prather, 1989).

      Using this higher value increases the
change in tropospheric ozone in 2100 by about
50% over the RCW case (tropospheric ozone
increases by about 69% compared with about.
46% when a value of 0.2% is assumed).  The
increase  in  tropospheric  ozone  indirectly
results in a decrease in CH4 concentrations
since the tropospheric ozone increase also
increases OH formation, which destroys CH4.
Due to  this partially  offsetting effect, the
increase in global warming is less than 0.1°C.

Sensitivity of OH to NOX

      Tropospheric OH formation  is affected
by the level of NOX emissions,  although the
rate  of OH formation  is uncertain.   In the
RCW case, we assumed a 0.1% OH change for
every 1.0% change in NOX emissions for the
Northern Hemisphere.  We evaluated a range
of uncertainty from 0.05% to 0.2%.

      An increase (decrease) in the amount  of
OH due to a higher (lower) sensitivity to NOX
emissions results in less (more) tropospheric
ozone  formation as well as  lower (higher)
levels of CO and CH4.  The higher  sensitivity
value of 0.2% reduces realized warming about
0.1°C by 2100 compared with the RCW case
(assuming   2.0-4.0°C   climate   sensitivities;
equilibrium warming is  about 0.1-0.2°C lower
by 2100), while the  lower sensitivity value  of
0.05% increases realized warming  less than
0.1°C  by 2100 (the   equilibrium   warming
increase is also  less than 0.1°C by 2100).
                                           C-44

-------
                                      Appendix C: Sensitivity Analyses
                       FIGURE C-20



            INCREASE IN REALIZED WARMING


   DUE TO RATE OF INTERACTION OF Clx WITH OZONE


               (Based on 3.0 Degree Sensitivity)
w

la
"i
u
(A
e
o

D)
0)
Q
                                                 RCW
                                                 Clx/Ozone
                                                 Interaction
     1985 2000
2025
  2050

Year
2075
2100
                          C-45

-------
 Policy Options for Stabilizing Global Climate
 BIOGEOCHEMICAL FEEDBACKS

      The sensitivity of the climate system to
 anthropogenic perturbations is determined by
 a  combination  of feedbacks that amplify or
 dampen  the  direct  radiative  effects  of
.increasing concentrations of greenhouse gases.
 Several important internal climate feedbacks,
 such as those resulting from changes in water
 vapor, clouds, and sea ice albedo, are included
 in the estimates of climate sensitivity discussed
 throughout this report. There are a number of
 feedbacks of a biogeochemical origin, however,
 that may also  play  an important  role in
 climatic change that were not included in the
 analyses  on  which this  range  is based.
 Biogeochemical  sources of feedback include
 releases of methane hydrates; changes in ocean
 chemistry, biology,  and  circulation;   and
 changes in the albedo of the global vegetation.

      Any attempt to quantify the impact of
 biogeochemical feedbacks is necessarily quite
 speculative at  this time; however,  it  does
 appear  that  they could have an  important
 impact  on  global  climate.   For example,
 Lashof (1989) has estimated that the gain from
 biogeochemical feedbacks ranges from  0.05-
 0.29 compared with  a 0.17-0.77 gain  from
 internal climate  feedbacks.   (The  gain is
 defined as the portion of global equilibrium
 temperature  change  attributable  to  the
 feedback  divided  by  the   total   global
 equilibrium temperature when the feedback is
 included). Some of these key feedbacks were
 incorporated  into  the  AMAC for  these
 sensitivity cases to determine the magnitude of
 their impact on global warming.

 Ocean Circulation

      As  mentioned  above, the oceans are
 currently  a  major  sink 'for heat  and  CO2.
 Concerns have been raised, however, that the
 basic  circulation patterns  that allow these
 processes to continue could be significantly
 altered  as the global  climate changes.  This
 possibility is suggested by  the  rapid rate of
 atmospheric CO2 change during past periods
 of climate change (e.g., see CHAPTER III). If
 circulation patterns did change, it is plausible
 that the oceans would no longer be a net sink
 for heat and CO2.
      It is not known at what point ocean
circulation would be altered.  For this analysis
we assumed that a 2°C increase  in  realized
warming would alter ocean circulation patterns
sufficiently to shut off net uptake of CO2 and
heat by the  oceans.   This would increase
atmospheric CO2concentrations from 10-13%
by 2100,  and would  reduce the  difference
between realized and equilibrium warming as
the atmosphere warmed more quickly due to
the oceans' inability to continue to act as a
heat sink.  As shown in Figure  C-21, this
feedback  is sufficient to increase  realized
warming up to 1.6°C by 2050 and 1.3-3.6°C by
2100 compared with the warming estimated for
the RCW  case.

Methane Feedbacks

      Increases in global temperature could
increase the amount of CH4 emissions due to
several  feedback  processes:   (1)  release  of
methane from hydrates, which  are methane
compounds contained in continental slope
sediments,  as   increasing   temperatures
destabilize the  formations;  (2)   additional
methane from high-latitude bogs due to longer
growing seasons and higher temperatures; and
(3) increased rate of methanogenesis from rice
cultivation. The amount of CH4 that could be
released   from  each  of   these   feedback
processes,  and the rate at which any releases
might occur, are highly speculative.  For each
process we have assumed that the rate of CH4
release is  linearly  related to the increase in
temperature, with each 1°C increase leading to
an additional 110 Tg from methane hydrates,
12  Tg  from  bogs,  and  7  Tg  from  rice
cultivation (Lashof, 1989).   These methane,
feedbacks  could  have a major  impact   on
atmospheric CH4  concentrations:   by 2100
concentrations would increase to about 6900-
8050 ppb, compared with 4300-4550 ppb in the
RCW case.  As shown in Figure  C-22, this
increase in CH4 would be sufficient to increase
realized wanning relative to the  RCW case
about 0.1-0.3°C by 2050 and 0.4-0.8°C by 2100
(assuming 2.0-4.0°C climate sensitivities).

Combined Feedbacks

      In  addition  to  the  two  separate
feedbacks  discussed above, we  analyzed  the
                                           C-46

-------
                                 Appendix C: Sensitivity Analyses
                  FIGURE C-21
       INCREASE IN REALIZED WARMING

    DUE TO CHANGE IN OCEAN CIRCULATION
          (Based on 3.0 Degree Sensitivity)
1985 2000
2025     2050
       Year
2075
                                          1 Ocean
                                         /  Circulation
                                            RCW
2100
                     C-47

-------
Policy Options for Stabilizing Global Climate
                           FIGURE C-22
        5  l
    10
    3
    o
    I   3
    «
    O>
    O
                INCREASE IN REALIZED WARMING

                 DUE TO METHANE FEEDBACKS
                   (Based on 3.0 Degree Sensitivity)
                                                     Methane
                                                   •'•' Feedbacks


                                                     RCW
        1985  2000
2025     2050

       Year
2075
2100
                              C-48

-------
                                                             Appendix C:  Sensitivity Analyses
combined   impact  of  several  types  of
biogeochemical  feedbacks.    The  following
specific feedbacks were included: (1) methane
from  hydrates,  bogs, and rice cultivation, as
previously discussed; (2)  increased stability of
the thermocline, thereby slowing the rate of
heat and CO2  uptake  by the  deep ocean by
30% due to  less mixing; (3) vegetation albedo,
which is a decrease in global albedo as a result
of changes  in  the distribution of terrestrial
ecosystems  by  0.06%  per 1°C warming;  (4)
disruption of existing ecosystems, resulting in
transient reductions in biomass and soil carbon
at the rate of 0.5 Pg C per year  per 1°C
warming; and (5) CO2 fertilization, which is an
increase in the amount of carbon stored in the
biosphere in response to higher CO2 concen-
trations at the rate of 0.3 Pg C per ppm.  See
Lashof (1989) for further discussion.

      The combined impact of these feedbacks
on realized warming is an increase of 0.3-0.7°C
by 2050 and 0.7-2.2°C by 2100 relative to the
RCW  case   (assuming  2.0-4.0°C   climate
sensitivities; see Figure C-23); the increase in
equilibrium warming is 0.2-1.3°C by 2050 and
0.6-2.8°C by 2100. These preliminary analyses
strongly suggest that biogeochemical feedbacks
could have a major impact  on the  rate of
climatic change during the next century.
                                            C-49

-------
Policy Options for Stabilizing Global Climate
                           FIGURE C-23



                INCREASE IN REALIZED WARMING


          DUE TO CHANGE IN COMBINED FEEDBACKS

                   (Based on 3,0 Degree Sensitivity)
       6  —
     to


     | 4-

     O
     «
     *
     1)

     O)
       2  h
         1985  2000
                                                    Combined
                                                    Feedbacks
                                                     RCW
2025     2050

       Year
2075     2100
                             C-50

-------
                                                           Appendix C:  Sensitivity Analyses
NOTES

1.  Pg = petagram; 1 petagram = 1015 grams.

2.  EJ = exajoule; 1 exajoule = 1018 joules.

3.  Tg = teragram; 1 teragram  = 1012 grams.


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-------